Coordination Of Energy Consumption And Interference In Software Defined Wireless Networks

In recent years,the energy wasting and interference caused by the wireless access devices deployed densely have become more and more serious.Most previous works focused on energy saving or interference suppression unilaterally,while the interaction of each other has been rarely considered,which may result in a suboptimization of the energy saving and performance improvement.Therefore,in high-density WLANs,how to meet the communication requirements of users with the optimal APs and transmit power becomes a new goal of system resource optimization.Aiming at solving these above problem,in the scenario of densely deploying APs,using the centralized control characteristics of SDWN technology,a coordination optimization algorithm for energy consumption and interference based on Bayesian game is proposed.By guaranteeing the communication demand of users in WLANs,our algorithm makes the no-load APs and interference APs slept and adjust the wake-up APs' transmit power to realize the joint optimization of energy consumption and interference.Firstly,a large number of actual measurements are implemented to verify the impact of interference on performance and energy consumption.Moreover,mathematical software is used to quantify the relationship among energy consumption,traffic load and transmit power of single AP.Then,based on the above measured model,an energy consumption and interference coordinated optimization algorithm based on Bayesian game is proposed.This algorithm aims at maximizing the benefits of each AP,combines the measured model,inter-AP interference,and users' requirements to design a Bayesian game model to solve the problem of sleep AP selection and wake-up APs' transmit power adjustment.However,when handling with enormous network nodes,the algorithm cannot obtain an optimal resource allocation scheme within limit period due to the high computational complexity.Therefore,a fast iteration-based algorithm is proposed,which operated on Bayesian game,applies clustering and iterative ideas to realize the coordinated optimization of energy consumption and interference.Finally,the algorithm is verified on the MATLAB and actual SDWN experiment platform.The experimental results show that our algorithm can improve the energysaving ratio from one percent to four percent,compared with the existing joint optimization algorithm while guaranteeing the user's communication demand.At the same time,the average channel capacity of single AP can be improved from two percent to 17%,the average channel capacity of single user can be improved from five percent to 48%.Therefore,our algorithm can not only reduce the cost but also improve the network performance.