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The data traffic that is accumulated at the Macro Base Station (MBS) keeps on increasing as almost all the people start using mobile phones. The MBS cannot accommodate all user’s demands, and attempts to offload some users to the nearby small cells so that the user could get the expected service. For the MBS to offload data traffic to an Access Point (AP), it should offer an optimal economic incentive in a way its utility is maximized. Similarly, the APs should choose an optimal traffic to admit load for the price that it gets from MBS. To balance this tradeoff between the economic incentive and the admittance load to achieve optimal offloading, Software Defined Networking (SDN) assisted Stackelberg Game (SaSG) model is proposed. In this model, the MBS selects the users carefully to aggregate the service with AP, so that the user experiencing least service gets aggregated first. The MBS uses the Received Signal Strength Indicator (RSSI) value of the users as the main parameter for aggregating a particular user for a contract period with LTE and WiFi. Each player involved in the game tries to maximize their payoff utilities, and thus, while incorporating those utilities in real-time scenario, we obtain maximum throughput per user which experiences best data service without any lack in Quality of Experience (QoE). Thus, the proposed SaSG model proves better when compared with other game theory models, and hence an optimal data offloading is achieved.
Anbalagan et al. (Sat,) studied this question.