During the last decade, the number of devices connected to the Internet by Wi-Fi has grown significantly. A high density of both the client devices and the hot spots posed new challenges related to providing the desired quality of service in the current and emerging scenarios. To cope with the negative effects caused by network densification, modern Wi-Fi is becoming more and more centralized. To improve network efficiency, today many new Wi-Fi deployments are under control of management systems that optimize network parameters in a centralized manner. In the paper, for such a cloud management system, we develop an algorithm which aims at maximizing energy efficiency and also keeps fairness among clients. For that, we design an objective function and solve an optimization problem using the branch and bound approach. To evaluate the efficiency of the developed solution, we implement it in the NS-3 simulator and compare with existing solutions and legacy behavior.
While the demand for battery capacity on mobile devices has grown with the increase in high-bandwidth multi-media rich applications, battery technology has not kept up with this demand. Therefore power optimization techniques are becoming increasingly important in wireless system design. Power optimization schemes are also important for interference management in wireless systems as interference resulting from aggressive spectral reuse and high power transmission severely limits system performance. Although power optimization plays a pivotal role in both interference management and energy utilization, little research addresses their joint interaction. In this paper, we develop energy-efficient power optimization schemes for interference-limited communications. Both circuit and transmit powers are considered and energy efficiency is emphasized over throughput. We note that the general power optimization problem in the presence of interference is intractable even when ideal user cooperation is assumed. We first study this problem for a simple two-user network with ideal user cooperation and then develop a practical non-cooperative power optimization scheme. Simulation results show that the proposed scheme improves not only energy efficiency but also spectral efficiency in an interference-limited cellular network.