A Spectrally Efficient MIMO System with Sparse Matrix Precoding

Abstract

This thesis proposes a novel technique of sparse matrix-based precoding at thetransmitter of a Multiple Input Multiple Output (MIMO) system. We proposedtwo sparse matrix precoded MIMO systems. Our first proposal improves thespectral efficiency beyond the existing spectral efficiency of Precoding-aided SpatialModulation (PSM-MIMO) system. Our second proposal increases spectralefficiency compared to an existing MIMO system.Both proposals use a two-stage precoding approach in which the conventionalzero-forcing (ZF) MIMO precoder, which inverts the matrix MIMO channel, iscombined with a sparse matrix precoding. With the conventional ZF precoder, thedegrees of freedom (DoF) available at the transmitter equals the number of antennasat the receiver. By adding another layer of precoding using a sparse matrix,we increase the DoF at the transmitter, thereby facilitating an increase in spectralefficiency. We demonstrate proof of the concept (PoC) by simulation-driven experiments.Our PoC is based on the ML (Maximum Likelihood) detection at thereceiver. ML detection has quite high complexity. We propose a belief propagationalgorithm at the receiver which is more practical to implement in a real-worldsystem. The belief propagation algorithm leverages the sparseness of the precodingmatrix and has low computational complexity.