Real-Valued Fixed-Complexity Sphere Decoder for High Dimensional QAM-MIMO Systems

The development of high performance, low computational complexity detection algorithms is a key challenge for real-time multiple-input multiple-output (MIMO) communication system design. The fixed-complexity sphere decoder (FSD) algorithm is one of the most promising approaches, enabling quasi-ML decoding accuracy and high performance implementation due to its deterministic, highly parallel structure. However, it suffers from exponential growth in computational complexity as the number of MIMO transmit antennas increases, critically limiting its scalability to larger MIMO system topologies. In this correspondence, we present a solution to this problem by applying a novel cutting protocol to the decoding tree of a real-valued FSD algorithm. The new real-valued fixed-complexity sphere decoder (RFSD) algorithm derived achieves similar quasi-ML decoding performance as FSD, but with an average 70% reduction in computational complexity, as we demonstrate from both theoretical and implementation perspectives for quadrature amplitude modulation (QAM)-MIMO systems.