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

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[ EN ]

What is claimed is:

1. A network node (16), comprising:

processing circuitry (68) 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, 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.

2. The network node (16) of Claim 1, wherein the first direction is an azimuth direction and the second direction is an elevation direction.

3. The network node (16) of any one of Claims 1-2, wherein the processing circuitry (68) 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.

4. The network node (16) of Claim 3, wherein 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.

5. The network node (16) of Claim 4, wherein 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.

6. The network node (16) of any one of Claims 1-5, wherein 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.

7. The network node (16) of Claim 6, wherein the processing circuitry (68) 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.

8. The network node (16) of any one of Claims 1-7, wherein the processing circuitry (68) 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.

9. The network node (16) of any one of Claims 1-8, wherein the processing circuitry (68) is further configured to determine a subset of a plurality of wireless devices (22) 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.

10. The network node (16) of Claim 9, wherein the processing circuitry (68) 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.

11. A method for a network node (16), the method comprising:

obtaining (S134) measurement information;

separately tracking (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 obtained measurement information, the first direction being different from the second direction; and

optionally performing (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.

12. The method of Claim 11, wherein the first direction is an azimuth direction and the second direction is an elevation direction.

13. The method of any one of Claims 11-12, further comprising:

tracking the first direction of the signal subspace of the covariance matrix of the channel by tracking Eigen vectors associated with the first direction; and

tracking the second direction of the signal subspace of the covariance matrix of the channel by tracking Eigen vectors associated with the second direction.

14. The method of Claim 13, wherein 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.

15. The method of Claim 14, wherein 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.

16. The method of any one of Claims 11-15, wherein 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.

17. The method of Claim 16, further comprising determining 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.

18. The method of any one of Claims 11-17, further comprising determining a single user-MIMO, SU-MIMO, precoder for a wireless device (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.

19. The method of any one of Claims 11-18, further comprising determining 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.

20. The method of Claim 19, further comprising determining 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.

21. A network node (16), comprising:

processing circuitry (68) configured to:

obtain measurement information;

perform two dimensional subspace tracking based at least in part on the obtained measurement information, a first direction and a second direction of the two dimensional subspace of a covariance matrix of a channel being tracked separately, 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;

optionally perform at least one Multiple Input Multiple Output, MEMO, related operation based on two dimensional subspace tracking.