{"title":"Leaky least mean square (LLMS) algorithm for channel estimation in BPSK-QPSK-PSK MIMO-OFDM system","authors":"D. Bhoyar, C. Dethe, M. Mushrif, A. Narkhede","doi":"10.1109/IMAC4S.2013.6526485","DOIUrl":null,"url":null,"abstract":"In broadband wireless channel multiple-input multiple-output (MIMO) communication system combined with the orthogonal frequency division multiplexing (OFDM) modulation technique can achieve reliable high data rate transmission and to mitigate intersymbol interference. High data rate system suffer from inter symbol interference (ISI). To estimate the desire channel at the receiver channel Estimation techniques are used and also enhance system capacity of system. The MIMO-OFDM system uses two independent space-time codes for two sets of two transmit antennas. The objective of this paper is to improve channel estimation accuracy in MIMO-OFDM system because channel state information is required for signal detection at receiver and its accuracy affects the overall performance of system and it is essential for reliable communication. This paper presents channel estimation scheme based on Leaky Least Mean Square (LLMS) algorithm proposed for BPSK-QPSK-PSK MIMO OFDM System. So by designing this we are going to analyze the terms of the Minimum Mean Squares Error (MMSE), and Bit Error Rate (BER) and improve Signal to Noise Ratio.","PeriodicalId":403064,"journal":{"name":"2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMAC4S.2013.6526485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
In broadband wireless channel multiple-input multiple-output (MIMO) communication system combined with the orthogonal frequency division multiplexing (OFDM) modulation technique can achieve reliable high data rate transmission and to mitigate intersymbol interference. High data rate system suffer from inter symbol interference (ISI). To estimate the desire channel at the receiver channel Estimation techniques are used and also enhance system capacity of system. The MIMO-OFDM system uses two independent space-time codes for two sets of two transmit antennas. The objective of this paper is to improve channel estimation accuracy in MIMO-OFDM system because channel state information is required for signal detection at receiver and its accuracy affects the overall performance of system and it is essential for reliable communication. This paper presents channel estimation scheme based on Leaky Least Mean Square (LLMS) algorithm proposed for BPSK-QPSK-PSK MIMO OFDM System. So by designing this we are going to analyze the terms of the Minimum Mean Squares Error (MMSE), and Bit Error Rate (BER) and improve Signal to Noise Ratio.
在宽带无线信道中,多输入多输出(MIMO)通信系统与正交频分复用(OFDM)调制技术相结合,可以实现可靠的高数据速率传输和减轻码间干扰。高数据速率系统存在码间干扰(ISI)问题。在接收机处使用信道估计技术来估计期望信道,从而提高系统的容量。MIMO-OFDM系统采用两组独立的空时码,分别对应两组发射天线。MIMO-OFDM系统的信道估计精度是接收机检测信号所必需的,信道状态信息的准确性直接影响系统的整体性能,是保证系统可靠通信的关键。针对BPSK-QPSK-PSK MIMO OFDM系统,提出了基于泄漏最小均方(LLMS)算法的信道估计方案。因此,通过设计,我们将分析最小均方误差(MMSE)和误码率(BER)的术语,并提高信噪比。