Maximizing System Throughput in D2D Networks Using Alternative DC Programming

Power control plays an important role in improving the system throughput in communication system since co-channel interference is a major limitation to the system throughput. The power control problem of maximizing the system throughput in the multiuser and multichannel communication system is a highly complicated nonconvex problem since user are interfered with one another if operating in the same wireless channel. We reformulate the nonconvex objective function of this problem as a difference of two convex functions, which is called DC (difference of convex function) programming. To reduce the computation complexity in the high dimensional space, we introduce an alternative power allocation scheme to search in the low dimensional space, where each user updates its power sequentially. A global optimal power allocation is found by utilizing the branch-and- bound algorithm for each user while taking other users' power allocation as constant value. Furthermore, we incorporate each user's maximum power and minimum data rate constraint into the optimization framework. We found that the minimum data rate constraint of each user can be turned into multiple linear inequalities and then be added to the DC programming optimization framework. The simulation results show that our introduced method achieves the highest sum data rate compared to the state-of-the-art methods, including iterative water filling and geometric programming.