Compressive Sensing Multi-User Detection for MC-CDMA System in Machine to Machine Communication

Abstract

Machine to Machine (M2M) Communication is one of the core technologies of 5G in the future. To relieve control signal overhead lead by massive access during M2M communication, we use greedy algorithm from the field of CS to perform joint Multi-User (MUD) detection of activity and data by taking advantage of sporadic nature of certain M2M applications. The simulation results show that it is effective in recovering sparse input signals as well as gaining higher spectral efficiency. We also show that combining cross validation (CV) with the greedy algorithm is reliable in identifying the sparsity level of input vector which makes CS-MUD more practical.