Jointly optimal congestion control, channel allocation and power control in multi-channel wireless multihop networks

In this paper, to increase end-to-end throughput and energy efficiency of the multi-channel wireless multihop networks, a framework of jointly optimize congestion control in the transport layer, channel allocation in the data link layer and power control in the physical layer is proposed. It models the network by a generalized network utility maximization (NUM) problem with elastic link data rate constraints. Through binary linearization and log-transformation, and after relaxing the binary constraints on channel allocation matrix, the NUM problem becomes a convex optimization problem, which can be solved by the gateway centralized through branch and bound algorithm with exponential time complexity. Then, a partially distributed near-optimal jointly congestion control, channel allocation and power control (DCCCAPC) algorithm based on Lagrangian dual decomposition technique is proposed. Performance is assessed through simulations in terms of network utility, energy efficiency and fairness index. Convergence of both centralized and distributed algorithms is proved through theoretic analysis and simulations. As the available network resources increase, the performance gain on network utility increases.