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Research on multiple classified signal detection algorithms based on mimo-ofdm system

机译:基于MIMO-OFDM系统的多分类信号检测算法研究

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OFDM is a high-speed signal transmission technology in wireless environment. In wireless channels, the frequency response curve is generally non-flat. MIMO technology can effectively increase system capacity, improve system performance, and improve network coverage and transmission reliability. OFDM technology can effectively resist intersymbol crosstalk caused by multipath propagation by adding a certain length of redundant guard interval in front of transmission symbols. According to the channel estimation and signal detection algorithms in MIMO?OFDM systems, this paper will choose a better algorithm to implement MIMO?OFDM systems and channel estimation and signal detection algorithms. Theoretical analysis and simulation results show that the optimal detection algorithm has the best performance, but its complexity is exponentially related to the number of antennas and modulation order. The architecture for dense texture analysis is developed based on Field Programmable Gate Array FPGA device which is a general engine for high-speed image processing. In order to maximize the performance, our architecture is designed for minimizing consumed resources. As explained in subsection our architecture is composed of two main operations, namely the AH based sum and difference of images and the calculus of texture features
机译:OFDM是无线环境中的高速信号传输技术。在无线通道中,频率响应曲线通常是非平面的。 MIMO技术可以有效提高系统容量,提高系统性能,提高网络覆盖和传输可靠性。 OFDM技术可以通过在传输符号前面添加一定长度的冗余保护区间来有效地抵抗多径传播引起的intersymbol串扰。根据MIMO的信道估计和信号检测算法,本文将选择更好的算法来实现MIMO系统和信道估计和信号检测算法。理论分析和仿真结果表明,最佳检测算法具有最佳性能,但其复杂性与天线数量和调制顺序指数呈指数级相关。基于现场可编程栅极阵列FPGA装置开发了密集纹理分析的架构,其是用于高速图像处理的一般发动机。为了最大化性能,我们的架构旨在最大限度地减少消耗的资源。如小节所解释的,我们的架构由两个主要操作组成,即基于AH的图像和纹理特征的微积分和微积分

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