A quadratic programming-based detector for large-scale MIMO systems

In this contribution, we present a low complexity detection algorithm that is based on a quadratic programming (QP) formulation. It provides better trade-offs between complexity and performance, especially in large-scale MIMO systems. It also achieves better bit error rate (BER) performance than known heuristic algorithms in large-scale MIMO literature, such as Local Ascent Search and Reactive Tabu Search algorithms, especially at higher-order modulations. This algorithm improves the performance of the conventional QP detectors using two stages of QP with the concept of interference cancellation and also with the concept of shadow area constraints as a measure of symbols reliability. Thus, we call it a Two-stage quadratic programming detector. Computer simulations demonstrate the efficacy of the proposed algorithm in large-scale MIMO systems for both uncoded and turbo coded cases.