Energy-efficient utility maximization for wireless networks with/without multipath routing

In wireless networks, end-to-end communication depends on link capacities which, in turn, are determined by transmit powers of interfering links. Optimal network performance and energy efficiency can be achieved by jointly optimizing congestion control and power control. In this paper, we study this joint optimization problem by formulating it into convex programming, i.e., we maximize a compound function which is a network utility function minus a factor, named tradeoff factor, of the associated power cost. We prove that this tradeoff factor is essential for good energy efficiency while maintaining the network throughput at a satisfactory level. The problem is solved by a distributed dual-decomposition based algorithm energy efficient jointly optimal congestion and power control (EJOC). EJOC tackles the power control problem in a recursive manner, operating as easily as the steepest descent method but converging much faster. This optimization framework is further extended to networks where each data source may have multiple alternative paths to its destination. Simulation results show that the proposed algorithm converges faster than other algorithm and is capable of significantly improving the energy efficiency of the network.