To devise D2D resource allocation algorithms in underlay D2D communications the channel state information (CSI) between the D2D transmitters and the BS and the D2D receiver CSI (DCSI-R) needs to be transmitted to the BS. However, this increases the control overhead and power wastage which increases with a fast fading channel since the CSI needs to be transmitted in every time slot. Most of the existing works assume DCSI-R availability at the BS. However, a few works assume its unavailability and determine the Nash equilibrium which may not be Pareto optimal. We address this problem and within a game theoretic framework propose a suboptimal semi-distributed D2D resource allocation algorithm. We consider the channel to exhibit path loss. Our goal is to maximize the social utility of the D2D users while meeting their utility requirements and the signal-to-interference-plus-noise ratio (SINR) requirements of the CUs to reach a Pareto optimal solution. Next, we consider shadowing, fast fading and mobility of CUs and propose another algorithm which is a modification of our first proposed algorithm. Through simulations we observe that the first algorithm does not perform well practically but the second algorithm is very robust to channel randomness and CU mobility.

翻译：在设计底层D2D通信的资源分配算法时，需将D2D发射机与基站间的信道状态信息以及D2D接收机信道状态信息传输至基站。然而这会导致控制开销与功率浪费——在快衰落信道中，由于需在每个时隙传输CSI，此类开销随信道变化速率递增。现有研究大多假设基站可获得D2D接收机CSI，但部分研究考虑其不可获取性并确定纳什均衡，然而该均衡解可能非帕累托最优。本文针对此问题，在博弈论框架下提出一种次优的半分布式D2D资源分配算法。假设信道具有路径损耗特性，目标是在满足D2D用户效用需求与蜂窝用户信干噪比要求的前提下最大化D2D用户的社会效用，以获得帕累托最优解。进一步考虑阴影效应、快衰落及蜂窝用户移动性，提出对初始算法的改进方案。仿真结果表明，初始算法在实际场景中性能不佳，而改进算法对信道随机性与CU移动性具有强鲁棒性。