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

Yunseo Nam, Yo-Seb Jeon, Byonghyo Shim

Abstract: This paper presents a joint modulation and coding technique called quantized sparse vector code (Q-SVC) for multiple-input multiple-output (MIMO) inter-symbol-interference (ISI) 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 coarsely-quantized 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.