Turbo detection based on signal simplicity and compressed sensing for massive MIMO transmission

International audienceIn this paper, we address the problem of large MIMO detection assuming QAM constellations. We show that the QAM signal becomes a simple signal (that is to say a bounded signal with extreme elements equal to the inferior and superior bounds [1]) after a real transformation. Based on this property, we present a low complexity detection algorithm which significantly outperforms classic algorithms such as zero forcing (ZF) and minimum mean square error (MMSE) algorithms. The proposed detection technique is based on a quadratic programming criterion whose constraints ensure that the detected vector is simple. We implement it successfully in an underdetermined MIMO system (the number of observations is less than the number of sources) and we show the necessary conditions of success detection. Then we consider an outer forward error correcting (FEC) code and we propose a turbo detection scheme. Based on the investigation of the output detector statistics in [2], we propose a symbol to binary converter (SBC) which can feed the FEC decoder with reliable output. On the other side, from the second iteration, the detection scheme resorts to a regularized quadratic criterion so that the searched vector draws near to the estimate resulting from the FEC decoder output. Simulation results show the efficiency of the proposed scheme