Per-antenna power constrained rate optimization for multiuser MIMO systems

Shuying Shi, M. Schubert, H. Boche
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引用次数: 49

Abstract

This paper investigates the problem of linear transceiver design for rate optimization in multiuser Gaussian multi-input-multi-output (MiMO) systems. We focus on a scenario with per-antenna power constraint, which is of importance for a realistic implementation. Two design criteria are considered: (1) maximizing the weighted sum rate subject to per-antenna power constraints; (2) maximizing the minimum user rate subject to per-antenna power constraints. Non-convexity and the complicated mathematical structure of the problems make it difficult to derive efficient, globally optimal algorithms. Even the power allocation problem for sum-rate optimization leads to a problem formulation involving ratios of posynomials, which is generally an intrinsically intractable NP hard problem. The problems studied here are even more complicated, since we consider a joint optimization over powers, transmit filters and receive filters. For these problems, we derive iterative algorithms and prove the monotonic convergence of the algorithms. Additionally, we show that the results can be extended to other variations of the problems and the problems with other kinds of power constraints.
多用户MIMO系统的单天线功率约束速率优化
研究了多用户高斯多输入多输出(MiMO)系统中线性收发器的速率优化设计问题。我们关注的是具有每个天线功率约束的场景,这对于实际实现非常重要。考虑了两个设计准则:(1)在每个天线功率约束下最大化加权和率;(2)在每个天线功率约束下最大化最小用户速率。问题的非凸性和复杂的数学结构使得很难推导出有效的全局最优算法。即使是求和速率优化的功率分配问题,也会导致一个涉及多项式比率的问题表述,这通常是一个本质上难以处理的NP困难问题。这里研究的问题更加复杂,因为我们考虑了功率、发射滤波器和接收滤波器的联合优化。针对这些问题,我们推导了迭代算法,并证明了算法的单调收敛性。此外,我们还证明了结果可以推广到问题的其他变体以及具有其他类型功率约束的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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