Rate And Energy Efficiency Based Relay Selection Algorithm In Multi-hop D2D Network

As one of the key technologies of 5G communication,D2 D communication is an important way to increase the data rate of mobile communications and expand the coverage.Multi-hop D2 D communication can effectively extend the communication distance and increase the data rate.The multi-hop D2 D communication may have different end-to-end data rate due to different relay selections.So,relay selection algorithms in multi-hop D2 D communication is a hot topic.This paper focuses on the relay selection algorithm in multi-hop D2 D communication scenario.First,the background and and significance of relay selection in multi-hop D2 D communication systems were briefly introduced in this paper.Then,this paper describes the research status of D2 D related technologies,and then introduces some existing relay selection algorithms in D2 D communication.After analyzing the characteristics of the three-hop communication scenario,a rate based relay selection algorithm is proposed in this paper.The theoretical analysis model of the algorithm is established and the capacity of the algorithm is analyzed under a reasonable assumption.The comparison between theoretical capacity and the capacity of the traversal algorithm proves the rationality of the theoretical analysis.Then,after some theoretical analysis,it is proved that the proposed algorithm can achieve the optimal end-to-end transmission rate achieved by the traversal algorithm in the current scenario,and the simulation results also prove it.Through simulation,it is showed that the proposed algorithm achieves higher end-to-end data rate with lower algorithm complexity than the simple clustering method.This paper also introduces the system energy efficiency evaluation into the aforesaid algorithm,and proposes an optimization algorithm to improve the system energy efficiency without affecting the end-to-end data rate of the system.This algorithm can be applied not only to the rate based relay selection algorithm proposed in this paper,but also to the simple clustering method.Simulation shows that the two algorithms can achieve significant improvements in energy efficiency after applying the energy efficiency optimization algorithm.