MLP/BP-based MIMO DFEs for Suppressing ISI and ACI in Non-minimum Phase Channels
|
|
- Helen Campbell
- 6 years ago
- Views:
Transcription
1 MLP/BP-based MIMO DFEs for Suppressing ISI and ACI in Non-minimum Phase Channels Terng-Ren Hsu ( 許騰仁 ) and Kuan-Chieh Chao Department of Microelectronics Engineering, Chung Hua University No.77, Sec. 2, Wufu Rd., Hsinchu, Taiwan, 312, R.O.C. Tel: , Fax: trhsu@chu.edu.tw Abstract In this wor, we base on multi-layered perceptron neural networs with bacpropagation algorithm (MLP/BP) to construct multi-input multi-output (MIMO) decision feedbac equalizers (DFEs). The proposal is used to recover severe distorted nonreturn-to-zero (NRZ) data in non-minimum phase channels. From the simulations, we note that the proposed scheme can recover severe distorted signals as well as suppress intersymbol interference (ISI), adjacent channel interference (ACI) and bacground noise. The better BER performance as compared to a set of LMS DFEs is achieved in non-minimum phase channels. Keywords: MLP/BP Neural Networ (Multi-Layered Perceptron Neural Networ with Bacpropagation Algorithm), DFE (Decision Feedbac Equalizer), NRZ (Nonreturn-to-zero), ISI (Intersymbol Interference), ACI (Adjacent Channel Interference) 1. Introduction In practical digital communication systems, the source data are transmitted over intersymbol interference channels, tainted by noise, and then received as distorted nonreturn-to-zero (NRZ) ones. Besides, adjacent channel interference (ACI) will lead to more distortions and worse performance. Besides, the additive white Gaussian noise (AWGN) is used to model the bacground noise. In this draft, we consider several parallel non-minimum phase channels. In such channels, intersymbol interference results in lac of zero crossing for the received signal. Also, adjacent signals result in color noises; the received signal will be tainted by such color noises. ISI and ACI mae the received signal with large distortion. As a result, it is necessary to apply data equalizers to recover the original waveform from the distorted one in practical digital communications [1]. Conventionally, the NRZ signal recovery is based on either linear equalizers (LEs) [1], or decision feedbac equalizers (DFEs) [1-2]. A linear equalizer can restore the original transmitted signal in a minimum phase channel, where the channel distortion is linear without spectral nulls in the channel response. Nevertheless, as the channel frequency response has spectral nulls, the received noise will be enhanced in the process of compensating these nulls, resulting in degraded performance. Such non-minimum phase channels lead to malfunctions of linear equalizers. The DFE employing previous decisions to remove the ISI on the current symbol has been extensively exploited to severe ISI rejection. The least mean squares (LMS) algorithm is used to estimate the coefficients of the equalizer [1-2] whose
2 accuracy determines the system performance. Recently, various equalization schemes based on artificial neural networs have been applied to the severely distorting signal recoveries. Having the capability of classifying the sampling pattern and fault tolerance, neural-based solutions provide better performance than conventional equalization methods. Based on the MLP/BP neural networs [3], the feedforward equalizers [4-5], and the decision feedbac equalizers [6] have been broadly used to NRZ data recovery in ISI channels. Besides, Perceptron neural networs have been used as data equalizers in ISI and ACI channels [7-8]. For high-speed data communications, it is common to use waveform equalization technique to improve the data rate or decrease the error rate [9-11]. The receiver must detect correct data under ISI, ACI, and AWGN conditions. In our previous wor [12], MLP/BP-based DFEs are used to tolerate sampling cloc sew and channel response variance in wireline band-limited channels. Moreover, we use an MLP/BP-based MIMO DFE [13] to suppress ISI, ACI, and AWGN in wireline parallel band-limited channels. This wor is based on above studies. We use an MLP/BP-based MIMO DFE to recover the distorted NRZ signal in non-minimum phase channels. From the simulations, better performances as compared to a set of LMS DFEs are achieved. This article is organized as follows. The equivalent channel model, and the proposed approach are presented in section 2 while section 3 shows the simulation results. Finally, the conclusions are presented in section Proposed Architecture In this section, an equivalent channel model is presented first followed by the proposed approach. The architecture and configuration of the generalized MLP/BP-based MIMO DFE are discussed in detail. A. Channel Models In non-minimum phase channels, the received signal pulse is unable to complete its transition within a symbol interval. Besides, neighbor channels would cause the adjacent channel interference and taint the received signals. The equivalent model for the ISI channels with ACI and AWGN is shown in Fig. 1 where finite impulse response (FIR) filters are used to model the ISI channel responses and ACI responses with the AWGN. TX 2-PAM Signal TX 2-PAM Signal TX 2-PAM Signal ISI Response Weight #11 ACI Response Weight #12 ISI Response Weight #1M Weight #21 ACI Response Weight #22 ISI Response ISI Weight #2M Weight #M1 ACI Response Weight #M2 Weight #MM ACI AWGN AWGN AWGN RX NRZ Signal RX NRZ Signal RX NRZ Signal Fig. 1. Equivalent model for the ISI channels with ACI and AWGN The ISI responses and ACI responses with AWGN can be written as follows: H 1 2 L (z) = f + f1 z + f 2 z f L z (1) A (z) = g y r = L i= 1 2 M r + g r1 z + g r 2 z g rm z (2) f x (3) i i
3 a = r M j= g x j r j (4) y ˆ = y + a + n (5) where H (z) is the transfer function of the ISI channel responses; L is the length of the ISI channel response; A r (z) is the transfer function of the ACI responses; M is the length of the ACI response; x o is the input sequence of ISI response; x r is the input sequence of r-th ACI response; y is the channel output which is warped by ISI only; a is the sum of adjacent channel interference; n is the AWGN; ŷ is the received signal which is distorted by ISI, ACI and AWGN. equal to 8. Table 1 Weighting of ACI among different channels. Ch Magnitude (db) Phase (degree) -5 Frequency Response ISI ACI Normalized Frequency Fig. 2. Frequency responses of ISI and ACI In this wor, the non-minimum phase channels with ACI are used to verify the proposed approaches. Such channel condition is practical in many digital communication systems, whose the transfer function of the ISI channels is H (z) = z z -2 and the transfer function of the ACI is A r (z) = z z -2. The frequency responses of them are illustrated in Fig. 2. We use uniform distribution random values between 1 and to simulate the effects between different channels and construct an N N matrix which is normalized to mae the sum of squares of all elements be N. The weighting of ACI between different channels is shown in Table 1 where N is B. MLP/BP-based MIMO DFEs An artificial neural networ consists of a set of highly interconnected neurons such that each neuron output is connected to other ones or/and to itself through weights with or without lag. Recently, there are many different artificial neural networs had been proposed, but the multi-layer perceptron neural networ with bacpropagation algorithm (MLP/BP) is the most important and popular one. [3] The MLP/BP neural networs are supervised learning, meaning that a training set includes an input vector and a desired output vector. The training patterns must characterize the system characteristic. Apposite training patterns can improve the training quality. Using the MLP/BP neural networs to solve problems includes two phases, one is training procedure and another is test procedure. In the training phase, we use the gradient steepest descent method to minimize the error function for updating the weights. After that we apply the training results to obtain the networ response in the test phase. The result is really a sub-optimal solution. Different networ configurations, different initial conditions or different learning rate, will lead
4 to different performance. Usually, we could perform quite a few independent runs and choose the most fitting outcome as the final solution. In this wor, we execute ten independent runs and select the best one as the final result. The bloc diagram of the MLP/BP-based MIMO DFEs is shown in Fig. 3. It is a single hidden layer MLP architecture. The inputs of this MLP/BP-based MIMO DFE consist of feed-forward signals, which come from the input symbols by tapped-delay-line registers, and feedbac signals, which come from previous decisions by another tapped-delay-line registers. Ch-n Feedbac Ch-n Z -1 Ch-1 Z -1 Z -1 Z -1 Z -1 Z -1 Z Input Input -1 X -n X -n X -2 X -1 X Y m Y 2 Y 1 Input Layer Hidden Layer Output Layer MIMO MLP/BP Neural Networ Threshold Threshold Ch-n Ch-1 Output Output Fig. 3. MLP/BP-based MIMO DFE 3. Simulation Results The performance of the MLP/BP-based MIMO DFE is evaluated through the simulations for the distorted NRZ signal recovery in the non-minimum phase ISI channels with the non-minimum phase ACI. On the other word, the frequency responses of both ISI and ACI are with deep spectrum null. All equalization schemes in this wor have eleven symbols per channel in the forward part and five symbols per channel in the feedbac part. We assume there are 8 channels in this system. The number of neurons in the input layer is equal to 128 (16 by 8). The MLP/BP-based MIMO DFE uses the single hidden layer MLP architecture. The number of neurons in the hidden layer is 32. Since all the proposed equalization schemes have a single output per channel, the number of neurons in the output layer is equal to 8 (1 by 8). In the training procedure, the length of the training set is equal to 1 4 symbols and the total training epochs are 1 3. The two-phase learning is used with the learning rate of.5 (2-1 ) when the mean square error of the training set is larger than 1-3, and the learning rate of.125 (2-3 ), otherwise. When the training epochs exceed eighty percent of the total epochs, the best parameters will be recorded to achieve the lowest mean square error of the training set in the last twenty percent of the training epochs. Hence the steady-state training results can be recognized. In fact, the simulations indicate no unstable problems as all training processes are converged. Because different initial conditions lead to different effects, the non-training evaluation set that has symbols is used to examine the training quality of numerous independent simulation outcomes. After numerous independent training and evaluation runs, those yielding better outcomes will be chosen to perform a long trial with the test set, and then the best one will be the final test result. The length of the test set is symbols, and the evaluation set is its subset. In this wor, we execute 1 independent runs and select the best one as the final result. Also, we compare the performance of our proposed approach with that of a set of LMS DFEs. We use a LMS DFE without cross inputs for a channel among these adjacent channels. In this wor, the training noise and the evaluation noise are assumed to be SNR = 2dB, and SNR of the test signal is between 1dB and 25dB. The signal to adjacent channel interference ratio (SIR) is equal to 15, 2, and 25, respectively. Fig. 4 shows the comparisons of the BER vs. SNR performance for a set of LMS DFEs and the
5 proposed MLP/BP-based MIMO DFE in the non-minimum phase channels with different SIR. The proposed approach can improve SNR about 2dB at BER=1-3, where SIR=25dB. Considering different SIR in the non-minimum phase channels at SNR= 15, 2 and 25dB, respectively, Fig. 5 also shows the comparisons of the BER vs. SIR performance for a set of LMS DFEs and the MLP/BP-based MIMO DFE. The proposed approach can improve SIR over 5dB at BER=1-3, where SNR=25dB. From Fig. 4 and Fig. 5, the proposed approach reports better performance under larger intersymbol interference and larger adjacent channel interference. The proposed scheme can recover severe distorted NRZ signal as well as suppress ISI, ACI and AWGN. BER, (Test Symbol Per Channel = 1e6) BER, (Test Symbol Per Channel = 1e6) 1 BER Performance (Training Epoch = 1) LMS DFEs (SIR=15dB) BPN MIMO DFE (SIR=15dB) LMS DFEs (SIR=2dB) BPN MIMO DFE (SIR=2dB) LMS DFEs (SIR=25dB) BPN MIMO DFE (SIR=25dB) SNR (db), (Training SNR = 2dB) Fig. 4. BER vs. SNR performance at SIR = 15, 2, and 25 db 1 BER Performance (Training Epoch = 1) LMS DFE SNR=15 BPN DFE SNR=15 LMS DFE SNR=2 BPN DFE SNR=2 LMS DFE SNR=25 BPN DFE SNR= SIR (db), (Training SNR = 2dB) Fig. 5. BER vs. SIR performance at SNR= 15 and 2dB 4. Conclusion The present scheme can overcome ISI while suppress ACI. According to the simulation results, the MLP/BP-based MIMO DFE can recover severe distorted NRZ signals and suppress ACI to achieve better BER performance than LMS DFEs in the non-minimum phase channels. Because the proposed equalizer is a multi-input multi-output architecture, we can extend the input and output number for more complex system. Because the architecture of the proposed approach involves a large number of addition and multiplication, such requests cause high hardware complexity. For hardware implementations, the architecture of the MLP/BP-based MIMO DFEs is more complex than that of the conventional methods. However, we thin that the rapid progress of VLSI technology will afford more complex approaches for better performance. References [1] S. Hayin, Communication Systems 3e, Chapter 7, Wiley, [2] B. S. Song, and D. C. Soo, NRZ Timing Recovery Technique for Band-Limited Channels, IEEE J. Solid-State Circuits, vol. 32, no. 4, pp , [3] C. T. Lin, and C. S. G. Lee, Neural Fuzzy Systems, pp , pp , Prentice Hall, [4] G. J. Gibson, S. S., and C. F. N. Cowan, Multilayer Perceptron Structures Applied to Adaptive Equalisers for Data Communications, Proc. IEEE Int. Conf. on Acoustics, Speech and Signal, vol. 2, 1989, pp [5] T. R. Hsu, T. Y. Hsu, H. Y. Liu, S. D. Tzeng, J. N. Yang and C. Y. Lee, A MLP/BP-based Equalizer for NRZ Signal Recovery in
6 Band-Limited Channels, Proc. the 43 rd IEEE Midwest Symp. Circuits and Systems, vol. 3, 2, pp [6] S. Siu, G. J. Gibson, and C. F. N. Cowan, Decision Feedbac Equalisation Using Neural Networ Structures and Performance Comparison with Standard Architecture, IEE Proc. Communications, Speech and Vision, vol. 137, pt. I, no. 4, Aug. 199, pp [7] Z. Xiang, G. Bi, and T. Le-Ngoc, Polynomial Perceptrons and Their Applications to Fading Channel Equalization and Co-Channel Interference Suppression, IEEE Trans. Signal Processing, vol. 42, no. 9, Sep. 1994, pp [8] D. P. Bouras, P. T. Mathiopoulos, and D. Marais, Neural-Net-Based Receiver Structures for Single- and Multiamplitude Bandlimited Signals in CCI and ACI Channels, IEEE Trans. Vehicular Technology, vol. 46, no. 3, Aug. 1997, pp [9] Y. S. Sohn, S. J. Bae, H. J. Par, C. H. Kim, and S. I. Cho, A 2.2Gbps CMOS Loo-Ahead DFE Receiver for Multidrop Channel with Pin-to-Pin Time Sew Compensation, Proc. IEEE Custom Integrated Circuits Conference (CICC), 23, pp [1] J. E. Jaussi, G. Balamurugan, D. R. Johnson, B. Casper, A. Martin, J. Kennedy, N. Shanbhag and R. Mooney, 8-Gb/s Source-Synchronous I/O Lin with Adaptive Receiver Equalization, Offset Cancellation, and Cloc De-Sew, IEEE J. Solid-State Circuits, vol. 4, no. 1, Jan. 25, pp [11] S. J. Bae, H. J. Chi, H. R. Kim, and H. J. Par, A 3Gb/s 8b Single-Ended Transceiver for 4-Drop DRAM Interface with Digital Calibration of Equalization Sew and Offset Coefficients, Proc. IEEE Int. Solid-State Circuits Conference (ISSCC), 25, pp [12] T. R. Hsu, J. N. Yang, T. Y. Hsu, and C. Y. Lee, MLP/BP-based Decision Feedbac Equalizers with High Sew Tolerance in Wireline Band-Limited Channels, WSEAS Trans. Communications, vol. 5, no. 2, Feb. 26, pp [13] T. R. Hsu, T. Y. Hsu, J. T. Yang, and C. Y. Lee, Multi-Input Multi-Output MLP/BP-based Decision Feedbac Equalizers for Overcoming Intersymbol Interference and Co-Channel Interference in Wireline Band-Limited Channels, WSEAS Trans. Circuits and Systems, vol. 5, no. 4, Apr. 26, pp
Proceedings of the 6th WSEAS International Conference on Multimedia Systems & Signal Processing, Hangzhou, China, April 16-18, 2006 (pp )
Proceedings of the 6th WSEAS International Conference on Multimedia Systems & Signal Processing, Hangzhou, China, April 16-18, 26 (pp137-141) Multi-Input Multi-Output MLP/BP-based Decision Feedbac Equalizers
More informationADAPTIVE channel equalization without a training
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 9, SEPTEMBER 2005 1427 Analysis of the Multimodulus Blind Equalization Algorithm in QAM Communication Systems Jenq-Tay Yuan, Senior Member, IEEE, Kun-Da
More informationPerformance Comparison of ZF, LMS and RLS Algorithms for Linear Adaptive Equalizer
Advance in Electronic and Electric Engineering. ISSN 2231-1297, Volume 4, Number 6 (2014), pp. 587-592 Research India Publications http://www.ripublication.com/aeee.htm Performance Comparison of ZF, LMS
More informationPerformance Evaluation of different α value for OFDM System
Performance Evaluation of different α value for OFDM System Dr. K.Elangovan Dept. of Computer Science & Engineering Bharathidasan University richirappalli Abstract: Orthogonal Frequency Division Multiplexing
More informationNarrow-Band Interference Rejection in DS/CDMA Systems Using Adaptive (QRD-LSL)-Based Nonlinear ACM Interpolators
374 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 52, NO. 2, MARCH 2003 Narrow-Band Interference Rejection in DS/CDMA Systems Using Adaptive (QRD-LSL)-Based Nonlinear ACM Interpolators Jenq-Tay Yuan
More informationChapter 2 Channel Equalization
Chapter 2 Channel Equalization 2.1 Introduction In wireless communication systems signal experiences distortion due to fading [17]. As signal propagates, it follows multiple paths between transmitter and
More informationCOMBINED BLIND EQUALIZATION AND AUTOMATIC MODULATION CLASSIFICATION FOR COGNITIVE RADIOS UNDER MIMO ENVIRONMENT
COBINED BLIND EQUALIZATION AND AUTOATIC ODULATION CLASSIFICATION FOR COGNITIVE RADIOS UNDER IO ENVIRONENT Barathram Ramkumar (Wireless@VT, Bradley Department of Electrical Computer Engineering, Virginia
More informationDesign of DFE Based MIMO Communication System for Mobile Moving with High Velocity
Design of DFE Based MIMO Communication System for Mobile Moving with High Velocity S.Bandopadhaya 1, L.P. Mishra, D.Swain 3, Mihir N.Mohanty 4* 1,3 Dept of Electronics & Telecomunicationt,Silicon Institute
More informationElectronic Dispersion Compensation of 40-Gb/s Multimode Fiber Links Using IIR Equalization
Electronic Dispersion Compensation of 4-Gb/s Multimode Fiber Links Using IIR Equalization George Ng & Anthony Chan Carusone Dept. of Electrical & Computer Engineering University of Toronto Canada Transmitting
More informationSimple Impulse Noise Cancellation Based on Fuzzy Logic
Simple Impulse Noise Cancellation Based on Fuzzy Logic Chung-Bin Wu, Bin-Da Liu, and Jar-Ferr Yang wcb@spic.ee.ncku.edu.tw, bdliu@cad.ee.ncku.edu.tw, fyang@ee.ncku.edu.tw Department of Electrical Engineering
More informationTCM-coded OFDM assisted by ANN in Wireless Channels
1 Aradhana Misra & 2 Kandarpa Kumar Sarma Dept. of Electronics and Communication Technology Gauhati University Guwahati-781014. Assam, India Email: aradhana66@yahoo.co.in, kandarpaks@gmail.com Abstract
More informationA Radial Basis Function Network for Adaptive Channel Equalization in Coherent Optical OFDM Systems
121 A Radial Basis Function Network for Adaptive Channel Equalization in Coherent Optical OFDM Systems Gurpreet Kaur 1, Gurmeet Kaur 2 1 Department of Electronics and Communication Engineering, Punjabi
More informationPerformance Evaluation of Nonlinear Equalizer based on Multilayer Perceptron for OFDM Power- Line Communication
International Journal of Electrical Engineering. ISSN 974-2158 Volume 4, Number 8 (211), pp. 929-938 International Research Publication House http://www.irphouse.com Performance Evaluation of Nonlinear
More informationBlind Equalization Using Constant Modulus Algorithm and Multi-Modulus Algorithm in Wireless Communication Systems
Blind Equalization Using Constant Modulus Algorithm and Multi-Modulus Algorithm in Wireless Communication Systems Ram Babu. T Electronics and Communication Department Rao and Naidu Engineering College
More information5Gbps Serial Link Transmitter with Pre-emphasis
Gbps Serial Link Transmitter with Pre-emphasis Chih-Hsien Lin, Chung-Hong Wang and Shyh-Jye Jou Department of Electrical Engineering,National Central University,Chung-Li, Taiwan R.O.C. Abstract- High-speed
More informationNeural Model for Path Loss Prediction in Suburban Environment
Neural Model for Path Loss Prediction in Suburban Environment Ileana Popescu, Ioan Nafornita, Philip Constantinou 3, Athanasios Kanatas 3, Netarios Moraitis 3 University of Oradea, 5 Armatei Romane Str.,
More informationMultiuser Detection with Neural Network MAI Detector in CDMA Systems for AWGN and Rayleigh Fading Asynchronous Channels
The International Arab Journal of Information Technology, Vol. 10, No. 4, July 2013 413 Multiuser Detection with Neural Networ MAI Detector in CDMA Systems for AWGN and Rayleigh Fading Asynchronous Channels
More informationBlind Equalization using Constant Modulus Algorithm and Multi-Modulus Algorithm in Wireless Communication Systems
Blind Equalization using Constant Modulus Algorithm and Multi-Modulus Algorithm in Wireless Communication Systems Ram Babu. T Electronics and Communication Department Rao and Naidu Engineering College,
More informationPerformance Evaluation of OFDM System with Rayleigh, Rician and AWGN Channels
Performance Evaluation of OFDM System with Rayleigh, Rician and AWGN Channels Abstract A Orthogonal Frequency Division Multiplexing (OFDM) scheme offers high spectral efficiency and better resistance to
More informationChapter - 7. Adaptive Channel Equalization
Chapter - 7 Adaptive Channel Equalization Chapter - 7 Adaptive Channel Equalization 7.1 Introduction The transmission o f digital information over a communication channel causes Inter Symbol Interference
More informationPerformance Comparison of Power Control Methods That Use Neural Network and Fuzzy Inference System in CDMA
International Journal of Innovation Engineering and Science Research Open Access Performance Comparison of Power Control Methods That Use Neural Networ and Fuzzy Inference System in CDMA Yalcin Isi Silife-Tasucu
More informationFixed Point Lms Adaptive Filter Using Partial Product Generator
Fixed Point Lms Adaptive Filter Using Partial Product Generator Vidyamol S M.Tech Vlsi And Embedded System Ma College Of Engineering, Kothamangalam,India vidyas.saji@gmail.com Abstract The area and power
More informationA 5-Gb/s 156-mW Transceiver with FFE/Analog Equalizer in 90-nm CMOS Technology Wang Xinghua a, Wang Zhengchen b, Gui Xiaoyan c,
4th International Conference on Computer, Mechatronics, Control and Electronic Engineering (ICCMCEE 2015) A 5-Gb/s 156-mW Transceiver with FFE/Analog Equalizer in 90-nm CMOS Technology Wang Xinghua a,
More informationBiosignal filtering and artifact rejection. Biosignal processing, S Autumn 2012
Biosignal filtering and artifact rejection Biosignal processing, 521273S Autumn 2012 Motivation 1) Artifact removal: for example power line non-stationarity due to baseline variation muscle or eye movement
More informationLocal Oscillators Phase Noise Cancellation Methods
IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-issn: 2278-2834, p- ISSN: 2278-8735. Volume 5, Issue 1 (Jan. - Feb. 2013), PP 19-24 Local Oscillators Phase Noise Cancellation Methods
More informationMIMO Systems and Applications
MIMO Systems and Applications Mário Marques da Silva marques.silva@ieee.org 1 Outline Introduction System Characterization for MIMO types Space-Time Block Coding (open loop) Selective Transmit Diversity
More informationECEN720: High-Speed Links Circuits and Systems Spring 2017
ECEN72: High-Speed Links Circuits and Systems Spring 217 Lecture 4: Channel Pulse Model & Modulation Schemes Sam Palermo Analog & Mixed-Signal Center Texas A&M University Announcements & Agenda Lab 1 Report
More informationAn Adaptive Adjacent Channel Interference Cancellation Technique
SJSU ScholarWorks Faculty Publications Electrical Engineering 2009 An Adaptive Adjacent Channel Interference Cancellation Technique Robert H. Morelos-Zaragoza, robert.morelos-zaragoza@sjsu.edu Shobha Kuruba
More informationMulti Modulus Blind Equalizations for Quadrature Amplitude Modulation
Multi Modulus Blind Equalizations for Quadrature Amplitude Modulation Arivukkarasu S, Malar R UG Student, Dept. of ECE, IFET College of Engineering, Villupuram, TN, India Associate Professor, Dept. of
More informationTIMING recovery (TR) is one of the most challenging receiver
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II: EXPRESS BRIEFS, VOL. 53, NO. 12, DECEMBER 2006 1393 A Baud-Rate Timing Recovery Scheme With a Dual-Function Analog Filter Faisal A. Musa, Student Member, IEEE,
More informationParallel Digital Architectures for High-Speed Adaptive DSSS Receivers
Parallel Digital Architectures for High-Speed Adaptive DSSS Receivers Stephan Berner and Phillip De Leon New Mexico State University Klipsch School of Electrical and Computer Engineering Las Cruces, New
More informationEstimation of I/Q Imbalance in MIMO OFDM
International Conference on Recent Trends in engineering & Technology - 13(ICRTET'13 Special Issue of International Journal of Electronics, Communication & Soft Computing Science & Engineering, ISSN: 77-9477
More informationDetection and Estimation of Signals in Noise. Dr. Robert Schober Department of Electrical and Computer Engineering University of British Columbia
Detection and Estimation of Signals in Noise Dr. Robert Schober Department of Electrical and Computer Engineering University of British Columbia Vancouver, August 24, 2010 2 Contents 1 Basic Elements
More informationStudy of Turbo Coded OFDM over Fading Channel
International Journal of Engineering Research and Development e-issn: 2278-067X, p-issn: 2278-800X, www.ijerd.com Volume 3, Issue 2 (August 2012), PP. 54-58 Study of Turbo Coded OFDM over Fading Channel
More informationStudies on FIR Filter Pre-Emphasis for High-Speed Backplane Data Transmission
Studies on FIR Filter Pre-Emphasis for High-Speed Backplane Data Transmission Miao Li Department of Electronics Carleton University Ottawa, ON. K1S5B6, Canada Tel: 613 525754 Email:mili@doe.carleton.ca
More informationA Technique for Pulse RADAR Detection Using RRBF Neural Network
Proceedings of the World Congress on Engineering 22 Vol II WCE 22, July 4-6, 22, London, U.K. A Technique for Pulse RADAR Detection Using RRBF Neural Network Ajit Kumar Sahoo, Ganapati Panda and Babita
More informationUltra-high-speed Interconnect Technology for Processor Communication
Ultra-high-speed Interconnect Technology for Processor Communication Yoshiyasu Doi Samir Parikh Yuki Ogata Yoichi Koyanagi In order to improve the performance of storage systems and servers that make up
More informationPerformance Analysis of Equalizer Techniques for Modulated Signals
Vol. 3, Issue 4, Jul-Aug 213, pp.1191-1195 Performance Analysis of Equalizer Techniques for Modulated Signals Gunjan Verma, Prof. Jaspal Bagga (M.E in VLSI, SSGI University, Bhilai (C.G). Associate Professor
More informationChannel operating margin for PAM4 CDAUI-8 chip-to-chip interfaces
Channel operating margin for PAM4 CDAUI-8 chip-to-chip interfaces Adam Healey Avago Technologies IEEE P802.3bs 400 GbE Task Force March 2015 Introduction Channel Operating Margin (COM) is a figure of merit
More informationModulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks
Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks Presented By: Aaron Smith Authors: Aaron Smith, Mike Evans, and Joseph Downey 1 Automatic Modulation Classification
More informationAn Equalization Technique for Orthogonal Frequency-Division Multiplexing Systems in Time-Variant Multipath Channels
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL 47, NO 1, JANUARY 1999 27 An Equalization Technique for Orthogonal Frequency-Division Multiplexing Systems in Time-Variant Multipath Channels Won Gi Jeon, Student
More informationStatistical Link Modeling
April 26, 2018 Wendem Beyene UIUC ECE 546 Statistical Link Modeling Review of Basic Techniques What is a High-Speed Link? 1011...001 TX Channel RX 1011...001 Clock Clock Three basic building blocks: Transmitter,
More informationCross-Layer MAC Scheduling for Multiple Antenna Systems
Cross-Layer MAC Scheduling for Multiple Antenna Systems Marc Realp 1 and Ana I. Pérez-Neira 1 marc.realp@cttc.es; Telecommun. Technological Center of Catalonia (CTTC); Barcelona (Catalonia-Spain) anusa@gps.tsc.upc.es;
More informationTHE computational complexity of optimum equalization of
214 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 2, FEBRUARY 2005 BAD: Bidirectional Arbitrated Decision-Feedback Equalization J. K. Nelson, Student Member, IEEE, A. C. Singer, Member, IEEE, U. Madhow,
More informationCHAPTER 4 LINK ADAPTATION USING NEURAL NETWORK
CHAPTER 4 LINK ADAPTATION USING NEURAL NETWORK 4.1 INTRODUCTION For accurate system level simulator performance, link level modeling and prediction [103] must be reliable and fast so as to improve the
More informationAS DATA RATES increase, the variation in channel
80 IEEE JOURNAL OF SOLID-STATE CIRCUITS, VOL. 40, NO. 1, JANUARY 2005 8-Gb/s Source-Synchronous I/O Link With Adaptive Receiver Equalization, Offset Cancellation, and Clock De-Skew James E. Jaussi, Member,
More informationDecrease Interference Using Adaptive Modulation and Coding
International Journal of Computer Networks and Communications Security VOL. 3, NO. 9, SEPTEMBER 2015, 378 383 Available online at: www.ijcncs.org E-ISSN 2308-9830 (Online) / ISSN 2410-0595 (Print) Decrease
More informationEE5713 : Advanced Digital Communications
EE573 : Advanced Digital Communications Week 4, 5: Inter Symbol Interference (ISI) Nyquist Criteria for ISI Pulse Shaping and Raised-Cosine Filter Eye Pattern Error Performance Degradation (On Board) Demodulation
More informationA 10Gbps Analog Adaptive Equalizer and Pulse Shaping Circuit for Backplane Interface
Proceedings of the 5th WSEAS Int. Conf. on CIRCUITS, SYSTEMS, ELECTRONICS, CONTROL & SIGNAL PROCESSING, Dallas, USA, November 1-3, 2006 225 A 10Gbps Analog Adaptive Equalizer and Pulse Shaping Circuit
More informationSPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS
SPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS RASHMI SABNUAM GUPTA 1 & KANDARPA KUMAR SARMA 2 1 Department of Electronics and Communication Engineering, Tezpur University-784028,
More informationA fully digital clock and data recovery with fast frequency offset acquisition technique for MIPI LLI applications
LETTER IEICE Electronics Express, Vol.10, No.10, 1 7 A fully digital clock and data recovery with fast frequency offset acquisition technique for MIPI LLI applications June-Hee Lee 1, 2, Sang-Hoon Kim
More informationStatistical Communication Theory
Statistical Communication Theory Mark Reed 1 1 National ICT Australia, Australian National University 21st February 26 Topic Formal Description of course:this course provides a detailed study of fundamental
More informationPerformance Improvement of OFDM System using Raised Cosine Windowing with Variable FFT Sizes
International Journal of Research (IJR) Vol-1, Issue-6, July 14 ISSN 2348-6848 Performance Improvement of OFDM System using Raised Cosine Windowing with Variable FFT Sizes Prateek Nigam 1, Monika Sahu
More informationEE3723 : Digital Communications
EE3723 : Digital Communications Week 11, 12: Inter Symbol Interference (ISI) Nyquist Criteria for ISI Pulse Shaping and Raised-Cosine Filter Eye Pattern Equalization (On Board) 01-Jun-15 Muhammad Ali Jinnah
More informationSINCE the performance of personal computers (PCs) has
334 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II: EXPRESS BRIEFS, VOL. 57, NO. 5, MAY 2010 Multi-Slot Main Memory System for Post DDR3 Jaejun Lee, Sungho Lee, and Sangwook Nam, Member, IEEE Abstract This
More informationNarrow Band Interference (NBI) Mitigation Technique for TH-PPM UWB Systems in IEEE a Channel Using Wavelet Packet Transform
Narrow Band Interference (NBI) Mitigation Technique for TH-PPM UWB Systems in IEEE 82.15.3a Channel Using Wavelet Pacet Transform Brijesh Kumbhani, K. Sanara Sastry, T. Sujit Reddy and Rahesh Singh Kshetrimayum
More informationAdaptive Modulation and Coding Technique under Multipath Fading and Impulsive Noise in Broadband Power-line Communication
Adaptive Modulation and Coding Technique under Multipath Fading and Impulsive Noise in Broadband Power-line Communication Güray Karaarslan 1, and Özgür Ertuğ 2 1 MSc Student, Ankara, Turkey, guray.karaarslan@gmail.com
More informationPERFORMANCE EVALUATION OF A GIGABIT DSL MODEM USING SUPER ORTHOGONAL COMPLETE COMPLEMENTARY CODES UNDER PRACTICAL CROSSTALK CONDITIONS
144 SOUTH AFRICAN INSTITUTE OF ELECTRICAL ENGINEERS Vol.108 4) December 2017 PERFORMANCE EVALUATION OF A GIGABIT DSL MODEM USING SUPER ORTHOGONAL COMPLETE COMPLEMENTARY CODES UNDER PRACTICAL CROSSTALK
More informationChannel Estimation in Multipath fading Environment using Combined Equalizer and Diversity Techniques
International Journal of Scientific & Engineering Research Volume3, Issue 1, January 2012 1 Channel Estimation in Multipath fading Environment using Combined Equalizer and Diversity Techniques Deepmala
More informationA10-Gb/slow-power adaptive continuous-time linear equalizer using asynchronous under-sampling histogram
LETTER IEICE Electronics Express, Vol.10, No.4, 1 8 A10-Gb/slow-power adaptive continuous-time linear equalizer using asynchronous under-sampling histogram Wang-Soo Kim and Woo-Young Choi a) Department
More informationSystem Identification and CDMA Communication
System Identification and CDMA Communication A (partial) sample report by Nathan A. Goodman Abstract This (sample) report describes theory and simulations associated with a class project on system identification
More informationA 24Gb/s Software Programmable Multi-Channel Transmitter
A 24Gb/s Software Programmable Multi-Channel Transmitter A. Amirkhany 1, A. Abbasfar 2, J. Savoj 2, M. Jeeradit 2, B. Garlepp 2, V. Stojanovic 2,3, M. Horowitz 1,2 1 Stanford University 2 Rambus Inc 3
More informationPerformance analysis of BPSK system with ZF & MMSE equalization
Performance analysis of BPSK system with ZF & MMSE equalization Manish Kumar Department of Electronics and Communication Engineering Swift institute of Engineering & Technology, Rajpura, Punjab, India
More informationDYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS
DYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS Srinivas karedla 1, Dr. Ch. Santhi Rani 2 1 Assistant Professor, Department of Electronics and
More informationDecision Feedback Equalization for Filter Bank Multicarrier Systems
Decision Feedback Equalization for Filter Bank Multicarrier Systems Abhishek B G, Dr. K Sreelakshmi, Desanna M M.Tech Student, Department of Telecommunication, R. V. College of Engineering, Bengaluru,
More informationA Symbol-Rate Timing Synchronization Method for Low Power Wireless OFDM Systems Jui-Yuan Yu, Ching-Che Chung, and Chen-Yi Lee
922 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II: EXPRESS BRIEFS, VOL. 55, NO. 9, SEPTEMBER 2008 A Symbol-Rate Timing Synchronization Method for Low Power Wireless OFDM Systems Jui-Yuan Yu, Ching-Che Chung,
More informationUTA EE5362 PhD Diagnosis Exam (Spring 2012) Communications
EE536 Spring 013 PhD Diagnosis Exam ID: UTA EE536 PhD Diagnosis Exam (Spring 01) Communications Instructions: Verify that your exam contains 11 pages (including the cover sheet). Some space is provided
More informationNeural Network Classifier and Filtering for EEG Detection in Brain-Computer Interface Device
Neural Network Classifier and Filtering for EEG Detection in Brain-Computer Interface Device Mr. CHOI NANG SO Email: cnso@excite.com Prof. J GODFREY LUCAS Email: jglucas@optusnet.com.au SCHOOL OF MECHATRONICS,
More information1. Introduction. 2. OFDM Primer
A Novel Frequency Domain Reciprocal Modulation Technique to Mitigate Multipath Effect for HF Channel *Kumaresh K, *Sree Divya S.P & **T. R Rammohan Central Research Laboratory Bharat Electronics Limited
More informationSimulative Investigations for Robust Frequency Estimation Technique in OFDM System
, pp. 187-192 http://dx.doi.org/10.14257/ijfgcn.2015.8.4.18 Simulative Investigations for Robust Frequency Estimation Technique in OFDM System Kussum Bhagat 1 and Jyoteesh Malhotra 2 1 ECE Department,
More informationORTHOGONAL frequency division multiplexing
IEEE TRANSACTIONS ON BROADCASTING, VOL. 54, NO. 4, DECEMBER 2008 761 Effect and Compensation of Symbol Timing Offset in OFDM Systems With Channel Interpolation Abstract Symbol timing offset (STO) can result
More informationPerformance Evaluation of V-Blast Mimo System in Fading Diversity Using Matched Filter
Performance Evaluation of V-Blast Mimo System in Fading Diversity Using Matched Filter Priya Sharma 1, Prof. Vijay Prakash Singh 2 1 Deptt. of EC, B.E.R.I, BHOPAL 2 HOD, Deptt. of EC, B.E.R.I, BHOPAL Abstract--
More informationDiscrete Multi-Tone (DMT) is a multicarrier modulation
100-0513 1 Fast Unbiased cho Canceller Update During ADSL Transmission Milos Milosevic, Student Member, I, Takao Inoue, Student Member, I, Peter Molnar, Member, I, and Brian L. vans, Senior Member, I Abstract
More informationPERFORMANCE ANALYSIS OF PARTIAL RANSMIT SEQUENCE USING FOR PAPR REDUCTION IN OFDM SYSTEMS
PERFORMANCE ANALYSIS OF PARTIAL RANSMIT SEQUENCE USING FOR PAPR REDUCTION IN OFDM SYSTEMS *A.Subaitha Jannath, **C.Amarsingh Feroz *PG Scholar, Department of Electronics and Communication Engineering,
More informationWireless Communication: Concepts, Techniques, and Models. Hongwei Zhang
Wireless Communication: Concepts, Techniques, and Models Hongwei Zhang http://www.cs.wayne.edu/~hzhang Outline Digital communication over radio channels Channel capacity MIMO: diversity and parallel channels
More informationApplication of Frequency-Shift Filtering to the Removal of Adjacent Channel Interference in VLF Communications
Application of Frequency-Shift Filtering to the Removal of Adjacent Channel Interference in VLF Communications J.F. Adlard, T.C. Tozer, A.G. Burr. Communications Research Group, Department of Electronics
More informationPerformance Evaluation of STBC-OFDM System for Wireless Communication
Performance Evaluation of STBC-OFDM System for Wireless Communication Apeksha Deshmukh, Prof. Dr. M. D. Kokate Department of E&TC, K.K.W.I.E.R. College, Nasik, apeksha19may@gmail.com Abstract In this paper
More informationDepartment of Electronic Engineering FINAL YEAR PROJECT REPORT
Department of Electronic Engineering FINAL YEAR PROJECT REPORT BEngECE-2009/10-- Student Name: CHEUNG Yik Juen Student ID: Supervisor: Prof.
More informationCOMPARISON OF CHANNEL ESTIMATION AND EQUALIZATION TECHNIQUES FOR OFDM SYSTEMS
COMPARISON OF CHANNEL ESTIMATION AND EQUALIZATION TECHNIQUES FOR OFDM SYSTEMS Sanjana T and Suma M N Department of Electronics and communication, BMS College of Engineering, Bangalore, India ABSTRACT In
More informationPerformance Optimization in Wireless Channel Using Adaptive Fractional Space CMA
Communication Technology, Vol 3, Issue 9, September - ISSN (Online) 78-58 ISSN (Print) 3-556 Performance Optimization in Wireless Channel Using Adaptive Fractional Space CMA Pradyumna Ku. Mohapatra, Prabhat
More informationA Comparison of Particle Swarm Optimization and Gradient Descent in Training Wavelet Neural Network to Predict DGPS Corrections
Proceedings of the World Congress on Engineering and Computer Science 00 Vol I WCECS 00, October 0-, 00, San Francisco, USA A Comparison of Particle Swarm Optimization and Gradient Descent in Training
More informationJoint Transmitter-Receiver Adaptive Forward-Link DS-CDMA System
# - Joint Transmitter-Receiver Adaptive orward-link D-CDMA ystem Li Gao and Tan. Wong Department of Electrical & Computer Engineering University of lorida Gainesville lorida 3-3 Abstract A joint transmitter-receiver
More informationAnalysis and Improvements of Linear Multi-user user MIMO Precoding Techniques
1 Analysis and Improvements of Linear Multi-user user MIMO Precoding Techniques Bin Song and Martin Haardt Outline 2 Multi-user user MIMO System (main topic in phase I and phase II) critical problem Downlink
More informationADAPTIVE MMSE TURBO EQUALIZATION USING HIGH ORDER MODULATION: EXPERIMENTAL RESULTS ON UNDERWATER ACOUSTIC CHANNEL
ADAPTIVE MMSE TURBO EQUALIZATION USING HIGH ORDER MODULATION: EXPERIMENTAL RESULTS ON UNDERWATER ACOUSTIC CHANNEL C. Laot a, A. Bourré b and N. Beuzelin b a Institut Telecom; Telecom Bretagne; UMR CNRS
More informationCenter for Advanced Computing and Communication, North Carolina State University, Box7914,
Simplied Block Adaptive Diversity Equalizer for Cellular Mobile Radio. Tugay Eyceoz and Alexandra Duel-Hallen Center for Advanced Computing and Communication, North Carolina State University, Box7914,
More informationPAPR Reduction techniques in OFDM System Using Clipping & Filtering and Selective Mapping Methods
PAPR Reduction techniques in OFDM System Using Clipping & Filtering and Selective Mapping Methods Okello Kenneth 1, Professor Usha Neelakanta 2 1 P.G. Student, Department of Electronics & Telecommunication
More informationEstimation of I/Q Imblance in Mimo OFDM System
Estimation of I/Q Imblance in Mimo OFDM System K.Anusha Asst.prof, Department Of ECE, Raghu Institute Of Technology (AU), Vishakhapatnam, A.P. M.kalpana Asst.prof, Department Of ECE, Raghu Institute Of
More informationeye_eq Program Tutorial
eye_eq Program Tutorial Jungsub Byun When we send transmissions more closely in succession to increase the data transmission rate, interference between them is unavoidable. This phenomenon is called intersymbol
More informationIN A TYPICAL indoor wireless environment, a transmitted
126 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 48, NO. 1, JANUARY 1999 Adaptive Channel Equalization for Wireless Personal Communications Weihua Zhuang, Member, IEEE Abstract In this paper, a new
More informationTHE idea behind constellation shaping is that signals with
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO. 3, MARCH 2004 341 Transactions Letters Constellation Shaping for Pragmatic Turbo-Coded Modulation With High Spectral Efficiency Dan Raphaeli, Senior Member,
More informationArtificial Neural Network Channel Estimation for OFDM System
International Journal of Electronics and Computer Science Engineering 1686 Available Online at www.ijecse.org ISSN- 2277-1956 Artificial Neural Network Channel Estimation for OFDM System 1 Kanchan Sharma,
More informationTo learn fundamentals of high speed I/O link equalization techniques.
1 ECEN 720 High-Speed Links: Circuits and Systems Lab5 Equalization Circuits Objective To learn fundamentals of high speed I/O link equalization techniques. Introduction An ideal cable could propagate
More informationJaswant 1, Sanjeev Dhull 2 1 Research Scholar, Electronics and Communication, GJUS & T, Hisar, Haryana, India; is the corr-esponding author.
Performance Analysis of Constant Modulus Algorithm and Multi Modulus Algorithm for Quadrature Amplitude Modulation Jaswant 1, Sanjeev Dhull 2 1 Research Scholar, Electronics and Communication, GJUS & T,
More informationMobile Radio Systems OPAM: Understanding OFDM and Spread Spectrum
Mobile Radio Systems OPAM: Understanding OFDM and Spread Spectrum Klaus Witrisal witrisal@tugraz.at Signal Processing and Speech Communication Laboratory www.spsc.tugraz.at Graz University of Technology
More informationPerformance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK DS-CDMA
Performance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK DS-CDMA By Hamed D. AlSharari College of Engineering, Aljouf University, Sakaka, Aljouf 2014, Kingdom of Saudi Arabia, hamed_100@hotmail.com
More informationIndex Terms. Adaptive filters, Reconfigurable filter, circuit optimization, fixed-point arithmetic, least mean square (LMS) algorithms. 1.
DESIGN AND IMPLEMENTATION OF HIGH PERFORMANCE ADAPTIVE FILTER USING LMS ALGORITHM P. ANJALI (1), Mrs. G. ANNAPURNA (2) M.TECH, VLSI SYSTEM DESIGN, VIDYA JYOTHI INSTITUTE OF TECHNOLOGY (1) M.TECH, ASSISTANT
More informationPerformance Analysis of Ofdm Transceiver using Gmsk Modulation Technique
Performance Analysis of Ofdm Transceiver using Gmsk Modulation Technique Gunjan Negi Student, ECE Department GRD Institute of Management and Technology Dehradun, India negigunjan10@gmail.com Anuj Saxena
More informationORTHOGONAL frequency division multiplexing (OFDM)
144 IEEE TRANSACTIONS ON BROADCASTING, VOL. 51, NO. 1, MARCH 2005 Performance Analysis for OFDM-CDMA With Joint Frequency-Time Spreading Kan Zheng, Student Member, IEEE, Guoyan Zeng, and Wenbo Wang, Member,
More informationIEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 12, DECEMBER
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 12, DECEMBER 2002 1865 Transactions Letters Fast Initialization of Nyquist Echo Cancelers Using Circular Convolution Technique Minho Cheong, Student Member,
More informationA Chip-Rate MLSE Equalizer for DS-UWB Systems
A Chip-Rate Equalizer for DS-UWB Systems Praveen Kaligineedi Department of Electrical and Computer Engineering The University of British Columbia Vancouver, BC, Canada praveenk@ece.ubc.ca Viay K. Bhargava
More information