Performance comparison of adaptive linear equalized and adaptive MMSE-DFE

被引:0
作者
Sharma, Saniay Kumar [1 ]
Ahmad, S. Naseem [2 ]
机构
[1] Dept. of Electronics and Communication Engg, Krishna Institute of Engg. and Technology, Ghaziabad-201206, 13 KM stone, Ghaziabad-Meerut Road
[2] Dept. of Electronics and Communication Engg, Jamia Millia Islamia
来源
Telecommunications and Radio Engineering (English translation of Elektrosvyaz and Radiotekhnika) | 2009年 / 68卷 / 08期
关键词
13;
D O I
10.1615/TelecomRadEng.v68.i8.50
中图分类号
学科分类号
摘要
The paper compares the performance of an adaptive linear equalizer and adaptive MMSE DFE. In mobile communication, intersymbol interference (ISI) caused by multipath in bandlimited (frequency selective) time dispersive channels distorts the transmitted signal, causing bit errors at the receiver. ISI has been recognized as the major obstacle to high-speed data transmission over wireless channels. Equalization is a technique used to combat ISI. Linear adaptive equalizers do not perform well on channels, which have deep spectral nulls in the passband. As a more powerful receiver algorithm, we prefer a decision feedback equalizer (DFE), which has better immunity against the spectral channel characteristics. In the paper, we have investigated various adaptive equalizers using the recursive least-squares (RLS) algorithm for wireless communication systems. In that regard, both linear equalizer and non-linear DFE with RLS algorithm have been examined in multipath fading channel model. We have also examined the influence of some important parameters, such as a tap number of the adaptive equalizers, and forgetting factor of the algorithm. Simulation results show that DFE perform much better than adaptive linear equalizer. Further the theoretical results have also been verified through computer simulation .© 2009 Begell House, Inc.
引用
收藏
页码:697 / 708
页数:11
相关论文
共 50 条
[21]   Symbol rate optimization for the MMSE-DFE on bandlimited dispersive channels [J].
AlDhahir, N ;
Cioffi, JM .
DIGITAL SIGNAL PROCESSING, 1996, 6 (02) :73-95
[22]   A Universal MMSE-DFE Equalizer with its Application to WLAN Receiver [J].
Hua Wei ;
Yao Huang ;
Jiang Du ;
Li Li .
Wireless Personal Communications, 2015, 85 :2507-2518
[23]   Mitigating Error Propagation of MMSE-DFE by Joint Parameter Optimization [J].
Wang, Rujiang ;
Delisle, Gilles Y. .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2009, 57 (08) :2239-2243
[24]   A Universal MMSE-DFE Equalizer with its Application to WLAN Receiver [J].
Wei, Hua ;
Huang, Yao ;
Du, Jiang ;
Li, Li .
WIRELESS PERSONAL COMMUNICATIONS, 2015, 85 (04) :2507-2518
[25]   Bridging the Gap Between MMSE-DFE and Optimal Detection of MIMO Systems [J].
Izadinasab, Mohammad Kazem ;
Damen, Oussama .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2020, 68 (01) :220-231
[26]   Iterative MMSE-DFE and Error Transfer for OFDM in Doubly Selective Channels [J].
Huang, Su ;
Wang, Jun ;
An, Zhecheng ;
Wang, Jintao ;
Song, Jian .
IEEE TRANSACTIONS ON BROADCASTING, 2015, 61 (03) :541-547
[27]   MMSE-DFE equalizer design for OFDM systems with insufficient cyclic prefix [J].
Parsaee, GR ;
Yarali, A ;
Ebrahimzad, H .
VTC2004-FALL: 2004 IEEE 60TH VEHICULAR TECHNOLOGY CONFERENCE, VOLS 1-7: WIRELESS TECHNOLOGIES FOR GLOBAL SECURITY, 2004, :3828-3832
[28]   Computationally Efficient MMSE and MMSE-DFE Equalizations for Asynchronous Cooperative Communications with Multiple Frequency Offsets [J].
Wang, Huiming ;
Xia, Xiang-Gen ;
Yin, Qinye ;
Wang, Wenjie .
2008 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-6, 2008, :2267-+
[29]   MMSE-DFE Based MIMO Relay System with Correlated Fading Channel [J].
Rong, Yue .
IEEE WIRELESS COMMUNICATIONS LETTERS, 2012, 1 (03) :157-160
[30]   A parallel low-complexity coefficient computation processor for the MMSE-DFE [J].
Al-Dhahir, N ;
Sayed, AH .
THIRTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2, 1998, :1586-1590