论文标题
合作D2D交流的两次计算资源分配:一种匹配的游戏方法
Two-Timescale Resource Allocation for Cooperative D2D Communication: A Matching Game Approach
论文作者
论文摘要
在本文中,我们考虑了合作设备 - 托管(D2D)通信系统,其中D2D发射器(DTS)充当继电器,以协助致密的蜂窝网络用户(CUS)进行传输质量服务(QOS)改进。拟议的系统实现了双赢的情况,即提高CUS的频谱效率,在为D2D对提供频谱访问时无法满足其费率要求。与以前的工作不同,为了减少开销,我们设计了一种新颖的两次计算资源分配方案,其中CUS和D2D对之间的配对在很长的时间尺度和CU和D2D对的传输时间中确定,在短时间内确定。具体而言,为了表征每个潜在的CU-D2D对的长期收益,我们研究了根据瞬时通道状态信息(CSI)决定传输时间的最佳合作政策。我们证明,最佳策略是可以通过二进制搜索实现的阈值策略。由于CUS和D2D对是自私的,因此仅当他们同意相互合作时才配对。因此,为了研究CUS和D2D对的合作行为,我们根据每种可能配对的最佳合作政策所获得的长期收益来制定配对问题作为匹配游戏。此外,与D2D网络中大多数以前的匹配模型不同,我们允许CUS和D2D对之间的传输以提高性能。为了解决配对问题,提出了分布式算法,该算法会收敛到ε稳定匹配。我们表明,算法的最优性和计算复杂性之间存在权衡。我们还根据D2D对单侧偏差的鲁棒性分析了算法。最后,模拟结果验证了所提出的匹配算法的效率。
In this paper, we consider a cooperative device-todevice (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist the densified cellular network users (CUs) for transmission quality of service (QoS) improvement. The proposed system achieves a win-win situation, i.e. improving the spectrum efficiency of the CUs that cannot meet their rate requirement while providing spectrum access for D2D pairs. Unlike previous works, to reduce the overhead, we design a novel two-timescale resource allocation scheme, in which the pairing between CUs and D2D pairs is decided at a long timescale and transmission time for CU and D2D pair is determined at a short timescale. Specifically, to characterize the long-term payoff of each potential CU-D2D pair, we investigate the optimal cooperation policy to decide the transmission time based on the instantaneous channel state information (CSI). We prove that the optimal policy is a threshold policy which can be achieved via binary search. Since CUs and D2D pairs are self-interested, they are paired only when they agree to cooperate mutually. Therefore, to study the cooperation behaviors of CUs and D2D pairs, we formulate the pairing problem as a matching game, based on the long-term payoff achieved by the optimal cooperation policy of each possible pairing. Furthermore, unlike most previous matching models in D2D networks, we allow transfer between CUs and D2D pairs to improve the performance. To solve the pairing problem, a distributed algorithm is proposed, which converges to an ε-stable matching. We show that there is a tradeoff between the optimality and the computational complexity of the algorithm. We also analyze the algorithm in terms of the robustness to the unilateral deviation of D2D pairs. Finally, the simulation results verify the efficiency of the proposed matching algorithm.