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Wireless Rake-Receiver Using Adaptive Filter with a Family of Partial Update Algorithms in Noise Cancellation Applications

机译:无线耙式接收器使用自适应过滤器,具有噪声消除应用中的一系列部分更新算法的系列

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For high data rate propagation in wireless ultra-wideband (UWB) communication systems, the inter- symbol interference (ISI), multiple-access interference (MAI), and multiple-users interference (MUI) are influencing the performance of the wireless systems. In this paper, the rake-receiver was presented with the spread signal by direct sequence spread spectrum (DS-SS) technique. The adaptive rake-receiver structure was shown with adjusting the receiver tap weights using least mean squares (LMS), normalized least mean squares (NLMS), and affine projection algorithms (APA) to support the weak signals by noise cancellation and mitigate the interferences. To minimize the data convergence speed and to reduce the computational complexity by the previous algorithms, a well-known approach of partial-updates (PU) adaptive filters were employed with algorithms, such as sequential- partial, periodic-partial, M-max-partial, and selective-partial updates (SPU) in the proposed system. The simulation results of bit error rate (BER) versus signal-to-noise ratio (SNR) are illustrated to show the performance of partial- update algorithms that have nearly comparable performance with the full update adaptive filters. Furthermore, the SPU-partial has closed performance to the full-NLMS and full-APA while the M-max-partial has closed performance to the full-LMS updates algorithms.
机译:对于无线超宽带(UWB)通信系统中的高数据速率传播,符号间干扰(ISI),多访问干扰(MAI)和多用户干扰(MUI)正在影响无线系统的性能。在本文中,通过直接序列扩频(DS-SS)技术具有扩展信号的耙接收器。示出了使用最小均方(LMS),归一化最小平均正方形(NLMS)和仿射投影算法(APA)调整接收器抽头权重,以通过噪声消除来支持弱信号并减轻干扰。为了使数据收敛速度最小化并通过先前算法来降低计算复杂性,使用算法(例如序列部分,周期性部分,M-MAX)使用众所周知的部分更新(PU)自适应滤波器的方法。在所提出的系统中部分和选择性部分更新(SPU)。误码率(BER)与信噪比(SNR)的仿真结果示出为显示与完整更新自适应滤波器具有几乎相当的性能的部分更新算法的性能。此外,SPU部分对全NLMS和全APA具有关闭性能,而M-MAX部分对全LMS更新算法具有关闭性能。

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