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TIME-FREQUENCY 2-D LMS BASED LONG-RANGE CHANNEL PREDICTION FOR WIRELESS OFDM SYSTEMS
作者姓名:Xu  Xiaodong  Jing  Ya  Hua  Jingyu  You  Xiaohu
作者单位:Xu Xiaodong Jing Ya Hua Jingyu You Xiaohu (National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China) (Zhejiang University of Technology,Hangzhou 310027,China)
基金项目:Supported by the National Natural Science Foundation of China (No.60496311).
摘    要:Adaptive modulation can optimize the spectrum efficiency and system performance with the channel state information achieved by the long-range channel prediction.To avoid re-estimating channel correlation function as the channel statioharity varies and to track the channel adaptively, LMS (Least-Mean-Square) based long-range channel prediction is discussed in the existing literature, but it needs long observation interval to reach the convergence.Given that all OFDM (Orthogonal Frequency Division Multiplexing) subcarriers have the identical time-domain correlation and sta- tionarity during the same time interval,this paper proposed a 2-D LMS based predictor which updates the filter weights in both time and frequency domain.The proposed scheme can effectively decrease the observation intervals and significantly speed up the convergence than the conventional LMS and Parallel LMS (PLMS).Complexity analysis and simulation results prove that the proposed scheme can improve the BER (Bit Error Rate) performance and spectrum efficiency with negligible complexity increase.

关 键 词:时间频率  2-D  月形模块模拟器  长范围通道  无线电
收稿时间:2 December 2005
修稿时间:2005-12-02

Time-frequency 2-D LMS based long-range channel prediction for wireless OFDM systems
Xu Xiaodong Jing Ya Hua Jingyu You Xiaohu.TIME-FREQUENCY 2-D LMS BASED LONG-RANGE CHANNEL PREDICTION FOR WIRELESS OFDM SYSTEMS[J].Journal of Electronics,2007,24(5):583-587.
Authors:Xu Xiaodong  Jing Ya  Hua Jingyu  You Xiaohu
Affiliation:1. National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
2. Zhejiang University of Technology, Hangzhou 310027, China
Abstract:Adaptive modulation can optimize the spectrum efficiency and system performance with the channel state information achieved by the long-range channel prediction.To avoid re-estimating channel correlation function as the channel statioharity varies and to track the channel adaptively, LMS (Least-Mean-Square) based long-range channel prediction is discussed in the existing literature, but it needs long observation interval to reach the convergence.Given that all OFDM (Orthogonal Frequency Division Multiplexing) subcarriers have the identical time-domain correlation and sta- tionarity during the same time interval,this paper proposed a 2-D LMS based predictor which updates the filter weights in both time and frequency domain.The proposed scheme can effectively decrease the observation intervals and significantly speed up the convergence than the conventional LMS and Parallel LMS (PLMS).Complexity analysis and simulation results prove that the proposed scheme can improve the BER (Bit Error Rate) performance and spectrum efficiency with negligible complexity increase.
Keywords:Orthogonal Frequency Division Multiplexing (OFDM)  Channel prediction  Least-Mean-Square (LMS)  Adaptive modulation
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