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MIMO Transceivers With Decision Feedback and Bit Loading: Theory and Optimization

机译:具有决策反馈和位加载的MIMO收发器:理论与优化

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摘要

This paper considers MIMO transceivers with linear precoders and decision feedback equalizers (DFEs), with bit allocation at the transmitter. Zero-forcing (ZF) is assumed. Considered first is the minimization of transmitted power, for a given total bit rate and a specified set of error probabilities for the symbol streams. The precoder and DFE matrices are optimized jointly with bit allocation. It is shown that the generalized triangular decomposition (GTD) introduced by Jiang, Li, and Hager offers an optimal family of solutions. The optimal linear transceiver (which has a linear equalizer rather than a DFE) with optimal bit allocation is a member of this family. This shows formally that, under optimal bit allocation, linear and DFE transceivers achieve the same minimum power. The DFE transceiver using the geometric mean decomposition (GMD) is another member of this optimal family, and is such that optimal bit allocation yields identical bits for all symbol streams-no bit allocation is necessary-when the specified error probabilities are identical for all streams. The QR-based system used in VBLAST is yet another member of the optimal family and is particularly well-suited when limited feedback is allowed from receiver to transmitter. Two other optimization problems are then considered: (a) minimization of power for specified set of bit rates and error probabilities (the QoS problem), and (b) maximization of bit rate for fixed set of error probabilities and power. It is shown in both cases that the GTD yields an optimal family of solutions.
机译:本文考虑具有线性预编码器和判决反馈均衡器(DFE)的MIMO收发器,并在发射机处进行位分配。假定为零强制(ZF)。首先考虑的是,对于给定的总比特率和符号流的一组特定的错误概率,应将发射功率最小化。预编码器和DFE矩阵与位分配一起进行了优化。结果表明,Jiang,Li和Hager引入的广义三角分解(GTD)提供了最优解。具有最佳位分配的最佳线性收发器(具有线性均衡器而不是DFE)是该系列的成员。这正式表明,在最佳位分配下,线性和DFE收发器达到相同的最小功率。使用几何均值分解(GMD)的DFE收发器是此最优系列的另一个成员,当所有流的指定错误概率均相同时,最优比特分配可为所有符号流产生相同的比特-无需比特分配。 VBLAST中使用的基于QR的系统是最优系列的又一成员,当允许从接收器到发送器的有限反馈时,它特别适合。然后考虑另外两个优化问题:(a)最小化指定比特率和错误概率集的功率(QoS问题),以及(b)最大化错误集合和错误率概率和功率的比特率。在这两种情况下,都表明GTD产生了最优的解决方案系列。

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