Resource Allocation for Video Streaming in Heterogeneous Cognitive Vehicular Networks

In future fifth-generation (5G) communication systems, driven by the evolution of today's most demanding applications, video streaming over vehicle networks will play an increasingly significant role in our daily lives. In this paper, based on a heterogeneous architecture consisting of both cellular base stations (BSs) of wide coverage and cognitive-radioenabled roadside infrastructures, a semi-Markov decision process (SMDP)-based resource-allocation scheme is proposed to facilitate video streaming application in terms of peak signal-to-noise ratio (PSNR) and smooth playback. In addition to improving video quality of vehicle users, quality of service (QoS) provisioning for background users that can originally exist in the cellular network is also considered in the proposed scheme. Specifically, based on the states of the background users, vehicle users, and the availability of the cognitive bands, the optimal resource allocation, aiming at maximizing the video streaming quality while guaranteeing the call-level performance of the background users, is achieved by addressing two interrelated joint call admission control (CAC) and channel allocation problems for cellular and roadside infrastructure networks, respectively. Simulation results show that the proposed scheme can well protect background users when coexisting with bandwidth-hungry vehicle video users and is effective in not only improving video streaming quality for vehicle users but boosting bandwidth utilization of the whole network as well.