In this paper, we focus on the design of a new scheme that combines the channel optimized vector quantization (COVQ) and the adaptive M-ary quadrature amplitude modulation (M-QAM). The adaptive modulation, when designed to track the channel variations, yields a higher throughput by adapting certain parameters of the receiver and the transmitter to the channel variation. After a time delay, the transmitter knows the receiver estimate of the Partial Channel State Information (PCSI) via a feedback path. The PCSI is a result of a comparison between the estimate of the average Channel Signal to Noise Ratio (CSNR) and λ-1 thresholds. The first step of the proposed scheme is, for each pair VQ codebook and QAM constellation, an iterative algorithm which is used to reach a local optimum solution minimizing the distortion, as the COVQ algorithm does. Next, a hard decision device in the receiver selects between λ cases, the pair QAM constellation and COVQ codebook that tracks the current conditions of the channel for each transmission of l source symbols. We also report, the impact of the time delay on the performance of this scheme in term of Peak Signal to Noise Ratio (PSNR). Simulation results, in the case of AWGN channels, show that the proposed adaptive optimized scheme outperforms the conventional system based on a fixed QAM constellation and the source encoder COVQ.
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