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Angular-Domain Massive MIMO Detection: Algorithm, Implementation, and Design Tradeoffs
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DOI：10.1109/TCSI.2020.2968408.png)
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Abstract
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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.
Keywords:
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
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