TY - JOUR
T1 - A framework of cross-layer design for multiple video streams in wireless mesh networks
AU - Cheng, Peng
AU - Zhang, Zhaoyang
AU - Chen, Hsiao Hwa
AU - Qiu, Peiliang
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (Nos. 60572115, 60472079), and Taiwan National Science Council research Grants NSC96-2221-E-110-035 and NSC96-2221-E-110-050.
PY - 2008/5/25
Y1 - 2008/5/25
N2 - In this paper, a novel cross-layer design framework for multiple realtime video traffics in CDMA wireless mesh networks is proposed. First, the performances of application, physical, MAC, and network layers are modeled by some classical models under reasonable assumptions. Then, we present a framework in which source coding, power control, ARQ control, and delay partitioning functionalities at different layers can be jointly optimized. Our objective is to maximize the video quality under strict end-to-end delay constraints through adjusting source coding rate, end-to-end delay distribution, and each node's transmit power. This optimization problem is proved to be a nonlinear but log-convex one. Finally, we propose a centralized solution based on the classical convex programming method, as well as a partially distributed solution based on the Lagrangian dual decomposition technique. The both solutions are proved to converge to the global optimum of the above problem.
AB - In this paper, a novel cross-layer design framework for multiple realtime video traffics in CDMA wireless mesh networks is proposed. First, the performances of application, physical, MAC, and network layers are modeled by some classical models under reasonable assumptions. Then, we present a framework in which source coding, power control, ARQ control, and delay partitioning functionalities at different layers can be jointly optimized. Our objective is to maximize the video quality under strict end-to-end delay constraints through adjusting source coding rate, end-to-end delay distribution, and each node's transmit power. This optimization problem is proved to be a nonlinear but log-convex one. Finally, we propose a centralized solution based on the classical convex programming method, as well as a partially distributed solution based on the Lagrangian dual decomposition technique. The both solutions are proved to converge to the global optimum of the above problem.
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U2 - 10.1016/j.comcom.2008.01.063
DO - 10.1016/j.comcom.2008.01.063
M3 - Article
AN - SCOPUS:42749092105
SN - 0140-3664
VL - 31
SP - 1529
EP - 1539
JO - Computer Communications
JF - Computer Communications
IS - 8
ER -