Research On The Minimum Power Consumption Optimization For The 5G Small Cell Network

With the development of modern information society and the arrival of data era,wired broadband services have been gradually extended to the field of wireless terminal services.The traditional mobile communication system for voice and text transmission is gradually evolved to provide mobile users with HD picture,real-time video and multimedia services to a new generation of wireless mobile communication network.Small cell network(SCN)is not only an effective way of data distribution and providing data flow,but also can be installed in the blind area where the traditional base station can not cover or indoor where the signal intensity is not high.Therefore,small cell network can be used as an important form for the fifth generation mobile communication technology(5G)to improve the overall performance like the throughput and coverage ability.However,as the data increases exponentially,resulting in the explosive growth of the power consumption.This has become a hot issue which needs to pay close attention.In this paper,we focus on the optimization of the power consumption for downlink multi-user small cell network with considering the quality of service(QoS)and the power constraint.First based on a practical power consumption model taking into account both the dynamic transmit power and static circuit power,we formulate,then transform the power consumption optimization problem into a convex problem by using semi-definite relaxation technique,obtain the optimal solution and the relationship between the number of antennas and the number of users by the CVX tool.We further note that the optimal solution becomes infeasible for realistic implementation due to its heavy backhaul burden and computational complexity.To this end,we propose an alternative suboptimal algorithm which has low implementation overhead and complexity,based on minimum mean square error(MMSE)precoding.Furthermore,we propose an antenna selection(AS)algorithm combining with our optimization algorithms to further reduce the static circuit power consumption for the small cell network.Finally,simulation results show that the optimization is very effective and the proposed suboptimal algorithm is better than the optimal algorithm on significantly reducing the backhaul burden and computational complexity.Moreover,simulation results show that the optimization algorithms with antenna selection algorithm can further reduce the power consumption of the small cell network.