Adaptive-rate image compression for wireless digital data transmission systems

Abstract

The vast amount of data needed to represent digital imagery motivates the use of advanced compression systems to reduce the bandwidth required to transmit high-resolution source imagery. We propose two methods to provide optimal image quality at a fixed image delivery rate. The first method, channel-controlled variable-rate (CCVR) image coding, operates within the constraint that the modulation symbol rate is fixed. The second method, adaptive-rate coding-modulation (ARCM), utilizes adaptive modulation, and is less complex, while providing increased performance. Both methods use a variable-compression-ratio image coder and variable-rate channel coding. The objective is to maximize the quality of the reconstructed image at the receiver when transmitted through Rayleigh fading and additive white Gaussian noise (AWGN). The reconstructed image quality is maximized through adaptive source-channel coding in the context of a bit rate tradeoff between the source and channel coders (CCVR), and then, in addition, adaptive-rate modulation (ARCM). Both methods require knowledge of the channel state which is used by the receiver to inform the transmitter, via a feedback channel, of the optimal strategy for image compression, channel coding, and modulation format. The resulting system using ARCM achieves up to a 17 dB improvement over the peak signal-to-noise ratio (PSNR) performance of a system using a fixed-compression-ratio image coder and fixed-rate channel coding.