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Equalization of MIMO-OFDM System under Time Varying Channel using ANFIS

机译:时变信道下基于ANFIS的MIMO-OFDM系统均衡

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Background/Objective: High speed reliable communication for wireless internet is the main challenge for all communication engineers. Methods: Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) is one possible solution, which promises high data rates. But MIMO-OFDM degrades the system performance in terms of Bit Error Rate (BER), due to Inter Symbol Interference (ISI), problem associated with multipath effect of the time varying wireless channels. To improve the performance of the MIMO-OFDM system a channel equalization technique is incorporated at the receiver end. Findings: The effectiveness of soft-computing approach in dealing the problem of non linear time varying channel is investigated in this paper by designing an equalizer based on Adaptive Neuro Fuzzy Inference System (ANFIS). The proposed technique is compared with the already tested Neural Network based equalizer. Result shows that the proposed equalizer gives better BER. Application/Improvements: The proposed equalizer can be implemented in wireless Local Area Networks (LAN) or mobile networks. The performance can be further improves with the increase signal length as evident by the graphs 14-16.
机译:背景/目的:无线互联网的高速可靠通信是所有通信工程师面临的主要挑战。方法:多输入多输出(MIMO)正交频分复用(OFDM)是一种可能的解决方案,它可以保证较高的数据速率。但是,由于符号间干扰(ISI),与时变无线信道的多径效应相关联的问题,MIMO-OFDM在误码率(BER)方面降低了系统性能。为了提高MIMO-OFDM系统的性能,在接收机端采用了信道均衡技术。发现:本文通过设计基于自适应神经模糊推理系统(ANFIS)的均衡器,研究了软计算方法在解决非线性时变信道问题方面的有效性。所提出的技术与已经测试过的基于神经网络的均衡器进行了比较。结果表明,所提出的均衡器具有更好的误码率。应用/改进:提议的均衡器可以在无线局域网(LAN)或移动网络中实现。如图14-16所示,随着信号长度的增加,性能可以进一步提高。

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