A Spectrally Efficient MIMO System with Sparse Matrix Precoding

This paper proposes a novel technique of sparse matrix based precoding at the transmitter of a Multiple Input Multiple Output (MIMO) system. Our proposal, which we have called SMP-MIMO (Sparse Matrix Precoded MIMO), uses a two-layer precoding approach in which the conventional zero-forcing (ZF) MIMO precoder, which inverts the matrix MIMO channel, is combined with a sparse matrix precoding. With the conventional ZF precoder, the degrees of freedom (DoF) available at the transmitter equals the number of antennas at the receiver. By adding another layer of precoding using a sparse matrix, we increase the DoF at the transmitter, thereby facilitating an increase in the spectral efficiency compared to the ZF-precoded MIMO. We demonstrate a proof of the SMP-MIMO concept (PoC) by simulation-driven experiments. Our PoC is based on the ML (Maximum Likelihood) detection at the receiver. The resulting computational complexity can be reduced by applying a compressive sensing algorithm or a belief propagation algorithm that leverages the sparseness of the precoding matrix.