ScholarWorks@경상국립대학교

초록

Along with the rapid growth of Internet of Things (IoT), low power wide area networks (LPWANs) based on unslotted ALOHA, without the need for strict synchronization among IoT devices, becomes one of the cost-effective solutions to support wireless access for sensors requiring long-range connectivity, low cost, and low-power consumption. However, the increasing number of IoT devices poses potential congestion for ALOHA with a low throughput limit of 0.183 (data frames per frame transmission time). This work addresses the throughput limitations of ALOHA by implementing immediate collision resolution (ICR) and integrating an online Bayesian backoff algorithm. The focus is on lifting the throughput limit to enhance LPWANs performance. The work further details translating MAC layer modeling into practical implementation, emphasizing the integration of additional functionalities like uplink local sensing (ULS) and receive window. Our implemented ALOHA with ICR shows a substantial 29% throughput improvement, validating theoretical predictions. © 2005-2012 IEEE.

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