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Overcoming the conventional trade-off between throughput and bit error rate(BER) performance, versus computational complexity is a long-term challenge foruplink Multiple-Input Multiple-Output (MIMO) detection in base station designfor the cellular 5G New Radio roadmap, as well as in next generation wirelesslocal area networks. In this work, we present ParaMax, a MIMO detectorarchitecture that for the first time brings to bear physics-inspired paralleltempering algorithmic techniques [28, 50, 67] on this class of problems.ParaMax can achieve near optimal maximum-likelihood (ML) throughput performancein the Large MIMO regime, Massive MIMO systems where the base station hasadditional RF chains, to approach the number of base station antennas, in orderto support even more parallel spatial streams. ParaMax is able to achieve anear ML-BER performance up to 160x160 and 80x80 Large MIMO for low-ordermodulations such as BPSK and QPSK, respectively, only requiring less than tensof processing elements. With respect to Massive MIMO systems, in 12x24 MIMOwith 16-QAM at SNR 16 dB, ParaMax achieves 330 Mbits/s near-optimal systemthroughput with 4--8 processing elements per subcarrier, which is approximately1.4x throughput than linear detector-based Massive MIMO systems.

Physics-Inspired Heuristics for Soft MIMO Detection in 5G New Radio and Beyond