QoS-aware cell association based on traffic prediction in heterogeneous cellular networks

The mobile communication system has become increasingly complicated with the dramatic growth of user's requirement in quality of service (QoS). The high fluctuation of traffic data makes conventional cell association schemes difficult to guarantee satisfactory service in accord with traffic demand. In this study, the authors propose a novel QoS-aware cell association scheme in a heterogeneous network. Utilising traffic prediction achieved by support vector regression, the user can decide the best cell according to the future traffic demand. The authors aim at maximising the total throughput with consideration of channel gains and blocking probability in different cells and formulate the cell association as a binary combinatorial optimisation problem. Since users are selfish for their own benefits without the global information, the authors turn this problem into a game theoretical framework. To obtain the Nash equilibrium with low computation complexity, a heuristic dynamic selection algorithm is proposed by updating selection probability which enables each user to associate with the best cell independently. Numerical simulation results show that the proposed algorithm achieves a remarkable throughput gain. The number of satisfied users increases substantially under the different density of users compared with conventional cell association schemes.