Social-Aware Resource Allocation Based on Cluster Formation and Matching Theory in D2D Underlaying Cellular Networks

With the appearance of wireless spectrum crisis in traditional cellular network, device-to-device (D2D) communication has been regarded as a promising solution to ease heavy traffic burden by enabling precise content delivery among mobile users. However, due to the channel sharing, the interference between D2D and cellular users can affect the transmission rate and narrow the throughput in the network. In this paper, we firstly present a weighted interference minimization cluster formation model involving both social attribute and physical closeness. The weighted-interference, which is evaluated under the susceptible-infected(SI) model, is utilized to gather user in social and physical proximity. Then, we address the cluster formation problem via spectrum clustering with iterative operation. Finally, we propose the stable matching theory algorithm in order to maximize rate oriented to accomplish the one-to-one resource allocation. Numerical results show that our proposed scheme acquires quite well clustering effect and increases the accumulative transmission rate compared with the other two advanced schemes.