Channel allocation for smooth video delivery over cognitive radio networks

To address the impact of the network dynamics on video streaming, the playout buffer is typically deployed at the receiver. With different buffer storage, users thus have different tolerance to the network dynamics. In this paper, we exploit this feature for channel allocation in cognitive radio (CR) networks. We first model the channel availability as an on-off process which is stochastically known. Based on the bandwidth capacity and the specific buffer storage of users, we then intelligently allocate the channels to maximize the overall network throughput while providing users with the smooth video playback, which is formulated as an optimization framework. Given the channel conditions and the video packet storage in the playout buffer, we propose a centralized scheme for provisioning the superior video service to users. Simulation results confirm that by exploiting the playout buffer of users, the proposed channel allocation scheme is robust against intense network dynamics and provides users with the elongated smooth video playback.