The deployment of machine-to-machine (M2M) communications on cellular networks provides ubiquitous services to Internet-of-Things (IoT) systems. Cellular networks have been chosen as the best infrastructure for M2M communications due to the wide coverage and spectral efficiency. However, with the increased number of devices connecting to the network, massive number of devices are expected to simultaneously access the network resources. This massive access results in excessive congestion and collisions in the random access channel (RACH) which causes major degradation in systems performance. This paper focuses on resolving the RACH collisions during the massive access scenarios for cellular M2M communications. We propose a collision resolution scheme using the backoff procedure which dynamically adjusts the backoff indicator (BI) based on the number of backlog devices and the available resources. The proposed scheme is integrated with three well-known random access schemes; standard random access (SRA), static access class barring (ACB) and dynamic access class barring (DAB). Furthermore, the paper presents an analysis for access success probability based on the dynamic backoff procedure. The optimal value of BI that achieves the highest access success probability is derived for the three different schemes. The analysis and simulation results indicate that the dynamic value of BI achieves approximately 99.9% access success rate with a slight increase in access delay of around 10%, which is considered a reasonable increment for delay-tolerant applications during the massive arrivals scenarios.
Machine-to-machine (M2M) communications on Long-term evolution (LTE) networks form a substantial part for the Internet-of-things (IoT). The random access procedure is the first step for M2M devices to access network resources. Many researchers have attempted to improve the efficiency of the random access procedure. This work revisits the performance of the hybrid random access protocols which combine congestion control techniques with collision resolution techniques. In particular, we investigate two hybrid protocols. The first one combines the pre-backoff (PBO) with tree random access (TRA), and the second one combines dynamic access barring (DAB) with TRA. The probability analysis is presented for both protocols. The performance is evaluated based on the access success rate, the mean throughput, the mean delay, the collision rate and the mean retransmissions. The simulation results show that the hybrid protocols achieve the highest success rate and throughput with moderate delay and low collision rates with a lower mean number of retransmissions compared to three benchmarks that apply either a congestion control or a collision resolution. The opportunities of future developments of hybrid protocols are listed at the end of this paper to highlight the issues that could be investigated to improve the performance of hybrid random access protocols.
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