Rate and Power Allocation for Joint Coding and Transmission in Wireless Video Chat Applications
Wireless video chat is a power-consuming and bitrate-intensive application. Unlike video streaming, which is one-way traffic, video chat features distributed two-way traffic relayed via base stations, where resource allocation of a client affects the video quality seen by its communicating partner....
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/81928 http://hdl.handle.net/10220/41071 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Wireless video chat is a power-consuming and bitrate-intensive application. Unlike video streaming, which is one-way traffic, video chat features distributed two-way traffic relayed via base stations, where resource allocation of a client affects the video quality seen by its communicating partner. In this paper, we study the mechanism design of this application via dynamic pricing, and seek efficiency and fairness of resource utilization. Specifically, we assume that the base station relays video bitstreams and charges a service price on the clients based on the transmission power consumption. Based on the price and a given power budget, the clients allocate bitrate and power for video coding and transmission such that the service price and the distortion seen by their partners are minimized. We study such network dynamics in Stackelberg game-theoretic framework. To solve the problem, we propose a complexity-scalable video encoding method and a power-rate-distortion (PRD) model for video chat. The model is more accurate in describing the PRD characteristics, yet of lower complexity in online updates of its coefficients. Based on the PRD model, we derive the distributed rate and power allocations for the clients. We show that a simple pricing update in the base stations is sufficient for optimal pricing. The proposed algorithms are optimal and converge to the Stackelberg equilibrium. Existing SNR- and power-based pricing schemes could not ensure fairness and efficiency simultaneously. We propose a hybrid pricing scheme that balances these conflicting criteria. Extensive simulations demonstrate superior performance of the proposed methods and solutions. |
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