Utility-based power control in wireless networks has been widely recognized as an effective mechanism to managing co-channel interferences. It is based on the maximization of system utility subject to power constraints, which is referred to as power control optimization problem. Global coupling between the mutual interference of wireless channels increases the difficulty of searching global optimum significantly. In this paper, we decouple the optimization problems with concave and non-concave utility functions; and transform them into a global consensus problem by introducing locally slack variables. We then propose two distributed iterative optimization algorithms for the global consensus problems with concave and non-concave objective functions, respectively, based on an alternating direction method of multipliers. Furthermore, we prove that both algorithms converge to the global optimum of the total network utility. Simulation results show the effectiveness of the algorithms. Comparison experiments show that the developed algorithms compare favourably against some other well-known algorithms.

With the ever-increasing wireless data application recently, considerable efforts have been focused on the design of distributed explicit rate scheme based on Network Utility Maximization (NUM) or wireless multi-hop mesh networks. This paper describes a novel wireless multi-hop multicast flow control scheme for wireless mesh networks via 802.11, which is based on the distributed self-turning Optimal Proportional plus Second-order Differential (OPSD) controller. The control scheme, which is located at the sources in the wireless multicast networks, can ensure short convergence time by regulating the transmission rate. We further analyze the theoretical aspects of the proposed algorithm. Simulation results demonstrate the efficiency of the proposed scheme in terms of fast response time, low packet loss and error ration.