基于5G 毫米波协作通信的小单元无线能量信标优化部署策略

Optimization Deployed Strategy of Wireless Power Beacon based on 5G Millimeter Wave Cooperative Communication Small Cell

关键词:  无线携能通信  移动边缘计算  设备间通信  任务卸载  功率分配

Key words:  High-low frequency hybrid networking  power beacon  millimeter wave cooperative communication  deployment optimization  greedy algorithm  energy harvesting.

摘要:

为实现5G无线网络中高频谱效率与低能耗的绿色通信，针对5G边缘网络，构建一个高低频混合组网的能量受限型用户设备(User Equipment Devices, UE) 毫米波协作通信的小单元网络模型。该模型用低成本、无回程的能量信标代替传统宏基站为UE提供能量补给，使UE彼此间可相互通信；通过设计一个 “需求-选择-建链”模式的新型建链协议，将通信毫米波定向传输技术应用于该建链过程中。在此模型基础上，以提高边缘系统频谱效率和能量收集覆盖率为目标，提出一个基于5G毫米波协作通信的小单元无线能量信标优化部署策略，通过最小化固定充电的能量信标数量，在实现系统能耗最小化问题基础上保证系统的正常运行。针对该最优化问题是一个混合整数规划的NP-难问题，设计一个具有常数因子的贪心算法近似求解优化问题。理论分析证明了算法的可行性。仿真结果表明，本文策略能有效优化能量信标部署，在同等覆盖率与区域频谱效率增益下能耗最低。

Abstract:

In order to implement the green communication with high spectral efficiency and low energy consumption in 5G wireless network, a new small cell network model of user equipment devices (UE) and millimeter wave(mmWave) cooperative communication for high-low frequency hybrid networking was established. This model used power beacons (PBs) to replace the conventional base station (BSs) to provide energy supply for the energy-constrained UEs in 5G edge network， and applied the directional transmission technology of the communication mmWave to the process of building the chain by designing a new “Build to Order(BTO)” protocol. In order to improve the spectrum efficiency and energy harvesting coverage rate of edge system, an optimized deployment strategy of small cell wireless energy beacon based on 5G mmWave cooperative communication was proposed. By minimizing the number of PBs in fixed charging, the strategy ensures the normal operation of the system on the basis of minimizing the energy consumption of the system. Since this problem is a mixed integer programming problem and is known to be NP-hard, a greedy algorithm with constant factors is designed to solve the optimization problem approximately. Theoretical analysis proves the feasibility of the algorithm. The simulation results show that the proposed strategy can effectively optimize the PBs deployment, and the energy consumption is the lowest under the same coverage and regional spectrum efficiency gain.