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Iterative sparse channel estimation and demodulation for blind equalisation

机译:用于盲均衡的迭代稀疏信道估计和解调

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The authors formulate a blind equalisation problem minimising the residual that is difference between the received signal and the predicted signal. Since both channel impulse responses and transmitted symbols are unknown, the authors regard the problem as a kind of dictionary learning problem. The authors divide the problem into two sub-problems and iteratively find the channel impulse response and the demodulated symbols. Since the wireless channels with a large bandwidth tend to have a sparse multipath structure, the authors apply the compressive sensing technique to the channel estimation sub-problem. Numerical results show that the proposed algorithm achieves the Genie-aided lower-bound performance.
机译:作者提出了一种盲均衡问题,该问题使接收信号和预测信号之间的差值残差最小。由于信道冲激响应和传输符号都是未知的,因此作者将此问题视为一种字典学习问题。作者将问题分为两个子问题,并迭代找到信道脉冲响应和解调符号。由于具有大带宽的无线信道倾向于具有稀疏的多径结构,因此作者将压缩感测技术应用于信道估计子问题。数值结果表明,该算法达到了精灵辅助下界性能。

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