期刊
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
卷 67, 期 6, 页码 1948-1961出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSI.2020.2968408
关键词
Massive MIMO; Complexity theory; Antennas; Antenna measurements; Detectors; Memory management; Massive MIMO detection; 5G new radio; angular-domain processing; CMOS technology; channel sparsity; VLSI implementation; digital baseband processing
资金
- Vetenskapsradet (Swedish Research Council) [D0582501]
In massive multiple-input multiple-output (MIMO) systems, the large size of channel state information (CSI) matrix significantly increases the computational complexity of uplink detection and size of required memory to store the channel data. To address these challenges, we propose to perform detection in the angular domain, where the channel information can be presented in a more condensed way. The underlying idea is to exploit the sparsity of massive MIMO channel in the angular domain to reduce the size of CSI matrix by selecting dominant beams. Then, an angular-domain linear detector followed by a non-linear post-processing scheme is proposed to perform detection using the reduced-size CSI. Evaluated using measured massive MIMO channels, our method results in 35%-73% reduction in complexity and required memory compared to traditional detectors while it achieves better performance. Moreover, this paper provides a framework, which trades between performance, complexity, and size of required memory. As a proof of concept, we implement the angular-domain detector in a 28 nm FD-SOI CMOS for a massive MIMO with 128 antennas communicating with up to 16 users. Synthesis result shows that our design attains a throughput of 2240 Mbps with an area of 829 k gates.
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