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Machine-to-Machine Communications With Massive Access: Congestion Control

With the deployment of machine-to-machine (M2M) communications, it is expected that the number of devices will enormously increase. When these devices attempt to concurrently access the network, a radio access network overload problem arises. In this case, the conventional random access procedure used in Long Term Evolution-Advanced (LTE-A) networks is rendered inefficient due to the frequent collisions that lead to excessive delay and resource wastage. In this paper, we propose an efficient scalable overload control algorithm for M2M with massive access. The proposed algorithm can allocate the uplink resources within bounded contention time in a distributed manner. Hence, it can achieve full resource utilization that leads to reduced: access delay, energy consumption, and blocking probability. Additionally, we provide a method for estimating the number of backlogged devices in the network. The performance of the proposed algorithm is evaluated analytically and using simulations. To prove its effectiveness, the performance of the proposed algorithm is compared to the dynamic-access class-barring scheme, where the results depict the superiority of the proposed scheme. Finally, a binary integer programming problem is formulated, where we show that the achieved access delay using the proposed algorithm approaches the optimal value.