Evolution Handoff Strategy for Real-Time Video Transmission over Practical Cognitive Radio Networks

The transmission delay of real-time video packet mainly depends on the sensing time delay (short-term factor) and the entire frame transmission delay (long-term factor). Therefore, the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization. In this paper, we focus on the issue of combining these two optimization models, and propose a novel Evolution Spectrum Handoff (ESH) strategy to minimize the expected transmission delay of real-time video packet. In the micro-optimized model, considering the tradeoff between Primary User's (PU's) allowable collision percentage of each channel and transmission delay of video packet, we propose a mixed integer non-linear programming scheme. The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time. In the macro-optimized model, using the optimal stopping time as reward function within the partially observable Markov decision process framework, the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission. Meanwhile, the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions, i.e., secondary user's mobility, PU's random access, imperfect sensing information, etc.. Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.