Traffic Offloading-Power Efficient Method using Game Theory for 5G Networks
Dense deployment of small cells in fifth generation (5G) networks can result in high power consumption caused by signalling overhead due to the extensive number of handovers and unbalanced load distribution among base stations in the network. This paper presents an integrated game theoretical and multiple attribute decision making (MADM) approach to offload the traffic from congested small cells by putting light-loaded small cells into passive mode without degrading the quality of service (QoS). The regret-based matching game is formulated to solve the cost function which deploys the base station load and power mode. Small cells select their ideal transmission power to approach the game equilibrium. After deploying the game approach, a multiple attribute Simple Additive Weighting (SAW) method is deployed to perform the handover (offloading) to the proper small cell in the network. Results reveal that our method largely reduces the power consumption and the number handovers, in addition to enhancing the throughput and load distribution in comparison to the conventional method.