无线EH认知物联网网络资源分配研究

Research on resource allocation in wireless EH cognitive internet of things network

由于5G技术的快速发展,基于能量采集的认知物联网(Internet of things,IOT)具有很大的应用前景。针对无线物联网网络中存在的"doubly-near-far"问题,考虑在认知物联网网络中将能量采集与信息接收站分开管理,提出了一个基于能量采集的异构认知物联网网络模型,实现用户能效的最大化。此外,该模型不仅考虑能量采集,还考虑了频谱利用率低、频谱资源稀缺的问题,针对该网络优化问题,提出了一个混合整数非线性规划问题,通过信道分配、功率控制以及时间分配的联合优化的方法,考虑用户数据速率、干扰约束的同时,最大化能效。仿真实验结果证明了所提出模型以及算法的有效性。

With the rapid development of 5 G technology,cognitive internet of things(IOT)based on energy harvesting has a great application prospect.Aiming at the problem of"doubly-near-far"in wireless IOT networks,considering separate management of energy harvesting and information receiving stations in cognitive IOT networks,a heterogeneous cognitive IOT network model based on energy harvesting is proposed to maximize user energy efficiency.The model not only consider energy harvesting,but also consider the problem of low utilization of spectrum resources and scarce of spectrum resources.Aiming at the network optimization problem,a mixed integer non-linear programming problem is proposed.Through joint optimization method of the channel allocation,the power control and the time distribution,the user data rate and the interference constraint are considered at the same time to maximize the EE.The simulation results demonstrate the effectiveness of algorithm and model.