NOMA-Aided Pure ALOHA with Immediate Collision Resolution for Low-Power IoT Communications

Abstract

ALOHA has become an essential random access protocol for low-power wide-area networks (LPWANs) due to its compatibility with low-cost, low-power consumption and long-range communication requirements. However, its inherent throughput limitation of approximately 0.183 packets per packet transmission time for a large user population significantly restricts its scalability and suitability for the rapidly growing number of IoT devices. To surpass this fundamental bound, we propose a non-orthogonal multiple access (NOMA)-based collision resolution scheme that enables devices to initiate immediate contention-resolving retransmissions following a collision event. This approach requires only an additional collision timer for each user to determine collision resolution participation and appropriate transmission power selection, thereby substantially enhancing throughput without incurring additional hardware costs. We present an analytical framework to evaluate the achievable system throughput and develop an online backoff algorithm that leverages an extended Kalman filter (EKF)-based backlog estimator to dynamically maximize system performance. Numerical results confirm the reliability of the proposed scheme, demonstrating that the system throughput can be improved to approximately 0.5 packets per packet transmission time under ideal conditions. Moreover, the EKF-based approach closely approximates optimal throughput and delay performance under both Poisson and bursty traffic conditions.