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By reuse the resource of existing cellular users, D2D (Device-to-Device) communication underlaying cellular network can improve the spectrum utilization rate and reduce the power consumption of mobile terminals. However, it will also bring interference to the existing cellular network. How to effectively restrain the interference caused by resource reuse has become the most important factor that affects the performance of multi-cell networks. In order to ensure the quality of service of D2D users and cellular users, this paper studies the power control and resource allocation scheme for D2D communication underlaying cellular communications. Specifically, based on multi-cell cellular network architecture, fractional frequency reuse is introduced to achieve resource partitioning and resource reuse between cellular users and D2D users. Based on the principle of maximizing the throughput of the whole system, the optimization objective is then established. Combined with the fractional power control and with the introduction of interference limits, we use the Lagrangian dual decomposition to solve the optimization objectives, and propose a dynamic power control strategy. Simulation results show that compared with the existing algorithms, the proposed scheme improves the performance of the overall system.

With the ever increasing number of user terminals and fast-growing demands for local service, D2D (Device-to-Device) relay communication technology is becoming essential to the next generation mobile networks, where an efficient relay selection scheme not only improves the system performance but also conserves energy consumption. Aiming at encouraging relay node to voluntarily forward data and regarding with relay node selection issue, this paper proposes an improved social-aware relay selection strategy. In particular, we introduce the concept of social threshold which is based on the knowledge of social relationship among mobile users. Then by exploiting optimal stopping theory, we further propose an optimal relay selection strategy on the basis of social threshold method. Simulation results indicate that the proposed algorithm is effective in reducing the number of probing times of candidate relays and improving the throughput gain of the system, which strikes a balance between energy consumption and system utility.