Coalition game-theory-based congestion control in Hybrid Fi-Wi indoor network

As more bandwidth hogging applications like video streaming or video conferencing are entering the telecom market, indoor networks need to be more efficient, failure-resilient and flexible. WiFi have predominantly been the most ubiquitous indoor wireless technology. WiFi Access Points (APs) are placed progressively in indoor locations resulting in highly congested ISM spectrum bands. Thus users are experience diminishing data rates. Hybrid Fiber-Wireless (Fi-Wi) architecture are pursued as the way forward for such large indoor networks. Fi-Wi provides a future proof backbone for supporting multiple wireless technologies indoor via a centralized controlled architecture. A residential gateway namely Home Communication Controller (HCC) hosts all APs and serve as the brain of the indoor network. Cell Access Nodes (CANs) located inside each room distributes the radio signals and are connected to the HCC (i.e. APs) using different optical wavelengths. The flexibility of the architecture makes it possible to switch the connection of APs with a different set of CANs periodically in order to reduce the congestion level of the whole network. Game theory is regarded as a major mathematical tool in formulating such congestion control problems. In this work we formulate the problem of congestion control using coalition game theory and propose a centralized assignment algorithm to dynamically assign CANs to APs. We prove that the assignment algorithm terminates in a stable partition which attains optimal grand aggregate utility for the network. The simulation results project a maximum decrease of 45% congestion level with 200 non-uniformly distributed users in the network.