Joint Energy Optimization of Video Encoding and Transmission
2018
Disposable wireless video sensors have many potential applications but are subject to stringent energy constraints. We studied the minimization of end-to-end distortion under an total energy constraint, by means of optimizing FEC code rate, number of source bits, and energy allocation between video encoding and wireless transmission. A two-step approach is employed. First, the FEC rate is optimized by exhaustive search. Then a binary-search-based algorithm is proposed to optimize the energy allocation and number of source bits. Experiments show that the algorithm achieves a PSNR gain up to 1dB over some reasonable baselines. A simpler suboptimal algorithm is also tested and exhibits similar performance.
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