Machine-to-machine (M2M) communications, also known as machine-type communications (MTC) in 3GPP LTE systems, provide autonomous connectivity between machines without human intervention to create new service, e.g., the Internet of Things and the smart grid. M2M communications normally involve a large number of MTC devices (MTCDs) to support a variety of sensor applications. Consequently, concurrent and massive access attempts of MTCDs to radio access networks (RANs) may cause intolerable delay, packet loss, and even service unavailability. In this paper, we propose a joint optimal physical random access channel (PRACH) resource allocation and access control mechanism to address the performance degradation caused by concurrent and massive access attempts of MTCDs in LTE systems. We define the notion of random access efficiency and formulate an optimization problem for maximization of the random access efficiency with random access delay constraint. We also propose a dynamic resource allocation and access control algorithm based on estimation of the number of MTCDs for a system with dynamically varying numbers of massive MTCDs. Then, an analytical model is provided using a discrete-time Markov chain for the proposed mechanism. The effectiveness of the proposed algorithm is demonstrated via analysis and simulations. The proposed algorithm was able to maintain the optimal random access efficiency while satisfying the average random access delay requirement of MTCDs in order to handle massive and dynamic MTCDs per cell.Index Terms-M2M communications, dynamic resource allocation, access control, random access efficiency, optimization 1536-1276 (c)

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