Compressive Sensing Massive IoT Access in Massive MIMO Systems with Media Modulation

This chapter introduces a media modulation-based mMTC solution to increase the throughput, utilizing a massive multi-input multi-output BS for enhanced detection performance. However, reliable active device detection and data decoding present a serious challenge in such an mMTC scenario. To address this problem, an efficient CS-based massive access solution is introduced, leveraging the sparsity of the UL massive access signals received at the BS. The adopted solution includes a structured orthogonal matching pursuit (StrOMP) algorithm for active device detection, exploiting the block sparsity of the UL access signals across successive time slots and the structured sparsity of media-modulated symbols to enhance detection performance. Furthermore, a successive interference cancellation (SIC)-based SSP algorithm is conceived for data demodulation of the active devices, leveraging the structured sparsity of media modulation-based symbols in each time slot to improve detection performance. Simulation results demonstrate the superiority of the considered scheme over state-of-the-art solutions.