Power Allocation Scheme Of Mobile Terminal In Heterogeneous Wireless Networks

In the past ten years, wireless communication and relevant industry have developed rapidly. A variety of heterogeneous wireless networks and technologies emerge. These heterogeneous networks emphasize on different clients and different business, which are hard to replace each other. Nowadays, single network has been difficult to meet the diverse needs of users. Additionally, each heterogeneous works independently that easily causes low efficiency of network resource utilization. This problem can be effectively solved through the integration and collaboration of heterogeneous wireless networks. But at the same time the integration and collaboration of multiple networks brings new problems. The battery capacity of the mobile terminal raises higher requirements, how to improve communication quality while reducing power consumption as much as possible is a key issue. Heterogeneous network management and control has become a critical problem to the entire communication system. Power control and allocation is an important part of the management of heterogeneous network resources, such as lower power consumption and improvement of the communication system quality. From the perspective of power control and allocation, the article points to study the mechanism of terminal power allocation under heterogeneous network collaborative environment.Firstly, this paper briefly introduces the communication and collaboration of heterogeneous network, analyzes the basic principle of cooperative communication technology and the relay cooperative model. Secondly, in view of the difference between heterogeneous network and homogeneous network, this paper introduces particle swarm algorithm to the power allocation scheme of mobile terminal, and presents a potential learning based particle swarm algorithm. This algorithm has several improvements:1,Put a potential learning item in the velocity update process by introducing “potential learning” concept;2,Improve the inertia weight parameter;3, Add a variation mechanism in the process of evolution to avoid falling into local optimal solution. Finally, this paper designs a utility function which targets on terminal power consumption and system received SNR, and applies the improved algorithm to the power control and distribution research of mobile terminal, to optimize the mobile power consumption and system signal-to-noise ratio.