Feedback Reduction for Random Beamforming in Multiuser MIMO Broadcast Channel

Clinical Orthopaedics and Related Research(2011)

引用 23|浏览4
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摘要
For the multiuser multiple-input multiple-output (MIMO) downlink channel, the users feedback their channel state information (CSI) to help the base station (BS) schedule users and improve the system sum rate. However, this incurs a large aggregate feedback bandwidth which grows linearly with the number of users. In this paper, we propose a novel scheme to reduce the feedback load in a downlink orthogonal space division multiple access (SDMA) system with zero-forcing receivers by allowing the users to dynamically determine the number of feedback bits to use according to multiple decision thresholds. Through theoretical analysis, we show that, while keeping the aggregate feedback load of the entire system constant regardless of the number of users, the proposed scheme almost achieves the optimal asymptotic sum rate scaling with respect to the number of users (also known as the multiuser diversity). Specifically, given the number of thresholds, the proposed scheme can achieve a constant portion of the optimal sum rate achievable only by the system where all the users always feedback, and the remaining portion (referred to as the sum rate loss) decreases exponentially to zero as the number of thresholds increases. By deriving a tight upper bound for the sum rate loss, the minimum number of thresholds for a given tolerable sum rate loss is determined. In addition, a fast bit allocation method is discussed for the proposed scheme, and the simulation results show that the sum rate performances with the complex optimal bit allocation method and with the fast algorithm are almost the same. We compare our multi-threshold scheme to some previously proposed feedback schemes. Through simulation, we demonstrate that the proposed scheme can reduce the feedback load and utilize the limited feedback bandwidth more effectively than the existing feedback methods.
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关键词
information theory,base station,channel state information,upper bound,zero forcing,rating scale
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