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Using Wavelet to Enhance the performance of OFDM System and Adaptive Array Beamforming

机译:使用小波增强OFDM系统和自适应阵列波束成形的性能

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Frequency selective fading effects inOFDMbased high speed wireless communication systems can be highly mitigated by using adaptive antenna arrays-In addition, the use of discrete wavelet transform (DWT) processing in OFDM systems can successfully counterthe degrading effect ofintersymbolinterference(ISI)without the need of cyclic prefix (CP),and hence conserves bandwidthand improves the spectral efficiency. In this paper, an OFDM system utilizing DWT based least mean square (LMS) adaptive beamformeris considered. Constant modulus algorithm (CMA) and least mean square (LMS), kind ofnonblind and blind algorithms used foradaptive beamforming are presented. These algorithms are embedded in smart antenna which calculates optimum weight vector that minimizes the total received power except the power coming from desired direction. The use of the wavelet transform reduces the signal space dimension and hence results in low complexity in addition to data denoising.Time saving in signal beamforming processing can be achieved by using different levels of decomposition in the wavelet transform, with acceptable accuracy. Theoretical analysis and computer simulations demonstrate how the suggested scheme, with different wavelet families and different decomposition levels, achieves better beamforming performancewithfasterconvergence, as compared to conventional adaptive beamforming.
机译:通过使用自适应天线阵列可以大大减轻基于OFDM的高速无线通信系统中的频率选择性衰落效应-此外,在OFDM系统中使用离散小波变换(DWT)处理可以成功地抵消符号间干扰(ISI)的降级效应,而无需循环前缀(CP),从而节省带宽并提高频谱效率。在本文中,考虑了使用基于DWT的最小均方(LMS)自适应波束形成的OFDM系统。提出了用于自适应波束形成的恒模算法(CMA)和最小均方(LMS)算法。这些算法被嵌入到智能天线中,该智能天线可计算最佳权向量,从而将总接收功率(来自所需方向的功率除外)最小化。小波变换的使用减少了信号空间的维数,因此除数据去噪外还降低了复杂度。通过在小波变换中使用不同程度的分解,可以以可接受的精度节省信号波束形成处理中的时间。理论分析和计算机仿真表明,与传统的自适应波束形成相比,所建议的方案具有不同的小波族和不同的分解级别,如何以更快的收敛性实现更好的波束形成性能。

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