Hardware Efficient Massive MIMO Detector Based on the Monte Carlo Tree Search Method

Abstract

A Monte Carlo tree search (MCTS)-based large-scale multiple-input, multiple-output (MIMO) detector is proposed. We describe how the MCTS algorithm, which has been successfully used in decision-making and game-playing problems, can be applied to MIMO detection. In particular, we discuss how the tree policy, default policy, simulation, and backpropagation steps of MCTS can be adapted to MIMO detection. We also describe some optimizations that reduce both the bit error rate and the computational complexity. The proposed MCTS MIMO detector exhibits performance that is comparable to existing methods while having a lower computational load. The design has been implemented in a 65-nm CMOS technology. For a $64 \times 8$ MIMO system, it achieves a throughput of 665 Mbps with a core area of 1.43 mm2, and it exhibits higher hardware efficiency than previous MIMO detector designs in the literature.