Compressive Sensing based Low Complexity Terahertz Receiver

Abstract

Terahertz (THz) communication is recognized as a promising technology that could help meet the growing demand of wireless system for the forthcoming 6G wireless technology. However, sampling rate required for signal processing in the THz system is very high and difficult to realize in practical systems. To combat this need for sampling at THz rates, the THz signal detection and demodulation at sub-Nyquist rate is carried out at the receiver. In this paper, we propose a signal-matched (SM) measurement matrix for THz system for sub-Nyquist rate sampling. The proposed SM matrix senses signal containing higher energy more efficiently as compared with the commonly used Gaussian and discrete cosine transform (DCT) matrices in the compressed sensing (CS) framework. Theoretical analysis and simulation results show that the bit error rate (BER) performance of a CS-based $T$ Hz receiver utilizing the proposed SM measurement matrix is better than the popular Gaussian and DCT measurement matrices, and is close to a conventional system sampled at Nyquist rate albeit with much lower system complexity. © 2021 IEEE.