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Mobile devices performing video coding and streaming over wireless and pervasive communication networks are limited in energy supply. To prolong the operational lifetime of these devices, an embedded video encoding system should be able to adjust its computational complexity and energy consumption as demanded by the situation and its environment. To analyze, control, and optimize the rate-distortion (R-D) behavior of the wireless video communication system under the energy constraint, we develop a power-rate-distortion (P-R-D) analysis framework, which extends the traditional R-D analysis by including another dimension, the power consumption. Specifically, in this paper, we analyze the encoding mechanism of typical video coding systems, and develop a parametric video encoding architecture which is fully scalable in computational complexity. Using dynamic voltage scaling (DVS), an energy consumption management technology recently developed in CMOS circuits design, the complexity scalability can be translated into the energy consumption scalability of the video encoder. We investigate the R-D behavior of the complexity control parameters and establish an analytic P-R-D model. Both theoretically and experimentally, we show that, using this P-R-D model, the video coding system is able to automatically adjust its complexity control parameters to match the available energy supply of the mobile device while maximizing the picture quality. The P-R-D model provides a theoretical guideline for system design and performance optimization in mobile video communication under energy constraints.