Efficient IoT Compatible Sparse Recovery-Based Detectors for Differential Space Shift Keying MIMO System

Abstract

Space shift keying (SSK) presents itself as promising multi-input multi-output (MIMO) modulation technique that comply with the crucial need for high throughput and low complexity transmission schemes for Internet-of-Things (IoT) applications. This efficiency stems from the fundamental property of SSK scheme of activating only one single antenna at any time instant, which eliminates the inter-channel interference (ICI) and enables the use of single RF-chain at the transmitter. Conventional SSK is of coherent nature, which requires the channel state information (CSI) to be available at the receiver. Obtaining accurate CSI introduces significant complexity to the system. The non-coherent counterpart of SSK, namely Differential space shift keying (DSSK), overcomes the need to have the CSI at the receiver while retaining the inherent advantages of coherent SSK. The detection in DSSK is based on the received blocks at two consecutive time slots. However, the computational complexity and memory-size requirements of the existing optimal maximum-likelihood receiver of the DSSK system grow exponentially with the number of transmit antennas. This hinders the practical implementation of large-scale DSSK systems. Thus, this work aims at utilizing the inherent sparsity of DSSK schemes to propose a reduced complexity, yet reliable, detectors for DSSK schemes based on the theory of sparse recovery (SR). Achieved results demonstrate significant computational complexity reduction with pragmatic error rate, especially for large-scale scenarios.