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Hybrid methods for blind adaptive equalization: new results and comparisons

机译:盲自适应均衡的混合方法:新结果和比较

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This paper proposes two new hybrid blind algorithms based on a new radius-adjusted approach for QAM signal constellations and presents a comprehensive survey of hybrid methods for blind adaptive equalization. The proposed hybrid blind algorithms define static circular regions around symbol points that correspond to a specific weighting factor and stepsize, which optimize the equalizer tap update based on the adaptation phase. Hybrid methods are discussed for the constant modulus algorithm (CMA), improved transfer to the decision-directed (DD) algorithm, and dual-mode hybrid algorithms. Comparisons are made between the proposed algorithms and related hybrid methods, and it is shown that the new algorithms lead to enhanced performance with minimal added complexity.
机译:本文提出了基于新的QAM信号星座的新的半径调整方法的混合盲算法,并提出了对盲自适应均衡的综合调查。所提出的混合盲算法定义围绕符号点的静态圆形区域,该符号点对应于特定加权因子和步骤化,其优化基于自适应阶段的均衡器抽头更新。讨论恒定模量算法(CMA),改善转移到决策(DD)算法以及双模混合算法的杂交方法。在所提出的算法和相关的混合方法之间进行比较,并显示新算法导致增强的性能,具有最小的增加的复杂性。

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