One-bit massive MIMO precoding via a minimum symbol-error probability design

March 13, 2018 Β· Declared Dead Β· πŸ› IEEE International Conference on Acoustics, Speech, and Signal Processing

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Authors Mingjie Shao, Qiang Li, Wing-Kin Ma arXiv ID 1803.04787 Category cs.IT: Information Theory Citations 30 Venue IEEE International Conference on Acoustics, Speech, and Signal Processing Last Checked 4 months ago
Abstract
Massive multiple-input multiple-output (MIMO) has the potential to substantially improve the spectral efficiency, robustness and coverage of mobile networks. However, such potential is limited by hardware cost and power consumption associated with a large number of RF chains. Recently, one-bit quantization is proposed to address this issue by replacing high-resolution digital-to-analog converters (DACs) with one-bit DACs, thereby simplifying the RF chains. Despite low system cost, advanced signal processing techniques are needed to compensate for quantization distortions caused by low resolution DACs. In this paper, a symbol-error-rate (SER)-based one-bit precoding scheme is proposed to minimize the detection error probability of all users under one-bit constraints. The problem is recast as a continuous optimization problem with a biconvex objective. By applying the block coordinate descent (BCD) method and the FISTA method, we develop an efficient iterative algorithm to obtain a one-bit precoding solution. Simulation results demonstrate its superiority over state-of-the-art algorithms in terms of bit error rate performance in high-order modulation cases.
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