A Low Complexity Expectation Propagation Algorithm for Active User Detection for Massive Connectivity
Rui Ma, Yuanli Ma, Jikun Zhu, Zheng Wang, Yuekai Cai · 2025
As the scale of Internet of Things (IoT) grows rapidly, accurate active user detection has emerged as an important problem in massive connectivity scenarios. This paper presents a novel low-complexity expectation propagation (LC-EP) algorithm for massive connectivity. Different from traditional methods that reduce the complexity of EP through channel hardening, LC-EP exploits a new statistical convergence property of the Gram matrix for the complexity reduction. Meanwhile, the decision method is modified from the original log-likelihood ratio (LLR)-based approach to an order-based method for the future performance gain. Simulation results demonstrate that the proposed LC-EP algorithm improves both detection accuracy and efficiency.