Massive MIMO 1-Bit DAC Transmission: A Low-Complexity Symbol Scaling Approach
September 24, 2017 Β· Declared Dead Β· π IEEE Transactions on Wireless Communications
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Authors
Ang Li, Christos Masouros, Fan Liu, A. L. Swindlehurst
arXiv ID
1709.08278
Category
eess.SP: Signal Processing
Cross-listed
cs.IT
Citations
123
Venue
IEEE Transactions on Wireless Communications
Last Checked
4 months ago
Abstract
We study multi-user massive multiple-input single-output (MISO) systems and focus on downlink transmission, where the base station (BS) employs a large antenna array with low-cost 1-bit digital-to-analog converters (DACs). The direct combination of existing beamforming schemes with 1-bit DACs is shown to lead to an error floor at medium-to-high SNR regime, due to the coarse quantization of the DACs with limited precision. In this paper, based on the constructive interference we consider both a quantized linear beamforming scheme where we analytically obtain the optimal beamforming matrix, and a non-linear mapping scheme where we directly design the transmit signal vector. Due to the 1-bit quantization, the formulated optimization for the non-linear mapping scheme is shown to be non-convex. To solve this problem, the non-convex constraints of the 1-bit DACs are firstly relaxed, followed by an element-wise normalization to satisfy the 1-bit DAC transmission. We further propose a low-complexity symbol scaling scheme that consists of three stages, in which the quantized transmit signal on each antenna element is selected sequentially. Numerical results show that the proposed symbol scaling scheme achieves a comparable performance to the optimization-based non-linear mapping approach, while its corresponding complexity is negligible compared to that of the non-linear scheme.
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