一种基于时变信道的自适应矢量量化方法

Time-varying Channels Based Adaptive Vector Quantizer

提出了一种信道自适应加权矢量量化(CAWVQ)算法。采用对处于两种不同状态的典型码书进行加权的算法,获得与信道状态相匹配的码书,并且只使用较少的存储空间。将该算法应用于噪声信道中,能够有效的提高矢量量化器的性能。仿真实验表明该算法能够比其他算法得到更高的信噪比。

In this paper, We propose a new scheme --channel adaptation weighted of vector quantization. （ CAWVQ）. The algorithm employs two representative codebooks to generate appropriate codebcok for current channel state by multiplying them with different weighted factors. The proposed scheme fits the practical state of the communicational channels well. And it just needs less memory than conventional COVQ. Applying the scheme to the noisy channel, it can improve the performance of vector quantizer. Simulation demonstrates the scheme can get more gains than other algorithms.