Feedback-aided MU-MIMO Scheduling Technique IEEE 802.16 Presentation Submission Template (Rev. 9) Document Number: IEEE S802.16m-07_166 September 09 2007.

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Presentation transcript:

Feedback-aided MU-MIMO Scheduling Technique IEEE Presentation Submission Template (Rev. 9) Document Number: IEEE S802.16m-07_166 September Source: Liyu Cai Hongwei Yang Keying Wu sbell.com.cn), Lei Wang Alcatel-Lucent Research and Venue: Session #51, Malaga, Spain Base Contribution: IEEE S802.16m-07_166 Purpose: For m discussion and eventual adoption for standardization of means and methods to support user feedback of CSIT error information or CCI measurement to aid the successful application of MU-MIMO. Notice: This document does not represent the agreed views of the IEEE Working Group or any of its subgroups. It represents only the views of the participants listed in the “Source(s)” field above. It is offered as a basis for discussion. It is not binding on the contributor(s), who reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor grants a free, irrevocable license to the IEEE to incorporate material contained in this contribution, and any modifications thereof, in the creation of an IEEE Standards publication; to copyright in the IEEE’s name any IEEE Standards publication even though it may include portions of this contribution; and at the IEEE’s sole discretion to permit others to reproduce in whole or in part the resulting IEEE Standards publication. The contributor also acknowledges and accepts that this contribution may be made public by IEEE Patent Policy: The contributor is familiar with the IEEE-SA Patent Policy and Procedures: and. Further information is located at and.

Purpose MU-MIMO is an important option of MIMO technology due to its potential to greatly improve the system throughput, and will be supported in 16m and other IMT-advanced systems. Existing MU-MIMO techniques suffer serious performance loss when CSI (Channel State Information) at the transmitter (CSIT) is imperfect, which cannot be avoided in real world systems. We propose an advanced scheduling technique to improve the performance of MU-MIMO in the case of imperfect CSIT.

Motivation Imperfect CSIT leads to additional CCI (Co-channel Interference) among users, which seriously deteriorates the MU-MIMO performance. The power of additional CCI grows with the number of users simultaneously supported in MU-MIMO. Therefore, decreasing the simultaneous users number can lead to a reduced CCI, and sometimes even higher system throughput.

Feedback-aided MU-MIMO scheduling Our approach: –UE feeds back additional information related to CSIT error. –BS collects such information from all UEs, and adjusts the simultaneous user number accordingly. Two cases: –Statistical properties of the CSIT error can be estimated at UE (e.g., the CSIT error comes from the quantization of CSI or the average of CSI feedback over a frequency band) UE feeds back the covariance matrixes of CSIT error. –Both the UEs and BS have difficulty to obtain the knowledge of CSIT error (e.g., uplink sounding is used for the BS to acquire CSIT) UE checks the CCI power to see if it is too high, and feeds back its decision.

Simulation conditions –Flat Rayleigh uncorrelated fading channels. –CSIT error modeled as i.i.d. AWGN with zero mean and variance  e 2. –MET algorithm and greedy scheduling CSIT error covariance feedback Simulation results

CCI measurement feedback Simulation results (cont.)

Recommendation User feedbacks of CSIT error information, or CCI level, should be supported in 16m systems, to aid the successful application of MU-MIMO.