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Second order moment estimation for multilevel quantized tailed shifts sequences optimising BER for asynchronous DS-CDMA systems

机译:用于异步DS-CDMA系统的BER优化的多级量化尾移序列的二阶矩估计

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Chaotic sequences offer a good alternative for spreading in DS-CDMA (direct sequence-code division multiple access) systems. These sequences are generated by nonlinear feedback dynamical systems and have interesting features like a very sensitive dependency on the initial state and noiselike correlation properties. This paper considers the case of a very well known family of PWAM (piece-wise affine Markov) maps, namely (n,t)-tailed shifts maps, and their quantized versions. In DS-CDMA systems the MAI (multiple access interference) is depending on the correlation properties of the spreading sequences. Hence, here we present the estimation method for the second order statistical moment of quantized (n,t)-tailed shifts sequences and its optimization for reducing MAI.
机译:混沌序列提供了在DS-CDMA(直接序列码分多次访问)系统中传播的良好替代方案。这些序列由非线性反馈动态系统生成,并且具有与初始状态和噪声相关性能的非常敏感的依赖性等有趣的特征。本文考虑了众所周知的PWAM系列PWAM系列映射的情况,即(n,t) - 换档映射及其量化版本。在DS-CDMA系统中,MAI(多访问干扰)取决于扩展序列的相关性。因此,这里我们介绍了量化的二阶统计矩的估计方法(N,T) - 换档序列及其对还原MAI的优化。

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