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Power minimization of multiaccess MIMO systems with rate constraint and finite-rate feedback

机译:具有速率限制和有限速率反馈的多路访问MIMO系统的功率最小化

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In this paper, power minimization of multi-access multiple-input multiple-output (MIMO) systems with rate constraint is studied where the users only have partial channel state information (CSI) obtained through finite-rate feedback. Although the optimal scheme is difficult to obtain, we propose a sub-optimal beamforming scheme where the beamforming vectors are selected by the feedback. The Base station (BS) broadcasts the optimal index of the code vectors in the codebook to the users. With optimal quatization of CSI and only a small number of feedback bits, the required average sum-power is shown to be close to or even smaller than the sub-optimal maximum eigenmode beamforming (MEB) scheme where perfect CSI is known at the users. To simplify the performance analysis, we use a sub-optimal quantization scheme for the proposed beamforming scheme, where the distance between the code vectors and the strongest eigen-channel vectors of the users is minimized. Although the sub-optimal quantization scheme has a higher sum-power than the optimal one, simulation results show that they achieve similar multi-user gain. By letting the feedback bits approach infinity, this sub-optimal quantization scheme becomes the MEB scheme. A closed-form expression for the sum-power of this sub-optimal quantization scheme is estimated by random matrix theory and quantization bounds on Grassmann manifold. The effect of the finite-rate feedback on multi-user gain is then studied using this closed-form expression.
机译:本文研究了具有速率约束的多址多输入多输出(MIMO)系统的功率最小化,其中用户仅具有通过有限速率反馈获得的部分信道状态信息(CSI)。尽管难以获得最优方案,但我们提出了一种次优的波束形成方案,其中通过反馈选择波束形成矢量。基站(BS)向用户广播码本中码矢量的最佳索引。利用CSI的最佳量化和仅少量的反馈位,所需的平均和功率显示为接近甚至小于亚最佳最大本征模波束成形(MEB)方案,在该方案中,用户可以找到理想的CSI。为了简化性能分析,对于拟议的波束形成方案,我们使用了次优量化方案,其中代码矢量与用户最强本征信道矢量之间的距离最小。尽管次优量化方案的总和功率比最优方案高,但仿真结果表明它们实现了相似的多用户增益。通过使反馈比特接近无穷大,该次优量化方案变为MEB方案。利用随机矩阵理论和格拉斯曼流形上的量化界限,估计了该次优量化方案的和能力的封闭形式。然后使用此闭式表达式研究有限速率反馈对多用户增益的影响。

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