Abstract: A joint channel selection and power control scheme is developed for video streaming in device-to-device (D2D) communications based cognitive radio networks. In particular, physical queue and virtual queue models by applying ‘M/G/1 queue ’and ‘M/G/1 queue with vacations’ theories are built up, respectively, to evaluate the delays experienced by various video traffics. Such delays play a vital role in calculating the packet loss rate for video streaming, which reflects the video distortion. Based on the distortion model, a video distortion minimization problem is formulated, subject to the rate constraint, maximum power constraint, primary users’ tolerant interference constraint, and secondary users’ minimum data rate requirement constraint. The optimization problem turns out to be a mixed integer nonlinear programming (MINLP), which is generally nondeterministic in polynomial time. A Lagrange dual method is thus employed to reformulate the video distortion minimization problem, based on which the sub-gradient algorithm is used to determine a relaxed solution. Thereafter, applying the iterative user removal yields the optimal joint channel selection and power control solution to the original MINLP problem. Extensive simulations validate our proposed scheme and demonstrate that it significantly increases the peak signal-to-noise ratio (PSNR) compared with the existing schemes.

Key words: channel selection, power control, cognitive radio networks, D2D communications, video streaming, convex optimization.