Social Network-Based Research On Terminal Direct Communication Network

With the continuously emergency of mobile multimedia services and the popularity of social network-based services,the unprecedented growth of mobile date traffic has brought a heavy burden on the traditional cellular networks.The contradiction between the growing service demands of users and the limited network bandwidth has become increasingly prominent.The existing wireless network architecture needs to be upgraded.Device-to-device(D2D)communication,as a promising solution to overcome wireless spectrum crisis,allows mobile devices to transmit data signals over local peer-to-peer links instead of through a traditional infrastructure,i.e.,the base station(BS)of cellular network.By reusing cellular spectrum resources under the control of the BS,D2D communication can dramatically increase the spectrum efficiency and network capacity.Moreover,because of the proximity effect of direct connections,D2D is expected to enhance the data transmission rates and promote new applications.Based on user activities in social network,D2D communication can enable fast content delivery,offolad cellular data traffic and increase the spectrum efficiency.In this paper,we study the content delivery problem related to optimization of peer discovery and resource allocation by combining both the social and physical layer information in D2D underlay networks.The social relationship,which is modeled as the probability of selecting similar contents and estimated by using the Bayesian nonparametric models,is used as a weight to characterize the impact of social features on D2D pair formation and content sharing.Next,we propose a 3-D iterative matching algorithm to maximize the sum rate of D2D pairs weighted by the intensity of social relationships while guaranteeing the quality of service requirements of both cellular and D2D links simultaneously.Finally,we prove that the proposed algorithm converges to a stable matching and is weak Pareto optimal.Simulation results show that the algorithm is able to achieve more than 90%of the optimal performance with a computation complexity 1000 times lower than the exhaustive matching algorithm.It is also demonstrated that the satisfaction performance of D2D receivers can be increased significantly by incorporating social relationships into the resource allocation design.