Resource Allocation Technology For D2D Discovery In LTE Networks

Device-to-Device is the technology which permits devices can direct communicate with each other.For the number of smart devices grow much faster than ever before,it will cause the problem of the lack of frequency resource in the existed LTE communication system.Therefore,D2D tech-nology is one potential technology for resolving this problem because of al-lowing smart devices communicate with each other directly without eNode B relaying.D2D technology also has a better prospect in IoV,IoT,and app based proximity services and so on.In addition,IMT2020 states that D2D technology plays an important role in the next generation communication sys-tem(5G).The technology is divided into two phases:D2D discovery phase and D2D communication phase.There are three technologies in each phase:resource allocation;interference cancellation and access method.This paper focuses on resource allocation in D2D discovery phase.There are two resource allocation algorithms in D2D discovery phase:random selection algorithm and greedy reselection algorithm.At first,we analyse these two algorithms with Poisson Point Process.We show the ex-isting resource allocation algorithms improve the discovery ratio through de-creasing the ratio between the number of device and resource block,but it will result in long the discovery delay.To solve this problem,we propose the grouping method based on the properties of greedy reselection algorithm.The degree of spatial multiplexing would be improved and the free resource blocks would be utilized completely by grouping method so that the discov-ery number increases in each period.And then,we prove that the grouping method in greedy reselection algorithm have better performance.When the resource of D2D communication and LTE system is orthog-onal,the main interference from D2D communication to cell users is In-band emission interference(IBEI).We discuss the two basement algorithm for limiting the in-band emission interference:grouping algorithm,open loop power control(OLPC)algorithm.There are some drawbacks in the two algorithms.For grouping based algorithm,the eNode B should have the knowledge of D2D devices such as the number of D2D device,distributed form and so on.However,in distributed algorithm,the eNB have no idea about the information above.So eNB can t group appropriately,not proper grouping size will cause intense interference and discovery efficiency.For OLPC algorithm,DUEs must decrease their transmission power for limit-ing in-band emission interference.Those factors may reduce the discovery efficiency significantly.Thus it is a critical issue to increase the discov-ery efficiency and reduce the IBEI simultaneously.We propose two inno-vative self-sorted greedy reselection algorithms:grouping in time domain self-sorted algorithm and grouping in frequency domain self-sorted algo-rithm.For grouping in time domain self-sorted algorithm,the devices who cause the considerable IBEI will accumulate in minimum sub-frames auto-matically so that the eNB needn't make a decision to grouping method.It is absolutely distributed algorithm.For grouping in frequency domain self-sorted algorithm,we increase the distance to PUCCH in frequency domain from the devices which cause the considerable IBEI.Coordinate with OLPC,it will permit the maximum transmission power for limiting the IBEI.And then,we prove that our proposed two self-sorted algorithms perform better than existing algorithms.