Robust wireless statistic division multiplexing and its performance analysis

Abstract

Aiming at solving the issue of the robustness of sensor signal recovery as well as tackling the dilemma of simultaneous spectrum utilization, this article will concentrate on designing a robust wireless statistic division multiplexing scheme. The proposed robust wireless statistic division multiplexing transmits multiple sensor signals and shares the same frequency band simultaneously. The fundamental principle of robust wireless statistic division multiplexing is described as statistical independence or statistical distinction of the sensor source signals. An unsupervised learning mechanism named independent component analysis is used for robust wireless statistic division multiplexing receiving processing. The robust wireless statistic division multiplexing can not only contribute tremendously to enhancing the spectrum efficiency but also bring in attractive anti-noise performance. In this article, first, the fundamental mechanism of robust wireless statistic division multiplexing will be discussed in comparison with that of time division multiplexing, frequency division multiplexing and code division multiplexing. Second, in terms of robust wireless statistic division multiplexing receiving mechanism based on independent component analysis principle, a novel cost function based on minimization mutual information modified by minimum bit error rate constraint is investigated to improve robust performance of source recovery. Furthermore, independent component analysis-based blind source separation method combines with an adaptive moment estimation stochastic optimization for promoting the effectiveness of the source recovery performance. Finally, theoretical analysis and simulation experiments demonstrate the effectiveness and robustness performance of robust wireless statistic division multiplexing.