Design and Performance Evaluation of Successive Interference Cancellation-Based Pure Aloha for Internet-of-Things Networks

Abstract

This paper presents the design and performance evaluation of successive interference cancellation (SIC)-based pure Aloha (PA) for Internet-of-Things (IoT) networks. To this end, a window-based SIC algorithm is presented. A throughput model of the SIC-based PA is developed and analyzed to study both throughput and packet delivery ratio (PDR) performance metrics. The numerical results show that high throughput gain can be achieved in PA, thanks to the increased PDR contributed by the SIC. Specifically, after ten iterations of the SIC, the maximum throughput gain of the SIC-based PA can achieve up to 6.55 dB over the conventional PA. The SIC efficiency results also suggest that the interference residual level after each iteration of SIC plays an important role in terms of improving throughput in PA networks. Finally, the conditions under which the proposed SIC-based PA meet both throughput and PDR performance requirements are discussed.