中国邮电高校学报(英文) ›› 2018, Vol. 25 ›› Issue (1): 1-14.doi: 10.19682/j.cnki.1005-8885.2018.0001

• Networks •    下一篇

Joint channel selection and power control for video streaming over D2D communications based cognitive radio networks

高雅,张海林,卢小峰   

  1. 西安电子科技大学
  • 收稿日期:2017-06-21 修回日期:2018-01-17 出版日期:2018-02-28 发布日期:2018-02-28
  • 通讯作者: 高雅 E-mail:gaoya@stu.xidian.edu.cn
  • 基金资助:
    国家自然科学基金;国家自然科学基金;国家自然科学基金;“高等学校学科创新引智计划”(简称“111计划”);重点高校基础研究项目;陕西省自然科学基金;河南省科技攻关重点项目

Joint channel selection and power control for video streaming over D2D communications based cognitive radio networks

  • Received:2017-06-21 Revised:2018-01-17 Online:2018-02-28 Published:2018-02-28
  • Contact: Ya Gao E-mail:gaoya@stu.xidian.edu.cn
  • Supported by:
    Natural Science Foundation of China;Natural Science Foundation of China;Natural Science Foundation of China; Natural Science Foundation of Shaanxi Province

摘要: 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.

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

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.