Sparse Vector Codes for MIMO lSI Channels with Low-Resolution ADCs

This paper presents a joint modulation and coding technique called quantized sparse vector code (QSVC) for multiple- input multiple- output (MIMO) inter-symbolinterference (lSI) channel with low-resolution analog-to- digital converters (ADCs). The key idea of Q-SVC is to encode sparse information bits over the space- time domain by a superposition of selected dictionary vectors. To decode Q-SVC from coarselyquantized measurements in a computationally efficient manner, we present a greedy sparse signal detection algorithm called Bayesian multipath matching pursuit (BMMP). The simulation results demonstrate that the proposed encoding and decoding pair can outperform the existing coded-modulation techniques in terms of both the frame error rate ( FER) and the computational complexity.