Total system energy minimization for wireless image transmission

In this paper, we focus on the total-system-energy minimization of a wirele ss image transmission system including both digital and analog components. Traditionally, digital power consumption has been ignored in system design, since transmit power has been the most significant component. However, as we move to an era of pico-cell environments and as more complex signal proc essing algorithms are being used at higher data rates, the digital power co nsumption of these systems becomes an issue. We present an energy-optimized image transmission system for indoor wireless applications which exploits the variabilities in the image data and the wireless multipath channel by e mploying dynamic algorithm transformations and joint source-channel coding. The variability in the image data is characterized by the rate-distortion curve, and the variability in the channel characteristics is characterized by the path-loss and impulse response of the channel. The system hardware c onfiguration space is characterized by the error-correction capability of t he channel encoder/decoder, number of powered-up fingers in the RAKE receiv er, and transmit power of the power amplifier. An optimization algorithm is utilized to obtain energy-optimal configurations subject to end-to-end per formance constraints. The proposed design is tested over QCIF images, IMT-2 000 channels and 0.18 mum, 2.5 V CMOS technology parameters. Simulation res ults over various images, various distances, two different channels, and tw o different rates show that the average energy savings in utilizing a total -system-energy minimization over a fixed system (designed for the worst ima ge, the worst channel and the maximum distance) are 53.6% and 67.3%, respec tively, for short-range (under 20 m) and long-range (over 20 m) systems.