Method for Improving Multiuser MIMO Downlink Transmissions

• US 20120257664A1
• Filed: 04/06/2012
• Published: 10/11/2012
• Est. Priority Date: 04/06/2011
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Laboratories America Inc (NEC Corporation)
• Inventors: Yue, Guosen, Prasad, Narayan, Jiang, Meilong, Khojastepour, Mohammad A., Rangarajan, Sampath
• Granted Patent: US 8,750,358 B2
• Time in Patent Office: Days
• US Class Current: 375/227
• CPC Class Codes: H04B 7/0417 Feedback systems
• CPC Class Codes: H04B 7/0452 Multi-user MIMO systems
• CPC Class Codes: H04B 7/0469 taking special antenna structures, e.g. cross polarized antennas into account
• CPC Class Codes: H04B 7/0626 Channel coefficients, e.g. channel state information [CSI]
• CPC Class Codes: H04B 7/063 Parameters other than those covered in groups H04B7/0623 - H04B7/0634, e.g. channel matrix rank or transmit mode selection
• CPC Class Codes: H04B 7/0639 Using selective indices, e.g. of a codebook, e.g. pre-distortion matrix index [PMI] or for beam selection
• CPC Class Codes: H04L 1/0013 Rate matching, e.g. puncturing or repetition of code symbols
• CPC Class Codes: H04L 1/0015 characterised by the adaptation strategy
• CPC Class Codes: H04L 1/0021 in which the algorithm uses adaptive thresholds
• CPC Class Codes: H04L 1/0035 evaluation of received explicit signalling
• CPC Class Codes: H04L 2025/03808 Transmission of equaliser coefficients
• CPC Class Codes: H04L 25/03949 equalizer selection or adaptation based on feedback multiple signaling inclusive of a precoding command for adapting the transmitter H04L1/0031; feedback for transmit diversity systems H04B7/0619; selection of codebook or precoding matrix for MIMO diversity systems H04B7/0456

Abstract

A method for improving multiple-input multiple-output MIMO downlink transmissions includes obtaining a channel state information CSI report including preferred matrix index PMI for precoding, channel quality index CQI and rank index RI at a base station from user terminals through a channel feedback; applying selectively a signal-to-interference-plus-noise-ratio SINR offset to a SINR of said CSI report; applying selectively a rate matching responsive to SINR offset or the CSI report; and controlling or adjusting the SINR offset.

Claims

1. A method for improving multiple-input multiple-output MIMO downlink transmissions, comprising the steps of:

obtaining a channel state information CSI report including preferred matrix index PMI for precoding, channel quality index CQI and rank index RI at a base station from user terminals through a channel feedback;

applying selectively a signal-to-interference-plus-noise-ratio SINR offset to an SINR of said CSI report;

applying selectively a rate matching responsive to SINR offset or said CSI report;

controlling or adjusting said SINR offset.

2. The method of claim 1, wherein said rate matching is based on a multi-user MU CSI report directly if a multiuser MU MIMO is scheduled in said downlink transmission.

3. The method of claim 1, wherein said SINR offset is applied to the SINR contained in the single-user SU CSI report or the SINR approximation based on the single-user SU CSI report before said rate matching if a multiuser MU MIMO is scheduled in said downlink transmission.

4. The method of claim 1, wherein said SINR offset is applied to the SINR contained in the multi-user MU CSI report or the SINR approximation based on the multi-user MU CSI report before said rate matching if a single-user SU MIMO is scheduled in said downlink transmission

5. The method of claim 1, wherein said controlling comprises a controller that is one of a unit of a scheduler or combined with a second controller.

6. The method of claim 1, further comprising applying an SINR scaling approximation for computing an SINR when exact precoders for co-scheduled streams are decided or evaluated during a scheduling including multiuser MU MIMO pairing and resource allocation, responsive selectively to said CSI report or a second said SINR offset.

7. The method of claim 6, further comprising applying a zero-forcing beamforming to said SINR scaling approximation if columns of an overall precoding matrix are not mutually orthogonal.

8. The method of claim 6, wherein said SINR scaling approximation comprises a channel approximation, a signal model with approximated channel, an SINR computation and an SINR approximation.

9. The method of claim 8, wherein said channel approximation comprises an approximation responsive to a semi-unitary matrix whose columns are a basis for the orthogonal complement to a range of a reported precoder from a user, a matrix which satisfies a Frobenius-norm constraint influenced by a size of a quantization codebook and channel statistics based in part on an SINR feedback for a particular stream of respective user based on single user SU said CSI reports or multiuser MU said CSI reports, respectively.

10. The method of claim 8, wherein said signal model with approximated channel comprises a same signal model expression as an original MU MIMO with channel matrix replaced by an approximation channel or a simplified model in which an introduced channel uncertainty affects only interfering streams.

11. The method of claim 8, wherein said SINR computation comprises computing an SINR for a respective receiver based on said signal model.

12. The method of claim 8, wherein said SINR approximation comprises, given a constraint on an uncertainty in a channel model, finding a conservative SINR as said SINR approximation for said rate matching and modulation and coding scheme MCS assignment.

13. The method of claim 1, wherein said channel feedback comprises, responsive to some feedback channel knowledge, pooling of users by said base station into two or more groups with one group of users sending back quantized instant channel information assuming a single user SU MIMO will be scheduled and another group of users sending back quantized instant channel information for assuming a multiuser MU MIMO will be scheduled.

14. The method of claim 1, responsive to various channel feedbacks and a pooling metric, pooling of users is performed for selecting a user for multiuser MU MIMO pairing from which some users are considered for user pairing for MU MIMO transmission and other users are only considered for single user SU MIMO transmission.