Detection in Sporadic Multiuser Systems over 3GPP LTE Networks

In this paper, we study the employability of compressed sensing algorithms in the context of multiuser detection in machine to machine systems over 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) framework. The key idea of this work is to exploit the sparsity in the Machine to Machine (m2m) communication which is rendered by the sporadic nature of the transmission by the machines. We have analyzed the Bit Error Rate (BER) performance for various signal to noise ratio conditions and the impact of sparsity indicated by the probability of activity, operational frequencies and antenna spacing at the base station on the detection performance of the system. Through the results, we substantiate that the compressed sensing algorithms prove to be a viable choice for multiuser detection and practical implementation.