Social-aware Peer Discovery And Resource Allocation For Device-to-Device Communication

Device-to-Device(D2D)communication refers to the technology that neighboring terminals communicate through a direct link and has the advantages of improving spectrum utilization,reducing transmission delay,and improving system capacity,and is considered as an important component of a next-generation cellular network.The first step in D2D communication is peer discovery,where the device detects other devices by sending probe beacons.In general,the higher the detection rate,the greater the probability of finding the device.But sending probe beacons frequently also consumes time and energy,limiting the useful life of mobile devices.Therefore,designing the proper beacon detection rate is critical and we find it difficult to strike a balance between user pairing performance and energy consumption,making peer discovery a challenging issue in D2D communications.On the other hand,since the D2D user multiplexes the spectrum resources of the cellular user during communication,the same frequency interference occurs between the D2D users and cellular users and the communication quality will be seriously degraded if the interference is severe.Therefore,it is necessary to reduce user interference and improve system performance through a reasonable and effective resource allocation scheme.In order to solve the above problems,this thesis first proposes a social-aware user pairing scheme for D2D communication.In this scheme,D2D users in the network are first divided into user groups according to social groups and social centrality,and then,the users determines the best beacon detection rate with constant intervals for each group.Compared with other schemes,this scheme divides the users according to the user's centricity so as to allocate the beacon detection rate.The simulation shows that this scheme can effectively reduce the energy loss and improve the matching success rate.Secondly,this thesis presents a time-varying optimization scheme of social network D2D communication resource allocation.The user's intimacy is calculated by calculating the user's call information to quantify the strength of the social relationship.Taking into account the time-varying nature of social relationships,Autoregressive Integrated Moving Average(ARIMA)models map call records to time series to predict users' social relationships.Next,we use the potential game to solve the problem of maximizing the utility of social groups with D2D communication resources allocation and prove that the game has a pure Nash equilibrium.Finally,we propose a distributed perceptual resource allocation algorithm,and achieve the convergence and stability of the algorithm.The simulation results show that under the condition of fairness,the overall utility of the proposed scheme is more than 30%higher than that of the alliance game scheme,and over 50%more than the random choice scheme.