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1. WO2020115523 - SUIVI DE SOUS-ESPACE BIDIMENSIONNEL ET FORMATION DE FAISCEAUX POUR SYSTÈMES D'ANTENNE ACTIVE

Note: Texte fondé sur des processus automatiques de reconnaissance optique de caractères. Seule la version PDF a une valeur juridique

[ EN ]

TWO-DIMENSIONAL SUBSPACE TRACKING AND BEAMFORMING FOR

ACTIVE ANTENNA SYSTEMS

TECHNICAL FIELD

Wireless communications and in particular to subspace tracking for performing Multiple Input Multiple Output (MIMO) related operations in a wireless communication network.

BACKGROUND

Massive Multiple Input Multiple Output (MIMO) is one technology that is incorporated in 4G+ wireless communication systems. Massive MIMO can provide significant capacity improvements over current solutions by using spatial multiplexing of multiple transmission layers either to a single user MIMO (SU-MIMO) or to multiple users MIMO (MU-MIMO). Downlink SU- and MU-MIMO precoding may require instantaneous channel state information at a transmitter (CSIT). Receiving CSIT can be challenging especially in frequency division duplex (FDD) systems as it may require a significant amount of feedback from the wireless device, e.g., user equipment (UE), to the network node, e.g., base station.

Using long-term channel state information, e.g., the covariance matrix of the channel, has been proposed for downlink Massive MIMO beamforming to decrease the overhead of instantaneous CSIT acquisition. Furthermore, several

computationally-efficient algorithms for estimating and tracking the dominant Eigen vectors of the channel covariance matrix have also been proposed. For example, a projection approximation subspace tracking algorithm was used to develop adaptive MU-MIMO precoding algorithms using the tracked principal Eigen vector of each wireless device. Only the dominant Eigen vector of each wireless device was utilized for co-scheduling decisions and downlink beamforming. As a result, these adaptive MU-MIMO precoding algorithms do not have sufficient robustness against multipath propagation effects that cause the signal subspace of each wireless device to have a rank much higher than one.

However, these low-complexity adaptive downlink MU-MIMO beamforming algorithms that may only consider one Eigen vector such as the dominant Eigen

vector for each wireless device may not be able to effectively suppress MU-MIMO interference in non-line-of-sight (NLOS) propagation conditions.

Another MU-MIMO precoding scheme was also proposed where this scheme utilizes projection approximation subspace tracking for tracking multiple

Eigenvectors of the covariance matrix of the channel of each wireless device. The tracked Eigen vectors were used for computing adaptive downlink MU-MIMO precoders for the paired wireless devices for suppressing the MU-MIMO interference as well as achieving good beamforming gain even in environments with severe multipath propagation.

However, this MU-MIMO precoding scheme may have complexity issues.

For example, this MU-MIMO precoding scheme employs subspace tracking of multiple Eigen vectors of the channel covariance matrix. For a network node with two-dimensional polarized array configuration, the tracked Eigen vectors correspond to the full dimension channel per polarization, i.e., the dimension of each Eigen vector is equal to the number (quantity) of antennas at the network node. Since the computational complexity of this MU-MIMO precoding scheme is proportional to the square of the dimension of the Eigen vectors, implementing this MU-MIMO precoding scheme in real-time can be difficult if the number (quantity) of antennas at the network node increased beyond 32 elements.

SUMMARY

In one study on the correlation properties of three-dimensional channels, it was shown that the covariance matrix of a three-dimensional channel can be well-approximated by the Kronecker product of the azimuth and elevation covariance matrices. As a result, a reduced complexity codebook that consists of the Kronecker product of separate azimuth and elevation codebooks was proposed. The Kronecker product codebook was shown to provide a performance close to that of the full codebook, yet with reduced codebook size.

The instant disclosure advantageously builds upon at least a portion of this study to compress the signal subspace information by decomposing the covariance matrix of the full channel to all the antenna elements of the network node to two matrices with reduced dimensions. This provides significant memory savings and

enables the network node, e.g., base station, to track a larger quantity of wireless devices for a fixed memory limitation. Further, one or more algorithms described herein may be applied for SU-MIMO precoding and MU-MIMO scheduling and precoding with a computational complexity that scales favorably with the quantity of antenna elements at the network node, i.e., the complexity may be less than the schemes described in the background section. For example, the computational complexity of the algorithm(s) described herein is lower than that of covariance-based precoding algorithms with full-dimension subspace tracking and precoding. In one or more embodiments, the full-dimensional uplink channel for a wireless device is estimated based at least in part on the tracked signal subspace. In one or more embodiments, the signal subspace information may be decomposed into two or more directions or matrices.

According to one aspect of the disclosure, a network node is provided. The network node includes processing circuitry configured to: obtain measurement information, separately track a first direction and a second direction of a signal subspace of a covariance matrix of a channel based at least in part on the obtained measurement information where the first direction being different from the second direction, and optionally perform at least one Multiple Input Multiple Output, MEMO, related operation based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel.

According to one or more embodiments of this aspect, the first direction is an azimuth direction and the second direction is an elevation direction. According to one or more embodiments of this aspect, the processing circuitry is configured to: track the first direction of the signal subspace of the covariance matrix of the channel by tracking Eigen vectors associated with the first direction; and track the second direction of the signal subspace of the covariance matrix of the channel by tracking Eigen vectors associated with the second direction. According to one or more embodiments of this aspect, a quantity of tracked Eigen vectors of the first direction of the signal subspace of the covariance matrix is different from a quantity of tracked Eigen vectors of the second direction of the signal subspace of the covariance matrix.

According to one or more embodiments of this aspect, the quantity of tracked Eigen vectors of the second direction of the signal subspace of the covariance matrix is greater than the quantity of tracked Eigen vectors of the first direction of the signal subspace of the covariance matrix. According to one or more embodiments of this aspect, the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel is configured to estimate signal subspace information of the channel by decomposing a channel matrix of the channel into two directional covariance matrices having reduced dimensions compared to the channel covariance matrix.

According to one or more embodiments of this aspect, the processing circuitry is further configured to determine Eigen values of the channel covariance matrix based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel. According to one or more embodiments of this aspect, the processing circuitry is further configured to determine a single user-MIMO, SU-MIMO, precoder for a wireless device based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel. According to one or more embodiments of this aspect, the processing circuitry is further configured to determine a subset of a plurality of wireless devices for multiple user-MIMO, MU-MIMO, co-scheduling based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel.

According to one or more embodiments of this aspect, the processing circuitry is further configured to determine MU-MIMO precoders for the subset of the plurality of wireless devices based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel.

According to another aspect of the disclosure, a method for a network node is provided. Measurement information is obtained. A first direction and a second direction of a signal subspace of a covariance matrix of a channel are separately tracked based at least in part on the obtained measurement information where the first direction being different from the second direction. At least one Multiple Input Multiple Output, MIMO, related operation is optionally performed based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel.

According to one or more embodiments of this aspect, the first direction is an azimuth direction and the second direction is an elevation direction. According to one or more embodiments of this aspect, the first direction of the signal subspace of the covariance matrix of the channel is tracked by tracking Eigen vectors associated with the first direction; and the second direction of the signal subspace of the covariance matrix of the channel is tracked by tracking Eigen vectors associated with the second direction. According to one or more embodiments of this aspect, a quantity of tracked Eigen vectors of the first direction of the signal subspace of the covariance matrix is different from a quantity of tracked Eigen vectors of the second direction of the signal subspace of the covariance matrix.

According to one or more embodiments of this aspect, the quantity of tracked Eigen vectors of the second direction of the signal subspace of the covariance matrix is greater than the quantity of tracked Eigen vectors of the first direction of the signal subspace of the covariance matrix. According to one or more embodiments of this aspect, the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel is configured to estimate signal subspace information of the channel by decomposing a channel matrix of the channel into two directional covariance matrices having reduced dimensions compared to the channel covariance matrix. According to one or more embodiments of this aspect, Eigen values of the channel covariance matrix are determined based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel. According to one or more embodiments of this aspect, a single user-MIMO, SU-MIMO, precoder for a wireless device is determined based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel.

According to one or more embodiments of this aspect, a subset of a plurality of wireless devices for multiple user-MIMO, MU-MIMO, co-scheduling is determined based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel. According to one or more embodiments of this aspect, MU-MIMO precoders for the subset of the plurality of wireless devices is determined based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel.

According to another aspect of the disclosure, a network node is provided.

The network node includes processing circuitry configured to: obtain measurement information, perform two dimensional subspace tracking based at least in part on the obtained measurement information where a first direction and a second direction of the two dimensional subspace of a covariance matrix of a channel being tracked separately and the first direction being different from the second direction, estimate dominant Eigen vectors and corresponding Eigen vectors of the channel covariance matrix of the channel based on the two dimensional subspace tracking, and optionally perform at least one Multiple Input Multiple Output, MIMO, related operation based on two dimensional subspace tracking.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present embodiments, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:

FIG. 1 is a schematic diagram of an exemplary network architecture illustrating a communication system connected via an intermediate network to a host computer according to the principles in the present disclosure;

FIG. 2 is a block diagram of a host computer communicating via a network node with a wireless device over an at least partially wireless connection according to some embodiments of the present disclosure;

FIG. 3 is a flowchart illustrating exemplary methods implemented in a communication system including a host computer, a network node and a wireless device for executing a client application at a wireless device according to some embodiments of the present disclosure;

FIG. 4 is a flowchart illustrating exemplary methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data at a wireless device according to some embodiments of the present disclosure;

FIG. 5 is a flowchart illustrating exemplary methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data from the wireless device at a host computer according to some embodiments of the present disclosure;

FIG. 6 is a flowchart illustrating exemplary methods implemented in a communication system including a host computer, a network node and a wireless device for receiving user data at a host computer according to some embodiments of the present disclosure;

FIG. 7 is a flowchart of an exemplary process in a network node according to some embodiments of the present disclosure;

FIG. 8 is a diagram of a uniformly-spaced dual polarized array;

FIG. 9 is a flowchart of an example two-dimensional subspace tracking process according to some embodiments of the present disclosure;

FIG. 10 is a flowchart of a MU-MIMO pairing and precoding process according to some embodiments of the disclosure;

FIG. 11 is a graph comparing the SU- and MU-MIMO processes according to some embodiments of the present disclosure with existing processes; and

FIG. 12 is a flowchart of an exemplary process in a wireless device according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

The instant disclosure describes a method, system and network node where the network node may employ/implement a two-dimensional antenna array for communicating with one or more wireless devices. The network node may measure one or more reference signals such as uplink sounding or demodulation reference signals from the wireless devices to estimate the full-dimension uplink channel of each wireless device. In one or more embodiments, two subspace tracking algorithms are used to track the signal spaces of the azimuth and elevation covariance matrices, separately, over time per wireless device by selecting the azimuthal and vertical components of the full-dimension channel estimates and then tracking their respective signal subspaces. The tracked azimuth and elevation signal space information can be used jointly for performing one or more MIMO related operations such as performing downlink SU-MIMO precoding, for evaluating MU-MIMO wireless device pairing decisions, and/or for computing adaptive downlink MU-MIMO precoders for the paired wireless devices where such operation(s) can be performed with reduced computational complexity, as described herein. In one or more embodiments, “precoder” refers to a precoding configuration and/or design to be implemented and/or performed, e.g., implementation of downlink MU-MIMO precoding according to a downlink MU-MIMO precoder. In one or more embodiments, a precoder is implemented by hardware and/or software at an entity such as the hardware (e.g., processing circuitry) and/or software (instructions in memory) of one or more of a network node and wireless device described herein.

Before describing in detail exemplary embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to subspace tracking for performing a MEMO related operation. Accordingly, components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

As used herein, relational terms, such as“first” and“second,”“top” and “bottom,” and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms“a”,“an” and“the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,”“comprising,”“includes” and/or“including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

In embodiments described herein, the joining term,“in communication with” and the like, may be used to indicate electrical or data communication, which may be accomplished by physical contact, induction, electromagnetic radiation, radio signaling, infrared signaling or optical signaling, for example. One having ordinary skill in the art will appreciate that multiple components may interoperate and modifications and variations are possible of achieving the electrical and data communication.

In some embodiments described herein, the term“coupled,”“connected,” and the like, may be used herein to indicate a connection, although not necessarily directly, and may include wired and/or wireless connections.

The term“network node” used herein can be any kind of network node comprised in a radio network which may further comprise any of base station (BS), radio base station, base transceiver station (BTS), base station controller (BSC), radio network controller (RNC), g Node B (gNB), evolved Node B (eNB or eNodeB), Node B, multi-standard radio (MSR) radio node such as MSR BS, multi-cell/multicast coordination entity (MCE), relay node, donor node controlling relay, radio access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU) Remote Radio Head (RRH), a core network node (e.g., mobile management entity (MME), self-organizing network (SON) node, a coordinating node, positioning node, MDT node, etc.), an external node (e.g., 3rd party node, a node external to the current network), nodes in distributed antenna system (DAS), a spectrum access system (SAS) node, an element management system (EMS), etc. The network node may also comprise test equipment. The term“radio node” used herein may be used to also denote a wireless device (WD) such as a wireless device (WD) or a radio network node.

In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) are used interchangeably. The WD herein can be any type of wireless device capable of communicating with a network node or another WD over radio signals, such as wireless device (WD). The WD may also be a radio communication device, target device, device to device (D2D) WD, machine type WD or WD capable of machine to machine communication (M2M), low-cost and/or low-complexity WD, a sensor equipped with WD, Tablet, mobile terminals, smart phone, laptop embedded equipped (LEE), laptop mounted equipment (LME), USB dongles, Customer

Premises Equipment (CPE), an Internet of Things (IoT) device, or a Narrowband IoT (NB-IOT) device etc.

Also, in some embodiments, the generic term“radio network node” is used. It can be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-cell/multicast Coordination Entity (MCE), relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

An indication generally may explicitly and/or implicitly indicate the information it represents and/or indicates. Implicit indication may for example be based on position and/or resource used for transmission. Explicit indication may for example be based on a parametrization with one or more parameters, and/or one or more index or indices, and/or one or more bit patterns representing the information. It may in particular be considered that control signaling as described herein, based on the utilized resource sequence, implicitly indicates the control signaling type.

The term signal used herein can be any physical signal or physical channel. Examples of downlink physical signals are reference signal such as Primary

Synchronization Signal (PSS), Secondary Synchronization Signal (SSS), Cell Specific Reference Signal (CRS), Positioning Reference Signal (PRS), Channel State

Information Reference Signal (CSI-RS), Demodulation Reference Signal (DMRS), Narrowband Reference Signal (NRS), Narrowband Primary Synchronization Signal (NPSS), Narrowband Secondary Synchronization Signal (NSSS), Synchronization Signals (SS), Multimedia Broadcast Single Frequency Reference Signal (MBSFN RS) etc. Examples of uplink physical signals are reference signal such as Sounding Reference Signal (SRS), DMRS, etc. The term physical channel (e.g., in the context of channel reception) used herein is also called as“channel.” The physical channel carries higher layer information (e.g. RRC, logical control channel, etc.). Examples of downlink physical channels are Physical Broadcast Channel (PBCH), Narrowband Physical Broadcast Channel (NPBCH), Physical Downlink Control Channel

(PDCCH), Physical Downlink Shared Channel (PDSCH), short Physical Downlink Shared Channel (sPDSCH), Machine Type Communication (MTC) physical downlink control channel (MPDCCH), Narrowband Physical Downlink Control Channel

(NPDCCH), Narrow Physical Downlink Shared Channel NPDSCH, Enhanced Physical Downlink Control Channel (E-PDCCH), etc. Examples of uplink physical channels are short Physical Uplink Control Channel (sPUCCH). shorten Physical Uplink Shared Channel (sPUSCH), Physical Uplink Shared Channel (PUSCH), Physical Uplink Control Channel (PUCCH), Narrowband Physical Uplink Shared Channel (NPUSCH), Physical Random Access Channel (PRACH), Narrowband Physical Random Access Channel (NPRACH), etc.

A channel may generally be a logical or physical channel. A channel may comprise and/or be arranged on one or more carriers, in particular a plurality of subcarriers. A wireless communication network may comprise at least one network node, in particular a network node as described herein. A terminal connected or communicating with a network may be considered to be connected or communicating with at least one network node, in particular any one of the network nodes described herein.

Transmitting in downlink may pertain to transmission from the network or network node to the terminal. Transmitting in uplink may pertain to transmission from the terminal to the network or network node. Transmitting in sidelink may pertain to (direct) transmission from one terminal to another. Uplink, downlink and sidelink (e.g., sidelink transmission and reception) may be considered communication directions. In some variants, uplink and downlink may also be used to described wireless communication between network nodes, e.g. for wireless backhaul and/or relay communication and/or (wireless) network communication for example between base stations or similar network nodes, in particular communication terminating at such. It may be considered that backhaul and/or relay communication and/or network communication is implemented as a form of sidelink or uplink communication or similar thereto.

Configuring a terminal or wireless device or node may involve instructing and/or causing the wireless device or node to change its configuration, e.g., at least one setting and/or register entry and/or operational mode. A terminal or wireless device or node may be adapted to configure itself, e.g., according to information or data in a memory of the terminal or wireless device. Configuring a node or terminal or wireless device by another device or node or a network may refer to and/or comprise transmitting information and/or data and/or instructions to the wireless device or node by the other device or node or the network, e.g., allocation data (which may also be and/or comprise configuration data) and/or scheduling data and/or scheduling grants. Configuring a terminal may include sending allocation/configuration data to the terminal indicating which modulation and/or encoding to use. A terminal may be configured with and/or for scheduling data and/or to use, e.g., for transmission, scheduled and/or allocated uplink resources, and/or, e.g., for reception, scheduled and/or allocated downlink resources. Uplink resources and/or downlink resources may be scheduled and/or provided with allocation or configuration data.

Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE and/or New Radio (NR) (also referred to as“5G”), may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the aforementioned system. Other wireless systems, including without limitation Wide Band Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB) and Global System for Mobile Communications (GSM), may also benefit from exploiting the ideas covered within this disclosure.

Note further, that functions described herein as being performed by a wireless device or a network node may be distributed over a plurality of wireless devices and/or network nodes. In other words, it is contemplated that the functions of the network node and wireless device described herein are not limited to performance by a single physical device and, in fact, can be distributed among several physical devices.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

One or more embodiments described herein advantageously provide subspace tracking for performing a MIMO related operation.

Referring now to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 1 a schematic diagram of a

communication system 10, according to an embodiment, such as a 3GPP-type cellular network that may support standards such as LTE and/or NR (5G), which comprises an access network 12, such as a radio access network, and a core network 14. The access network 12 comprises a plurality of network nodes 16a, 16b, 16c (referred to collectively as network nodes 16), such as NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area 18a, 18b, 18c (referred to collectively as coverage areas 18). Each network node 16a, 16b, 16c is connectable to the core network 14 over a wired or wireless connection 20. A first wireless device (WD) 22a located in coverage area 18a is configured to wirelessly connect to, or be paged by, the corresponding network node 16c. A second WD 22b in coverage area 18b is wirelessly connectable to the corresponding network node 16a. While a plurality of WDs 22a, 22b (collectively referred to as wireless devices 22) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole WD is in the coverage area or where a sole WD is connecting to the corresponding network node 16. Note that although only two WDs 22 and three network nodes 16 are shown for convenience, the communication system may include many more WDs 22 and network nodes 16.

Also, it is contemplated that a WD 22 can be in simultaneous communication and/or configured to separately communicate with more than one network node 16 and more than one type of network node 16. For example, a WD 22 can have dual connectivity with a network node 16 that supports LTE and the same or a different network node 16 that supports NR. As an example, WD 22 can be in communication with an eNB for LTE/E-UTRAN and a gNB for NR/NG-RAN.

The communication system 10 may itself be connected to a host computer 24, which may be embodied in the hardware and/or software of a standalone server, a cloud-implemented server, a distributed server or as processing resources in a server farm. The host computer 24 may be under the ownership or control of a service provider, or may be operated by the service provider or on behalf of the service provider. The connections 26, 28 between the communication system 10 and the host computer 24 may extend directly from the core network 14 to the host computer 24 or may extend via an optional intermediate network 30. The intermediate network 30 may be one of, or a combination of more than one of, a public, private or hosted network. The intermediate network 30, if any, may be a backbone network or the Internet. In some embodiments, the intermediate network 30 may comprise two or more sub-networks (not shown).

The communication system of FIG. 1 as a whole enables connectivity between one of the connected WDs 22a, 22b and the host computer 24. The connectivity may be described as an over-the-top (OTT) connection. The host computer 24 and the connected WDs 22a, 22b are configured to communicate data and/or signaling via the OTT connection, using the access network 12, the core network 14, any intermediate network 30 and possible further infrastructure (not shown) as intermediaries. The OTT connection may be transparent in the sense that at least some of the participating communication devices through which the OTT connection passes are unaware of routing of uplink and downlink communications. For example, a network node 16 may not or need not be informed about the past routing of an incoming downlink communication with data originating from a host computer 24 to be forwarded (e.g., handed over) to a connected WD 22a. Similarly, the network node 16 need not be aware of the future routing of an outgoing uplink communication originating from the WD 22a towards the host computer 24.

A network node 16 is configured to include a subspace tracking unit 32 which is configured to perform at least one network node 16 function/operation as described herein.

Example implementations, in accordance with an embodiment, of the WD 22, network node 16 and host computer 24 discussed in the preceding paragraphs will now be described with reference to FIG. 2. In a communication system 10, a host computer 24 comprises hardware (HW) 38 including a communication interface 40 configured to set up and maintain a wired or wireless connection with an interface of a different communication device of the communication system 10. The host computer 24 further comprises processing circuitry 42, which may have storage and/or processing capabilities. The processing circuitry 42 may include a processor 44 and memory 46. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 42 may comprise

integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 44 may be configured to access (e.g., write to and/or read from) memory 46, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only Memory).

Processing circuitry 42 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by host computer 24. Processor 44 corresponds to one or more processors 44 for performing host computer 24 functions described herein. The host computer 24 includes memory 46 that is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 48 and/or the host application 50 may include instructions that, when executed by the processor 44 and/or processing circuitry 42, causes the processor 44 and/or processing circuitry 42 to perform the processes described herein with respect to host computer 24. The instructions may be software associated with the host computer 24.

The software 48 may be executable by the processing circuitry 42. The software 48 includes a host application 50. The host application 50 may be operable to provide a service to a remote user, such as a WD 22 connecting via an OTT connection 52 terminating at the WD 22 and the host computer 24. In providing the service to the remote user, the host application 50 may provide user data which is transmitted using the OTT connection 52. The“user data” may be data and information described herein as implementing the described functionality. In one embodiment, the host computer 24 may be configured for providing control and functionality to a service provider and may be operated by the service provider or on behalf of the service provider. The processing circuitry 42 of the host computer 24 may enable the host computer 24 to observe, monitor, control, transmit to and/or receive from the network node 16 and or the wireless device 22. The processing circuitry 42 of the host computer 24 may include an information unit 54 configured to enable the service provider to one or more of transmit, receive, forward, determine, communicate and store information related to tracking of the signal subspace described herein and/or at least one MIMO related operation that is based on the subspace tracking.

The communication system 10 further includes a network node 16 provided in a communication system 10 and including hardware 58 enabling it to communicate with the host computer 24 and with the WD 22. The hardware 58 may include one or more antennas 59 (collectively referred to as antenna 59) such as a two-dimensional antenna array as described herein, for transmitting to and/or receiving from the wireless device 22 and/or one or more entities in system 10. The hardware 58 may include a communication interface 60 for setting up and maintaining a wired or wireless connection with an interface of a different communication device of the communication system 10, as well as a radio interface 62 for setting up and maintaining at least a wireless connection 64 with a WD 22 located in a coverage area 18 served by the network node 16. The radio interface 62 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and/or one or more RF transceivers. The communication interface 60 may be configured to facilitate a connection 66 to the host computer 24. The connection 66 may be direct or it may pass through a core network 14 of the communication system 10 and/or through one or more intermediate networks 30 outside the communication system 10.

In the embodiment shown, the hardware 58 of the network node 16 further includes processing circuitry 68. The processing circuitry 68 may include a processor 70 and a memory 72. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 68 may comprise integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 70 may be configured to access (e.g., write to and/or read from) the memory 72, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only Memory).

Thus, the network node 16 further has software 74 stored internally in, for example, memory 72, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node 16 via an external connection. The software 74 may be executable by the processing circuitry 68. The processing circuitry 68 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by network node 16. Processor 70 corresponds to one or more processors 70 for performing network node 16 functions described herein. The memory 72 is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 74 may include instructions that, when executed by the processor 70 and/or processing circuitry 68, causes the processor 70 and/or processing circuitry 68 to perform the processes described herein with respect to network node 16. For example, processing circuitry 68 of the network node 16 may include subspace tracking unit 32 configured to perform at least one network node 16 function/operation as described herein. In one or more embodiments, network node 16 such as via one or more of subspace tracking unit 32, processor 70, processing circuitry 68, communication interface 60 and radio interface 62 is configured to perform precoding implemented by one or more of the precoders described herein, e.g., MU-MIMO precoder.

The communication system 10 further includes the WD 22 already referred to. The WD 22 may have hardware 80 that may include one or more antennas 89

(collectively referred to as antenna 89) such as a two-dimensional antenna array as described herein, for transmitting to and/or receiving from the network node 16 and/or one or more entities in system 10. The WD 22 may have hardware 80 that may include a radio interface 82 configured to set up and maintain a wireless connection 64 with a network node 16 serving a coverage area 18 in which the WD 22 is currently located. The radio interface 82 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and/or one or more RF transceivers.

The hardware 80 of the WD 22 further includes processing circuitry 84. The processing circuitry 84 may include a processor 86 and memory 88. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 84 may comprise integrated circuitry for processing and/or control, e.g., one or more processors and/or processor cores and/or FPGAs (Field Programmable Gate Array) and/or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 86 may be configured to access (e.g., write to and/or read from) memory 88, which may comprise any kind of volatile and/or nonvolatile memory, e.g., cache and/or buffer memory and/or RAM (Random Access Memory) and/or ROM (Read-Only Memory) and/or optical memory and/or EPROM (Erasable Programmable Read-Only Memory).

Thus, the WD 22 may further comprise software 90, which is stored in, for example, memory 88 at the WD 22, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the WD 22. The software 90 may be executable by the processing circuitry 84. The software 90 may include a client application 92. The client application 92 may be operable to provide a service to a human or non-human user via the WD 22, with the support of the host computer 24. In the host computer 24, an executing host application 50 may communicate with the executing client application 92 via the OTT connection 52 terminating at the WD 22 and the host computer 24. In providing the service to the user, the client application 92 may receive request data from the host application 50 and provide user data in response to the request data. The OTT connection 52 may transfer both the request data and the user data. The client application 92 may interact with the user to generate the user data that it provides.

The processing circuitry 84 may be configured to control any of the methods and/or processes described herein and/or to cause such methods, and/or processes to be performed, e.g., by WD 22. The processor 86 corresponds to one or more processors 86 for performing WD 22 functions described herein. The WD 22 includes memory 88 that is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software 90 and/or the client application 92 may include instructions that, when executed by the processor 86 and/or processing circuitry 84, causes the processor 86 and/or processing circuitry 84 to perform the processes described herein with respect to WD 22. For example, the processing circuitry 84 of the wireless device 22 may include a MIMO unit 34 configured to perform at least one wireless device 22 function/operation as described herein. In one or more embodiments, wireless device 22 such as via one or more of MIMO unit 34, processor 86, processing circuitry 84, radio interface 82 and client application 92 is configured to perform precoding implemented by one or more of the precoders described herein, e.g., MU-MIMO precoder.

In some embodiments, the inner workings of the network node 16, WD 22, and host computer 24 may be as shown in FIG. 2 and independently, the surrounding network topology may be that of FIG. 1.

In FIG. 2, the OTT connection 52 has been drawn abstractly to illustrate the communication between the host computer 24 and the wireless device 22 via the network node 16, without explicit reference to any intermediary devices and the precise routing of messages via these devices. Network infrastructure may determine the routing, which it may be configured to hide from the WD 22 or from the service provider operating the host computer 24, or both. While the OTT connection 52 is active, the network infrastructure may further take decisions by which it dynamically changes the routing (e.g., on the basis of load balancing consideration or

reconfiguration of the network).

The wireless connection 64 between the WD 22 and the network node 16 is in accordance with the teachings of the embodiments described throughout this disclosure. One or more of the various embodiments improve the performance of OTT services provided to the WD 22 using the OTT connection 52, in which the wireless connection 64 may form the last segment. More precisely, the teachings of some of these embodiments may improve the data rate, latency, and/or power consumption and thereby provide benefits such as reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime, etc.

In some embodiments, a measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve. There may further be an optional network functionality for reconfiguring the OTT connection 52 between the host computer 24 and WD 22, in response to variations in the measurement results. The measurement procedure and/or the network functionality for reconfiguring the OTT connection 52 may be implemented in the software 48 of the host computer 24 or in the software 90 of the WD 22, or both. In embodiments, sensors (not shown) may be deployed in or in

association with communication devices through which the OTT connection 52 passes; the sensors may participate in the measurement procedure by supplying values of the monitored quantities exemplified above, or supplying values of other physical quantities from which software 48, 90 may compute or estimate the monitored quantities. The reconfiguring of the OTT connection 52 may include message format, retransmission settings, preferred routing etc.; the reconfiguring need not affect the network node 16, and it may be unknown or imperceptible to the network node 16. Some such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary WD signaling facilitating the host computer’s 24 measurements of throughput, propagation times, latency and the like. In some embodiments, the measurements may be implemented in that the software 48, 90 causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection 52 while it monitors propagation times, errors etc.

Thus, in some embodiments, the host computer 24 includes processing circuitry 42 configured to provide user data and a communication interface 40 that is configured to forward the user data to a cellular network for transmission to the WD 22. In some embodiments, the cellular network also includes the network node 16 with a radio interface 62. In some embodiments, the network node 16 is configured to, and/or the network node’s 16 processing circuitry 68 is configured to perform the functions and/or methods described herein for

preparing/initiating/maintaining/supporting/ending a transmission to the WD 22, and/or preparing/terminating/maintaining/supporting/ending in receipt of a transmission from the WD 22.

In some embodiments, the host computer 24 includes processing circuitry 42 and a communication interface 40 that is configured to a communication interface 40 configured to receive user data originating from a transmission from a WD 22 to a network node 16. In some embodiments, the WD 22 is configured to, and/or comprises a radio interface 82 and/or processing circuitry 84 configured to perform the functions and/or methods described herein for

preparing/initiating/maintaining/supporting/ending a transmission to the network node 16, and/or preparing/terminating/maintaining/supporting/ending in receipt of a transmission from the network node 16.

Although FIGS. 1 and 2 show various“units” such as subspace tracking unit 32, and MIMO unit 34 as being within a respective processor, it is contemplated that these units may be implemented such that a portion of the unit is stored in a corresponding memory within the processing circuitry. In other words, the units may be implemented in hardware or in a combination of hardware and software within the processing circuitry.

FIG. 3 is a flowchart illustrating an exemplary method implemented in a communication system, such as, for example, the communication system of FIGS. 1 and 2, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIG. 2. In a first step of the method, the host computer 24 provides user data (Block S100). In an optional substep of the first step, the host computer 24 provides the user data by executing a host application, such as, for example, the host application 50 (Block S102). In a second step, the host computer 24 initiates a transmission carrying the user data to the WD 22 (Block S104). In an optional third step, the network node 16 transmits to the WD 22 the user data which was carried in the transmission that the host computer 24 initiated, in accordance with the teachings of the embodiments described throughout this disclosure (Block S106). In an optional fourth step, the WD 22 executes a client application, such as, for example, the client application 114, associated with the host application 50 executed by the host computer 24 (Block S108).

FIG. 4 is a flowchart illustrating an exemplary method implemented in a communication system, such as, for example, the communication system of FIG. 1, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 1 and 2. In a first step of the method, the host computer 24 provides user data (Block SI 10). In an optional substep (not shown) the host computer 24 provides the user data by executing a host application, such as, for example, the host application 50. In a second step, the host computer 24 initiates a transmission carrying the user data to the WD 22 (Block S 112). The transmission may pass via the network node 16, in accordance with the teachings of the embodiments described throughout this disclosure. In an optional third step, the WD 22 receives the user data carried in the transmission (Block S 114).

FIG. 5 is a flowchart illustrating an exemplary method implemented in a communication system, such as, for example, the communication system of FIG. 1, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 1 and 2. In an optional first step of the method, the WD 22 receives input data provided by the host computer 24 (Block S 116). In an optional substep of the first step, the WD 22 executes the client application 114, which provides the user data in reaction to the received input data provided by the host computer 24 (Block SI 18). Additionally or alternatively, in an optional second step, the WD 22 provides user data (Block S120). In an optional substep of the second step, the WD provides the user data by executing a client application, such as, for example, client application 114 (Block S 122). In providing the user data, the executed client application 114 may further consider user input received from the user. Regardless of the specific manner in which the user data was provided, the WD 22 may initiate, in an optional third substep, transmission of the user data to the host computer 24 (Block S124). In a fourth step of the method, the host computer 24 receives the user data transmitted from the WD 22, in accordance with the teachings of the embodiments described throughout this disclosure (Block S126).

FIG. 6 is a flowchart illustrating an exemplary method implemented in a communication system, such as, for example, the communication system of FIG. 1, in accordance with one embodiment. The communication system may include a host computer 24, a network node 16 and a WD 22, which may be those described with reference to FIGS. 1 and 2. In an optional first step of the method, in accordance with the teachings of the embodiments described throughout this disclosure, the network node 16 receives user data from the WD 22 (Block S128). In an optional second step, the network node 16 initiates transmission of the received user data to the host computer 24 (Block S130). In a third step, the host computer 24 receives the user data carried in the transmission initiated by the network node 16 (Block S132).

FIG. 7 is a flowchart of an exemplary process in a network node 16 for performing at least one MIMO related operation using tracked signal subspace information as described herein. One or more Blocks and/or functions performed by network node 16 may be performed by one or more elements of network node 16 such as by subspace tracking unit 32 and/or transmission determination unit 76 in processing circuitry 68, processor 70, radio interface 62, etc. In one or more embodiments, network node 16 such as via one or more of processing circuitry 68, processor 70, communication interface 60 and radio interface 62 is configured to obtain (Block S134) measurement information. For example, in one or more embodiments, at least one measurement is performed to at least in part obtain measurement information. In one or more embodiments, one or more uplink sounding and/or demodulation reference signals from one or more wireless devices 22 are measured to obtain at least in part measurement information. In one or more embodiments, the at least one measurement corresponds to at least one channel measurement such as to provide one or more channel estimates. In one or more embodiments, the at least one measurement includes measuring DMRS of the wireless device 22 at multiple points in space and corresponding channel vector at this point for determining a beampattem of a beamforming vector for each wireless device 22, as described herein. In one or more embodiments, measurement information may be received from one or more entities in system 10.

In one or more embodiments, network node 16 such as via one or more of processing circuitry 68, processor 70, communication interface 60 and radio interface 62 is configured to separately track (Block S136) a first direction and a second direction of a signal subspace of a covariance matrix of a channel based at least in part on the measurement information where the first direction being different from the second direction, as described herein as subspace tracking. In one or more

embodiments, the second order statistics of the channel are tracked, thereby focusing on energy in dominant Eigen vectors which help maximize wireless device 22 power. In one or more embodiments, the subspace tracking provides tracked signal subspace information, which is also referred to as signal subspace information.

Having generally described embodiments and arrangements for subspace tracking for performing MIMO related operations in a wireless communication

network, additional detailed and embodiments are provided below. For example, an embodiment of a process/algorithm for performing subspace tracking is described.

Algorithm Description

A network node 16 employing an example of antenna 59 as a 2-dimensional polarized antenna as shown in FIG. 8 is provided. In particular, the signal space of the channel in the horizontal and vertical directions is estimated, separately, using one or more subspace tracking algorithms. For SU-MIMO transmission, a separate precoder can be determined for each direction using the tracked signal subspace information for this direction only and the two precoders may then be combined to yield the full precoder for the 2-dimensional polarized array. For MU-MIMO transmission, the tracked signal space in each dimension can be jointly used for wireless device 22 pairing decisions, SINR estimation, and MU-MIMO precoding design/determination, among for other MIMO related operations.

Two-dimensional Subspace Tracking Algorithm

Let Mv and MH denote the number (quantity) of rows and columns of the 2-dimensional antenna array shown in FIG. 8, respectively, i.e., the total number (quantity) of antenna elements is given by 2 MVMH. The following is defined:

MVXMhX 2 multi-dimensional matrix H^t) such that the (m, n, p ) element of H^t) is the coefficient of the channel associated with the antenna element in row m, column n and polarization p at time instant t where m = 1, ... , Mv, n = 1, ... , MH, and p = 0, 1. Furthermore, the 2 MVMH X 1 full channel vector associated with the /ϋi wireless device is written as


where (. )T and (. )H denote the vector transpose and Hermitian transpose operators, respectively, and
is the MVMHX 1 vector containing the coefficients of the channel associated with the antennas with polarization p, and
can be obtained by applying the vectorization operator (that stacks the columns of a 2-dimensional matrix on top of each other) to the two-dimensional sub-matrix of Ht(t) associated with polarization p.

Due to the similarity of the covariance matrices of the channel associated with each set of polarized antennas, i.e.,

it was proposed in an existing study to track the signal subspace per antenna polarization, i.e., the dominant Eigen vectors and corresponding Eigen values of the MVMHXMVMH matrix Cj (t) . In particular, the PASTd algorithm is used to iteratively estimate the MVMHXR matrix S^t) whose columns are the most significant R Eigen vectors of Ct(t) in addition to the diagonal matrix
> Ai R_ 1( } containing the corresponding Eigen values where


> i R-1(t) and R £ MVMH. This leads to a

computational complexity of processing one channel measurement ht(t) to update the tracked signal subspace using the PASTd algorithm to be 8 MVMHRV + 4 MVMH + 2 R complex multiplications. The tracked signal subspace may correspond to and/or be included in the tracked signal subspace information where this information may be updated.

In another existing study, it was illustrated that the covariance matrix of the channel vector associated with a 2-dimensional array can be approximated as the Kronecker product of the horizontal and vertical covariance matrices. Hence, the following can be written


where 0 denotes the Kronecker product operator, Ci H(t ) is the MHXMH covariance matrix in the horizontal direction and Ci v(t ) is the MVXMV covariance matrix in the vertical direction. The Eigen value decomposition of Ct(t) is considered, which is given by

c = umw ?(t)


is the MVMHXMVMH matrix whose columns are the Eigen vectors of the matrix Ct(t) and the diagonal MVMHXMVMH matrix ^(t) contains the corresponding Eigen values on the main diagonal. Using the above Kronecker decomposition of the full-dimension covariance matrix, the matrices containing the Eigen vectors and Eigen values of the covariance matrix are denoted, respectively, as


where Ui H(t ) is the MH X MH matrix containing the Eigen vectors in the horizontal direction and T^H ) is the diagonal matrix containing the corresponding Eigen values. Similarly, Ui v(t ) is the Mv X Mv matrix containing the Eigen vectors and Ff iz (t) is the diagonal matrix containing the corresponding Eigen values in the vertical direction.

In contrast to the existing study that tracks the signal space of the matrix Ct(t ), the instant disclosure relates to tracking the signal subspace of the horizontal and vertical covariance matrices separately. FIG. 9 is a flowchart of one embodiment for performing the tracking of Block S 136 where two-dimensional subspace tracking is performed. The horizontal and vertical channel vectors are extracted from the full dimension channel (Block S140). In one or more embodiments, the outputs of Block S140 are fed into the subspace tracking blocks, described below, of the subspace tracking algorithm as input measurements. The subspace tracking algorithm implements two separate subspace tracking blocks: a horizontal covariance tracking block that tracks the dominant RH £ MH Eigen vectors (each of dimension MHX1) and the corresponding Eigen values of the matrix Ci H(t ) (Block S142), and a vertical covariance tracking block tracks the dominant Rv £ Mv Eigen vectors (each of dimension MVX 1) and the corresponding Eigen values of the matrix Ci v(t ) (Block S144). In one or more embodiments, the quantity of tracked Eigen vectors for the first direction (e.g., horizontal direction) is different from the quantity of tracked Eigen vectors for the second direction (e.g., vertical direction). For example, the quantity of tracked Eigen vectors for the first direction may be greater than the quantity of tracked Eigen vectors for the second direction, or vice-versa. In one or more embodiments these quantities are the same.

The estimates of the horizontal and vertical subspace tracking blocks can be combined to yield the dominant R = RVRH Eigen vectors and corresponding Eigen values of the full channel covariance matrix
Let


denote the MxXRx matrix whose columns are the Rx dominant Eigen vectors of Ci,x t ) where X E {H, V } denotes the horizontal or vertical directions and the RxXRx diagonal matrix A (t) contains the corresponding Eigen values, i.e.,

Therefore, the tracked Eigen vectors and Eigen values of the full-dimension channel are determined/obtained as


The PASTd algorithm is implemented to track the dominant Eigen vectors and Eigen values of the channel in each direction. Note that the algorithm in a previous study uses the channel estimates contained in the matrix Ht(t) to perform two iterations of PASTd (one iteration for each polarization) and then updates S)(t) and A (t) . In contrast to this previous study, in one or more embodiments, the subspace tracking block in each direction performs multiple iterations for each polarized channel. In particular, the vertical covariance tracking block uses the columns of the matrix Ht(t)

as its input measurement set which is denoted by


performs 2 MH PASTd iterations while the horizontal covariance tracking block uses the rows of Ht(t) as its input measurements which are denoted by Mi H(t) =


In one or more embodiments, the number (quantity) of tracked subspaces may be different in the horizontal and vertical dimensions. In one or more embodiments, the spatial spread is smaller in the vertical dimension, and in such situations, it may be beneficial to track fewer subspaces vertically compared to horizontally. In one or more embodiments, only one Eigen vector is tracked in the vertical dimension, and multiple Eigen vectors are tracked in the horizontal dimension.

The PASTd algorithm utilizes the forgetting factor 0 < b < 1 to help ensure that data in the past are down-weighted. The covariance tracking algorithm in the direction X E {H, V} of the channel of the /ϋi user/wireless device is implemented as follows:

Initialize the /h column

of the identity matrix.

For t = 1, 2, Do

o For n = 1, , Mx (where X denotes the complement of X ), and p = 0,1 Do:

Init


For j — 0, ... , Rx— 1, Do

Compute the inner product


Compute the estimate of the exponentially-weighted Eigen value

Compute the MxX 1 innovation vector vi ; (t) =


y jT

Update s (t) = s Xj)(t - l) + vi (t )

rif(t)

Compute the deflated measurement Mi +1(t) =


End For

o End For

End for

The Eigen value A-y (t) can be computed by dividing the exponentially-


effective memory length of the tracking algorithm. For a constant forgetting factor b, the effective memory length is given by 1/(1- b). The described PASTd algorithm may require only 4 MXRX + 2 Mx + 2 Rx complex multiplications per iteration and may require 2 MXRX + Rx real parameters,

to be stored for each wireless device 22. Since the PASTd

algorithm may not necessarily produce orthonormal Eigen vectors, the Gram-Schmidt orthonormalizing procedure (Blocks S146, S148) (after processing all the available

channel estimates) on the estimates js *(t) j may be used to obtain the

orthonormal basis of the tracked signal subspace. Hence, the total complexity of the proposed two-dimensional subspace tracking algorithm is given by 8 MVMH(RV +

RH + 1) + 4 MHRV + 4 MVRH complex multiplications for every available full channel estimate
The tracked signal subspace information may be updated as described herein (Block S150).

Referring back to FIG. 7, in one or more embodiments, network node 16 such as via one or more of processing circuitry 68, processor 70, communication interface 60 and radio interface 62 is configured to optionally perform (Block S138) at least one Multiple Input Multiple Output (MEMO) related operation based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel, i.e., based on the tracked signal subspace information. For example, the MIMO related operation may be related to one or more of SU-MIMO precoding (i.e., SU-MIMO precoder design), MU-MIMO pairing, MU-MIMO precoding (MU-MIMO precoder design), as described below. In one or more embodiments, the tracked signal subspace information may be used for various purposes such as, for example, for determining the angle of arrival of the received signal (which together with the range information can be used to locate the wireless device 22) by using high resolution spectral estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm.

SU-MIMO Precoder Design

The SU-MIMO precoders for each wireless device 22 can be constructed using the dominant Eigen vectors of its tracked covariance matrix (i.e., part of tracked signal subspace information). For the polarized antenna array shown in FIG. 8, the rank dL SU-MIMO precoder for the 1th wireless device 22 can be obtained/determined by co-phasing the
Eigen vectors of the covariance matrix per polarization. For example, the rank 2 SU-MIMO precoder for the i* wireless device 22 is given by


where pt is the co-phasing factor and st is the jth dominant Eigen vector of the matrix In one or more embodiments, the fixed or random co-phasing factor cpi can be used by the network node 16. In one or more embodiments, the network node 16 can use the wideband precoding matrix indicator (PMI) feedback from the network node 16 to determine the co-phasing factor and number (quantity) of transmitted layers. In this case, the SU-MIMO precoder of the 1th wireless device 22 is given by


where Np is the number (quantity) of ports used to transmit the reference symbols for PMI feedback, Vp2a is the port to antenna mapping, VPMI(t ) is the reported PMI with rank

The j* -dominant Eigen vector of the covariance matrix C(t) can be directly obtained from the tracked horizontal and vertical Eigen vectors as


where jH and jv are the horizontal and vertical indices of the tracked Eigen values that yield the jth dominant Eigen value, i.e.,


MU-MIMQ Pairing and Precoder Design

Given a set of wireless device 22 candidates for MU-MIMO transmission in a current subframe, the decision on the wireless device 22 for MU-MIMO co scheduling and the MU-MIMO precoders for each co-scheduled wireless device 22 can be obtained using the tracked two-dimensional subspace information (i.e., tracked signal subspace information). FIG. 10 is a flowchart of one or more embodiments of a MU-MIMO pairing and precoding selection algorithm/process. For example, the network node 16 may be configured to determine a subset of a plurality of wireless devices 22 for MU-MIMO co-scheduling based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel. In one or more embodiments, the network node 16 is further configured to determine MU-MIMO precoders for the subset of the plurality of wireless devices 22 based on the separate tracking of the first direction and the second direction of the signal subspace of the covariance matrix of the channel. In this process, the candidate wireless devices 22 for the current transmission are obtained from the scheduler where several pairing hypotheses are constructed, and the best hypothesis is selected based on the expected performance metric (Block S152, S154, S156). Finally, the MU-MIMO precoders are computed (Block S158) such that the MU-MIMO interference is limited. The two-dimensional subspace information (i.e., tracked signal subspace information), described herein such as with respect to Block S136 is used in various stages of this algorithm/process.

The two-dimensional tracked signal subspace information can be utilized to decide whether a wireless device 22 can be added to an existing hypothesis. For example, wireless devices 22 can be added to a pairing hypothesis based on a measure of the amount of MU-MIMO interference leakage. The MU-MIMO leakage measure between wireless device 22(1) and wireless device 22(2) is computed as


which measures the distance between the principal Eigen vector of one wireless device 22 and the receive subspace of the other and the amount of power contained in the non-tracked subspaces. In one or more embodiments, the dependence on the time index t has been dropped or omitted to enhance readability. A wireless device 22 is added to the hypothesis if the leakage measure between this wireless device 22 and all the wireless devices 22 in the hypothesis is less than a predetermined threshold. Note that the above expression for the leakage measure can be simplified using the two-dimensional tracked signal subspace information as


which may require only 2 MVRV + 2 MHRH + 4(RV + RH) complex multiplications instead of 2MVMHRVRH + 4 RVRH complex multiplications if evaluated using the full-dimension subspace tracking algorithm.

The tracked signal subspace information can also be used to estimate the MU-MIMO pairing interference to decide the pairing hypothesis as shown in FIG. 10. For example, it may be assumed that MU-MIMO interference occurs due to leakage on the non-tracked signal space directions and that MU-MIMO precoding (i.e., MU-MIMO precoder design) that can effectively eliminate the MU-interference at the tracked signal space directions given that there are enough transmit antennas at the network node 16. Assume that the first L wireless devices (WD) 22, i.e., WDo, WDi,

..., WDi-i, are paired in a MU-MIMO hypothesis. The total MU-MIMO interference power leaking on WDo can be estimated using the tracked signal space information in each direction as


where it is assumed that the non-tracked Eigen values are all equal in magnitude.

Finally, the MU-MIMO precoder can be computed using the two-dimensional tracked signal space information. Assume that the best hypothesis pairs the first L WDs { WDo, ..., WDL-I }. The rank di MU-MIMO precoder of each paired wireless

device is computed by co-phasing its projected Eigen vectors. For example, the rank 2 MU-MIMO SLNR precoder for the WD 0 with a fixed co-phasing factor i90 is given by


where


and the columns of the MX R{L-1) matrix 50 span the signal space of the L-l wireless devices 22 paired with WDo, i.e., 50 = (5! S2

diagjTV-L A2 ··· Al-1], s2 is the noise power, d is a power-normalization constant, and St and At are computed from the Kronecker product of the tracked Eigen vectors and Eigen values and the horizontal and vertical directions.

Therefore, one or more MEMO related operations may be performed based at least in part on the tracked signal subspace information.

Performance Evaluation

A non-limiting embodiment of a 7-site deployment scenario is used as an example for evaluation where each site has 3 cells and the inter-site distance is equal to 500 m. An FDD system operating in LTE Band 2 with bandwidth 20 MHz is simulated where the uplink carrier frequency is given by 1.86 GHz while the downlink frequency is equal to 1.94 GHz. The 5G SCM Urban Macro channel model with NLOS communication is used. The antenna configuration at the network node 16 is the AAS AIR 3246 (4x4x2) configuration. A TM9 transmission scheme with 8 CST RS ports is implemented. The traffic model for the downlink is selected as full buffer while the uplink has no traffic except for aperiodic CQI. The number (quantity) of layers transmitted is fixed at 2 for all the considered schemes. Uplink channel estimates are obtained from the uplink DMRS in aperiodic CQI reports where ideal channel estimation is assumed, i.e., measurement information is obtained. The wireless devices 22 are randomly dropped in the simulation area and move with speed 3 Km/hr.

FIG. 11 is a graph of the average downlink cell throughput versus the number (quantity) of wireless devices 22 in the simulation area. As illustrated the performance of Eigen beamforming using PASTd, as described herein, is better in terms of throughput than GoB transmission. SU-MIMO Eigen beamforming using PASTd (i.e., SU-MIMO PASTd, R=2, as described herein) provides 12% throughput gain over SU-MIMO GoB while MU-MIMO Eigen beamforming using PASTd (i.e., MU-MIMO PASTd, R=5, as described herein) provides 25% gain over MU-MIMO GoB. Further, there is negligible performance degradation due to the use of the two-dimensional PASTd described herein compared to tracking the full channel described in an existing study.

Therefore, one or more embodiments of the disclosure allows for employing two-dimensional subspace tracking to track the signal space of the covariance matrix of the uplink channel in the azimuth and elevation directions separately. The tracked two-dimensional signal space information can be used to calculate SU- and MU-MIMO precoders with significantly lower computational complexity than the complexity of full-channel signal subspace tracking with negligible performance degradation.

FIG. 12 is a flowchart of an exemplary process in a wireless device 22 according to some embodiments of the present disclosure. One or more Blocks and/or functions performed by wireless device 22 may be performed by one or more

elements of wireless device 22 such as by MIMO unit 34 in processing circuitry 84, processor 86, radio interface 82, etc. In one or more embodiments, wireless device 22 such as via one or more of processing circuitry 84, processor 86, radio interface 82 and radio interface 82 is configured to transmit (Block S160) at least one reference signal, as described herein. In one or more embodiments, wireless device 22 such as via one or more of processing circuitry 84, processor 86, radio interface 82 and radio interface 82 is configured to receive (Block S162) a configuration for participating in MIMO where the configuration is based at least in part on a separate tracking of a first direction and a second direction of a signal subspace of a covariance matrix of a channel that is based at least in part on the transmitted at least one reference signal, as described herein.

Abbreviations that may be used in the preceding description include:

AAS Adaptive Antenna System

CSn Channel State Information at the Transmitter

CRS Cell- specific Reference Symbols

DMRS Demodulation Reference Signals

eNB Evolved Node B

FDD Frequency Division Duplex

GoB Grid of Beams

FTE Long Term Evolution

MIMO Multiple Input Multiple Output

MU Multi-User

NLOS Non- Line of Sight

PASTd Projection Approximation Subspace Tracking with deflation

SINR Signal to Interference-plus-Noise Ratio

SINR Signal to Leakage-plus-Noise Ratio

SU Single-User

TDD Time Division Duplex

UE User Equipment

ZF Zero-Forcing

As will be appreciated by one of skill in the art, the concepts described herein may be embodied as a method, data processing system, and/or computer program

product. Accordingly, the concepts described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects all generally referred to herein as a “circuit” or“module.” Furthermore, the disclosure may take the form of a computer program product on a tangible computer usable storage medium having computer program code embodied in the medium that can be executed by a computer. Any suitable tangible computer readable medium may be utilized including hard disks, CD-ROMs, electronic storage devices, optical storage devices, or magnetic storage devices.

Some embodiments are described herein with reference to flowchart illustrations and/or block diagrams of methods, systems and computer program products. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer readable memory or storage medium that can direct a computer or other

programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

It is to be understood that the functions/acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that

communication may occur in the opposite direction to the depicted arrows.

Computer program code for carrying out operations of the concepts described herein may be written in an object oriented programming language such as Java® or C++. However, the computer program code for carrying out operations of the disclosure may also be written in conventional procedural programming languages, such as the "C" programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer. In the latter scenario, the remote computer may be connected to the user's computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, all embodiments can be combined in any way and/or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and subcombinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or subcombination.

It will be appreciated by persons skilled in the art that the embodiments described herein are not limited to what has been particularly shown and described herein above. In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. A variety of

modifications and variations are possible in light of the above teachings without departing from the scope of the following claims.