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：在底层D2D通信中设计资源分配算法时，需要将D2D发射机与基站间的信道状态信息(CSI)以及D2D接收机的CSI(DCSI-R)传输至基站。然而，这会增加控制开销和功率浪费，且随着快衰落信道的出现，由于每个时隙都需要传输CSI，此类开销将进一步增大。现有研究大多假设基站已知DCSI-R，但少数研究考虑其不可知性并求解纳什均衡，然而该均衡可能并非帕累托最优。针对这一问题，我们基于博弈论框架提出了一种次优的半分布式D2D资源分配算法。假设信道仅存在路径损耗，我们的目标是在满足D2D用户效用需求及蜂窝用户(CU)信干噪比(SINR)要求的前提下最大化D2D用户的社会效用，从而获得帕累托最优解。进一步地，在考虑阴影效应、快衰落及CU移动性的场景下，我们对首个算法进行改进并提出第二个算法。仿真结果表明，首个算法在实际场景中表现不佳，而第二个算法对信道随机性和CU移动性具有极强的鲁棒性。