Coordinated linear beamforming in downlink multi-cell wireless networks

• US 8,218,422 B2
• Filed: 06/03/2009
• Issued: 07/10/2012
• Est. Priority Date: 06/03/2008
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Laboratories America Inc (NEC Corporation)
• Inventors: Venturino, Luca, Wang, Xiaodong, Prasad, Narayan
• Primary Examiner(s): Kizou, Hassan
• Assistant Examiner(s): Jiang, Charles C
• Application Number:
  US12/477,255
• Publication Number:
  US 20090296650A1
• Time in Patent Office: 1,133 Days
• Field of Search: 370203-211, 370/310, 370/328, 370/329, 370/330, 4554221-460
• US Class Current: 370/208
• CPC Class Codes: H04W 16/28 using beam steering

Abstract

System and methods are disclosed for optimizing wireless communication for a plurality of mobile wireless devices. The system uses beamforming vectors or precoders having a structure optimal with respect to the weighted sum rate in a multi-cell orthogonal frequency division multiple access (OFDMA) downlink. A plurality of base stations communicate with the mobile devices and all base stations perform a distributed non-convex optimization exploiting the determined structure.

Claims

1. A method to optimize wireless communication for a plurality of mobile wireless devices, comprising:

a. determining a structure for downlink beamforming vectors optimizing a weighted sum-rate across multiple orthogonal resource slots in the time, frequency or code domain; and

b. distributing a non-convex optimization exploiting the determined structure over a plurality of base stations.

2. The method of claim 1, wherein the non-convex optimization is responsive to one or more of:

a set of channel estimates;

user priorities; and

maximum transmit power available at each base-station.

3. The method of claim 1, wherein the non-convex optimization utilizes Karush-Kuhn-Tucker (KKT) equations.

4. The method of claim 1, wherein the distributing over the base stations includes providing a small number of channel estimates at each base station and limited message passing among adjacent base stations.

5. The method of claim 1, comprising obtaining channel estimates.

6. The method of claim 1, comprising obtaining predicted channel estimates responsive to an average scheduling delay parameter.

7. The method of claim 1, wherein the mobile wireless device comprises a multiple-input single-output (MISO) system wherein each user is equipped with a single receive antenna and receives a single data stream from its serving base station via space-division multiple-access (SDMA).

8. The method of claim 1, comprising determining the optimal structure of the beamforming vectors optimizing the weighted sum-rate in a MISO system.

9. The method of claim 8, comprising determining a leakage matrix.

10. The method of claim 9, wherein determining a leakage matrix L_m,k(n) comprises:

11. The method of claim 10, comprising determining

12. The method of claim 8, comprising determining λ

₁, . . . , λ

_M and

13. The method of claim 12, comprising updating beam vectors as

w_m,k(n)={circumflex over (β

)}_m,k(n;

λ

_m){circumflex over (T)}_m,k^†

(n;

λ

_m)h_m,k(n).

14. The method of claim 8, comprising choosing an initial feasible set of beam vectors.

15. The method of claim 14, wherein the initial feasible set is selected after splitting power across the available slots.

16. The method of claim 14, comprising performing channel-matched beamforming to select the initial feasible set of beam vectors.

17. The method of claim 14, comprising performing in-cell zero-forcing beamforming to select the initial feasible set of beam vectors.

18. The method of claim 14, comprising performing maximum signal-to-leakage-plus-noise ratio (MSLNR) beamforming to select the initial feasible set of beam vectors.

19. The method of claim 1, comprising providing an equivalent MISO system wherein each mobile user has multiple-receive antennas and performs rank-one receive beamforming before detection.

20. The method of claim 1, wherein the mobile wireless device comprises a multiple-input multiple-output (MIMO) system and wherein each user is equipped with multiple receive antennas and receives multiple data streams from a serving base station via linear precoding.

21. The method of claim 20, comprising determining a leakage matrix.

22. The method of claim 20, comprising solving a following convex optimization problem at each base-station m, for a given {L_m,k(n)} and {R_m,k(n)}:

23. The method of claim 20, comprising selecting an initial feasible set of positive semi-definite covariance matrices after splitting power across available slots.

24. The method of claim 23, comprising performing Maximum Signal-to-Leakage-plus-Noise Ratio (MSLNR) precoding to select the initial feasible set of positive semi-definite covariance matrices.

25. The method of claim 1, comprising determining an optimal structure of the linear precoders in a MIMO system.

26. The method of claim 21, wherein determining a leakage matrix L_m,k(n) comprises determining:

27. A communication system, comprising:

a. a plurality of mobile devices that receive data made by linear precoding matrices having a predetermined structure for downlink precoding, the predetermined structure being optimal with respect to a weighted sum rate in a multi-cell orthogonal frequency division multiple access (OFDMA) downlink; and

b. a plurality of base stations communicating with the mobile devices, all base stations performing a distributed a non-convex optimization exploiting the predetermined structure.