A Novel Efficient Stochastic Gradient Descent based MIMO Detector with Noise-Free Initialization

Multiple Input Multiple Output (MIMO) is a critical component of modern wireless communication systems, widely utilized for its enhancement of system capacity. However, one of the major challenges of MIMO is the high complexity of the detection algorithm. In this paper, we propose a novel low-complexity detection algorithm based on multi-layer perception (MLP) and stochastic gradient descent (SGD). This algorithm significantly accelerates convergence using zero-forcing initialization and momentum optimization method. Additionally, a fixed-point optimized hardware architecture is proposed. The proposed design achieves up to 2.39× higher area efficiency with respect to the existing solutions, making it a promising candidate for practical application.