Permutation Matrix Modulation

TL;DR

Permutation Matrix Modulation (PMM) is a new MIMO scheme that encodes information using permutation matrices, enhancing data rates and offering a trade-off between detection complexity and error performance.

Contribution

The paper introduces PMM, a novel MIMO modulation scheme using permutation matrices, with analysis of achievable rates, optimal rate calculation, and low-complexity detection methods.

Findings

PMM achieves higher data rates compared to existing systems.

Zero-forcing detection reduces complexity but has higher error rates.

Optimal rate can be obtained via interior-point optimization.

Abstract

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.