Performance Analysis of Network Assisted Neighbor Discovery Algorithms

Most of the existing applications designed for users in proximity are based on cellular network communications, involving either registration at an application server and/or obtaining location information from a positioning system. However, they are either resource consuming or battery draining. In order to deal with these problems, the concept of direct Device-to-Device (D2D) communication has been proposed as a solution. It can not only increase the spectrum efficiency, but also improve the coverage of cellular network. The discovery of the devices is the precondition of the communication between them. Previous studies indicate that D2D discovery without cellular network assistance is feasible but time, resource and energy consuming. Therefore, in this thesis work we develop algorithms that take advantage of network assistance to improve the performance of the neighbor discovery algorithms in terms of energy efficiency, resource utilization, discovery time and discovery rate. We distinguish five levels of network involvement from allowing for synchronization to explicitly providing information on the used peer discovery resources. The analysis in this work indicates that the setting of transmission probability for devices plays a critical role in the process of D2D discovery. Furthermore, stopping the devices which have already been discovered by enough candidates can improve the performance, in terms of reducing the interference to other devices and saving energy consumption. It is also shown in the simulation results that, to reach a given quantity of D2D communication candidates for all the devices in the area of study, the discovery time as well as the energy consumption can be reduced up to 87-91% from the lowest level of the network assistance to the highest level.