Low Complexity Uplink Grant-Free NOMA Based on Boosted Approximate Message Passing

Abstract

We propose a new framework of uplink grant-free non-orthogonal multiple access (NOMA) composed of user activity detection, channel estimation, and data detection. Since the original problem becomes the multiple-measurement vector recovery (MMVR) problem and requires high complexity to solve, we employ an approach based on reduce-MMV-and-boost (ReMBo) together with approximate message passing (AMP) to reduce the complexity significantly. Computer simulations confirm that the proposed framework exhibits the symbol error rate (SER) close to the conventional one while even lower complexity.