Evolutionary game based access class barring for machine-to-machine communications

Abstract

Machine-to-machine (M2M) communication faces the most critical challenge that when a massive number of MTC devices perform random access, there will be severe congestions. 3GPP developed a network coordinated random access stabilization scheme known as the access class barring(ACB) to deal with the problem in LTE-Advanced. However, MTC devices in overlapped areas still suffer severe access delays due to the noncooperation and individual setting of ACB factor among BSs. We propose evolutionary game based ACB algorithm to help MTC devices alleviate congestions and thus eliminate substantial defects in the ordinary ACB. Finally, the performance of the evolutionary game based ACB algorithm is analysed, and simulation results show the convergence and effectiveness of the proposed algorithm.