We propose a novel scheme that allows MIMO system to modulate a set of permutation matrices to send more information bits, extending our initial work on the topic. This system is called Permutation Matrix Modulation (PMM). The basic idea is to employ a permutation matrix as a precoder and treat it as a modulated symbol. We continue the evolution of index modulation in MIMO by adopting all-antenna activation and obtaining a set of unique symbols from altering the positions of the antenna transmit power. We provide the analysis of the achievable rate of PMM under Gaussian Mixture Model (GMM) distribution \revv{and finite cardinality input (FCI). Numerical results are evaluated by comparing PMM with the other existing systems.} We also present a way to attain the optimal achievable rate of PMM by solving a maximization problem via interior-point method. A low complexity detection scheme based on zero-forcing (ZF) is proposed, and maximum likelihood (ML) detection is discussed. We demonstrate the trade-off between simulation of the symbol error rate (SER) and the computational complexity where ZF performs worse in the SER simulation but requires much less computational complexity than ML.
翻译:我们提出一个新方案,让IMIMO系统能够调整一套调整矩阵,以发送更多的信息比特,扩大我们关于这个专题的初始工作。这个系统称为“变异矩阵模型模型(PMM) ” 。基本想法是使用一个变异矩阵矩阵作为预解解器,并将它作为调制符号处理。我们继续通过采用全安宁激活和从改变天天天传输功传输力位置改变天线传输力位置获得一套独特的符号,从而在MOIM继续进化指数调调制的演化过程,通过采用全无线激活和从天线传输力改变天线传输力的位置获得一套独特的符号。我们分析了高萨混合模型(GMMM)分配 分布\revvv{和有限主基输入(FCI)下PMMMMM的可实现率。我们通过将PMMM与其他现有系统进行比较来评估数值结果。我们还提供了一种途径,通过内部点方法解决最大化问题,从而实现PMMMM的可实现最佳比率率。我们提议了一个以零叉(ZF)为基础的低复杂探测计划,并讨论最大可能性(ML)探测。我们讨论了最大可能性(ML)探测。我们展示了象征错误率的模拟错误率(SER错误率(SER)比但更严重,但更需要更重的模拟,但更重的MZMZMZ的模拟,进行更重的模拟需要更重的MZ的计算。