Service time prediction based dynamic resource allocation for device-to-device communication underlaying cellular networks

Abstract

Resource allocation is a critical issue in device-to-device (D2D) communication underlying cellular networks. Existing work only considers static resource allocation, which cannot well address the dynamic resource allocation problem in a real cellular network. This paper studies dynamic resource allocation for D2D communication and proposes a service time prediction based dynamic resource allocation mechanism for a cellular network system. The proposed allocation mechanism considers different service types, and introduces the concept of as a metric to reflect the performance of a user or the system, and takes into account service time prediction in spectral resource allocation. Specifically, it enables the base station to predict the service time of a new user and the remaining service time of existing users in the system, and take into account the predicted service time and remaining service time in calculating the utility gain caused by a new user. Based on the estimated utility gain, the base station will select the physical resource block (PRB) with the largest utility gain every time it allocates a PRB to the new user. Simulation results show that the proposed dynamic allocation mechanism can significantly improve the system performance in terms of the system utility and the number of users successfully admitted to the system.