Power Allocation Algorithm In Wireless Networks Based On Convex Optimization

In today's communications field,with the increasing demand for users,the scale of communication facilities continues to grow.As a result,the corresponding energy consumption has also increased correspondingly,which makes green communication become the mainstream trend of communication system development.In the research of green communication networks,power control technology has attracted much attention.It can acquire network systems under various conditions such as limited energy of network nodes,mutual interference between signals,and attenuation of channels.The feedback information is used to adjust the transmission power of each node,thereby realizing the effective allocation of power and maximizing the utilization of network resources.Therefore,power control technology is a research hotspot to improve energy efficiency,reduce energy consumption,and ensure the fairness of network systems.In order to maximize the minimum transmission rate and minimize the total energy consumption in the network system,this thesis proposes different distributed power control methods based on convex optimization.The main results of this thesis are as follows:1.At first,we transform the problem of improving the bottleneck rate of the wireless network into the max-min fairness optimization problem.In order to guarantee the minimal transmit data rate,we leverage the bit error rate(BER)with Q-function to model the achievable data rates with signal to interference plus noise ratio(SINR).After that,we prove that the mathematical model of the maximumminimum fairness optimization problem is approximated as a concave function based on the PerronFrobenius theorem.Then we propose a distributed power control algorithm to obtain the optimal solution.2.For the problem of minimizing the total power consumption in wireless communication network systems,this thesis first proposes a dynamic algorithm,which can quickly calculate the final power allocation scheme.Then we prove the feasibility and convergence of the algorithm.Further,we discuss that there may be no solution in the problem of minimization of total power consumption.In terms of this problem we propose a dynamic algorithm that adapts the rate requirements to minimize the total energy consumption and to simultaneously provide fairness guarantees.After that,we discuss a variety of different wireless communication scenarios with minimum transmission rates.Numerical simulations show the efficient performance of the proposed algorithms.