Jointly optimal rate control and relay selection for cooperative wireless video streaming

  • Authors:
  • Zhangyu Guan;Tommaso Melodia;Dongfeng Yuan

  • Affiliations:
  • School of Information Science and Engineering, Shandong University, Jinan, China and Department of Electrical Engineering, State University of New York at Buffalo, Buffalo, NY;Department of Electrical Engineering, State University of New York at Buffalo, Buffalo, NY;School of Information Science and Engineering, Shandong University, Jinan, China

  • Venue:
  • IEEE/ACM Transactions on Networking (TON)
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Physical-layer cooperation allows leveraging the spatial diversity of wireless channels without requiring multiple antennas on a single device. However, most research in this field focuses on optimizing physical-layer metrics, with little consideration for network-wide and application-specific performance measures. This paper studies cross-layer design techniques for video streaming over cooperative networks. The problem of joint rate control, relay selection, and power allocation is formulated as a mixed-integer nonlinear problem, with the objective of maximizing the sum peak signal-to-noise ratio (PSNR) of a set of concurrent video sessions. A global optimization algorithm based on the branch and bound framework and on convex relaxation of nonconvex constraints is then proposed to solve the problem. The proposed algorithm can provide a theoretical upper bound on the achievable video quality and is shown to provably converge to the optimal solution. In addition, it is shown that cooperative relaying allows nodes to save energy without leading to a perceivable decrease in video quality. Based on this observation, an uncoordinated, distributed, and localized low-complexity algorithm is designed, for which we derive conditions for convergence to a Nash equlibrium (NE) of relay selection. The distributed algorithm is also shown to achieve performance comparable in practice to the optimal solution.