一种面向电力物联网的认知D2D网络能效资源分配算法

在电力物联网中为了提高D2D(device-to-device)网络的频谱效率和系统能效,考虑不完美信道状态信息(channel state information, CSI)的影响,提出了一种鲁棒能效最大的资源分配算法。考虑D2D用户最大发射功率约束、蜂窝用户功率约束和共道干扰功率约束,建立下垫式频谱共享模式下混合蜂窝/D2D通信的上行传输资源分配模型；考虑蜂窝用户干扰中断约束,基于最小最大概率机和辅助变量法,将原非凸优化问题转换为凸优化求解。基于凸优化理论,获得鲁棒资源分配问题的解析解。仿真结果表明所提算法的有效性。

Energy-efficient resource allocation algorithm for cognitive D2D networks for Power IOT

In order to improve spectral efficiency and system energy efficiency of device-to-device (D2D) networks in power IOT, a robust energy-efficient maximization resource allocation algorithm is proposed under the consideration of imperfect channel state information (CSI). Considering the maximum transmit power constraint of D2D user, the maximum transmit power of cellular user and the co-channel interference constraint, an uplink resource allocation model is formulated for hybrid cellular/D2D communications with underlay spectrum sharing. Based on the outage interference constraint of cellular user, the formulated non-convex optimization problem is converted into a convex one by using the mini-max probability machine and the auxiliary variable method. The analytical solutions of robust resource allocation problem are obtained by convex optimization theory. Simulation results show the effectiveness of the proposed algorithm.