Power-distortion optimization for wireless image/video SoftCast by transform coefficients energy modeling with adaptive chunk division
Traditional communication systems usually suffer from the threshold effect when channel signal-to-noise ratio (CSNR) fluctuates unpredictably in wireless and mobile scenarios. The SoftCast scheme, however, provides graceful quality transition in wide CSNR range. In SoftCast, input image is decorrelated by a transform and modulated directly to a dense constellation for transmission, leaving out the conventional quantization, entropy coding and channel coding. A key point of SoftCast is that the transmission power needs to be allocated among the transform coefficients unequally, according to the energy of coefficients. Importantly, the energy diversity used to guide power allocation should be shared between the sender and the receiver for correct decoding. This paper addresses the power distortion optimization problem, introducing a new adaptive chunk division scheme to describe the energy diversity among coefficients. A concrete algorithm is developed to determine the chunk boundaries that achieve optimal transmission power usage. Experimental results show that the proposed scheme can improve the performance of the original SoftCast by 4~8dB using a smaller number of chunks.