Research On D2D Communication Mode Selection And Resource Allocation In Cellular Networks

With the development of information communication technology,mobile devices have become a necessity of modern life,which has triggered explosive growth in data traffic.Traditional cellular networks can no longer meet the needs of new generation of communication technology.In response to the increasing number of spectrum resources in the communication network.In the communication industry believe that in the fifth-generation mobile communication system,it can alleviate this phenomenon through the introduction of the device-To-Device Communications(D2D)communication technology,meet the diversified service needs of users,and improve the overall performance.Not only that,D2 D communication technology has also played a crucial role in many applications such as social networks,Internet of Vehicle,D2 D relay,and emergency communication.Including but not limited to extremely high spectrum efficiency,good user experience,and more flexible transmission methods.D2 D saves wireless broadband resources when sharing cellular user resources,but it also generates a mass of interference.In order to avoid interference effectively,the reasonable allocation of communication resources has become the key to improve the performance of D2 D communication systems in cellular networks.At the same time,because of the broadcastability of wireless channels and the openness of D2 D transmission,D2 D users are easily threatened by security,and data information is stolen or maliciously tampered with.The physical layer security technology prevents eavesdropping without encryption.It has become the main advantage of 5G networks.Therefore,it is important to ensure that the adaptation of the new generation of communication technology and the cellular network of the new generation of communication technology and the cellular network is important.The research theme of this article is mainly divided into two aspects: on the one hand,the problem of interference generated by D2 D reuse cell network is reduced through a joint plan,and on the other hand,the security problem in the D2 D communication process is improved through power distribution.The main tasks of this article are as follows:(1)In the case of ensuring the quality of D2 D communication,in order to reduce the impact of unreliable D2 D links,this article proposes a solution for the combination of D2 D communication mode selection,channel distribution and power control.In the scheme of joint three algorithms,in order to maximize the system throughput and improve the network performance.Firstly,SINR and channel capacity are used as the criteria for mode selection,and the optimal selection of modes is achieved based on the results of the interference value caused by D2 D users to the base station compared with the threshold value.In addition,a scheme based on the combination of Hopcroft-karp algorithm and mode selection algorithm is proposed to reasonably perform the optimal allocation of channel resources.Finally,the improved Gray Wolf algorithm is used to achieve power optimization.The results of the simulation experiment show that the plan of the three algorithms proposed in this article can effectively improve the total throughput of the system.(2)In the interference hybrid network of eavesdropping users,communication security is the prerequisite for the success of D2 D services.In order to reduce the risk of eavesdropping in users in wireless communication channels and improve the quality of user communication.Optimizing the security energy efficiency and minimum security throughput of eavesdropping user transmission links.In the case of limited computing resources,improvement efficiency is improved,and this article introduces a new meta enlightenment algorithm with low computing complexity-Beluga Whale Optimization(BWO)to solve the above information security transmission problem.As a group algorithm,BWO is similar to the problem of security transmission.The probability of balance coefficient and whale falling is adaptive,so the ability to explore and develop algorithm can be adjusted according to the current iteration and the changes of the optimal solution.The results of the simulation experiments show that the algorithm mentioned in this article has a lower complexity in the optimization process.