The current wireless cellular networks can be used to provide machine-to-machine (M2M) communication services. However, the Long Term Evolution (LTE) networks, which are designed for human users, may not be able to handle a large number of bursty random access requests from machine-type communication (MTC) devices. In this paper, we propose a scheme that uses both access class barring (ACB) and timing advance information to prevent random access overload inM2M systems. We formulate an optimization problem to determine the optimal ACB parameter, which maximizes the expected number of MTC devices successfully served in each random access slot. Hence, the number of random access slots required to serve all MTC devices can be minimized.
To reduce the computational complexity and improve the practicability of the proposed scheme, we propose a closed-form approximate solution to the optimization problem and present an algorithm to estimate the number of active MTC devices requiring access in each random access slot. The correctness of the analytical model and the accuracy of the estimation algorithm are validated via simulations. Results show that both numerical and approximate solutions provide the same performance. Our proposed scheme can reduce nearly half of the random access slots required to serve all MTC devices compared to the existing schemes, which use timing advance information only, ACB only, or cooperative ACB.