Network coded soft forwarding for multiple access relay channels with compressive sensing

In this paper, we propose a novel estimate-and-forward (EF) transmission protocol, and combine it with the essence of compressive sensing (CS) for a network consisting of two correlated sources, one relay and one destination. Compared with the conventional estimate-and-forward (EF) protocol, in our protocol, correlation is exploited in calculating the soft symbols at the relay. Then we transform the network coded soft symbol vector into a sparse vector, which is suitable for compression by using CS. We analyze that the soft symbols in the proposed protocol are more suitable than those in the EF protocol for CS. Simulations show that our protocol can achieve as good bit error rate performance as the uncompressed EF protocol with reduced transmission time at the relay, thus improving the system throughput performance.