MISO TX-power minimization under imperfect instantaneous CSIT

Samip Malla, G. Abreu
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引用次数: 1

Abstract

The signal to interference and noise ratio (SINR)-constrained transmit (TX)-power minimization problem, incorporating perfect and instantaneous channel state information at the transmitter (CSIT), culminates in higher overhead and extensive backhauling, likewise average CSIT suffers from quality fluctuations. Also, methods relying on the statistical SINR constraints require several algebraic steps in converting those constraints to deterministic convex equivalents. This process not only loosens the constraint of the problem, but also significantly subtracts the potential performance. In contrary to above mentioned procedures, we account for imperfect instantaneous CSIT and propose a simple solution based on Perron-Frobenius (PF) theorem and uplink-downlink duality to address the problem in a multi-user multiple input single output (MISO) system under prescribed outage. We derive accurate models for the distribution of true SINR experienced by the receivers subject to imperfect CSIT and conditioned on constraint-matching SINR estimates. Simulation results demonstrate the significant performance gain achieved by the proposed solution when compared with the state of the art.
不完全瞬时CSIT下的MISO tx功率最小化
信号干扰和噪声比(SINR)约束的传输(TX)功率最小化问题,结合了发射器(CSIT)的完美和瞬时信道状态信息,最终导致更高的开销和广泛的回程,同样,平均CSIT也受到质量波动的影响。此外,依赖于统计SINR约束的方法需要几个代数步骤来将这些约束转换为确定性凸等价。这个过程不仅放松了问题的约束,而且显著地降低了潜在的性能。与上述过程相反,我们考虑到不完美的瞬时CSIT,并提出了基于Perron-Frobenius (PF)定理和上行-下行对偶性的简单解决方案,以解决规定停机情况下多用户多输入单输出(MISO)系统中的问题。在不完全CSIT和约束匹配SINR估计条件下,我们得到了真实SINR分布的精确模型。仿真结果表明,与现有的算法相比,该算法获得了显著的性能提升。
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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