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Journal articles on the topic 'Decision Feedback Equalizer'

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Published: 4 June 2021

Last updated: 28 January 2023

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1

Tuzlukov, Vyacheslav. "Generalized Receiver with Decision-Feedback Equalizer for Multicode Wideband DS-CDMA." WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 21 (September 1, 2022): 202–22. http://dx.doi.org/10.37394/23201.2022.21.23.

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In the present paper, a chip-level minimum mean-square-error (MMSE) decision-feedback equalizer for the downlink receiver of multicode wideband direct sequence code-division multiple access (DS-CDMA) wireless communication systems over frequency-selective channels is investigated. Firstly, the MMSE per sym-bol achievable by an optimal decision-feedback equalizer is derived, assuming that all interchip interference (ICI) of the desired user can be eliminated. The MMSE of the decision-feedback equalizer is always less than or at most equal to that of linear equalizers. When all the active codes belong to the desired user, the ideal deci-sion-feedback equalizer is able to eliminate multicode interference and approach the performance of the single-code case at high signal-to-noise ratio (SNR) range. Secondly, we apply the hypothesis-feedback equalizer or tentative-chip decision-feedback equalizer in the multicode scenario. The tentative-chip decision-feedback equ-alizer outperforms the chip-level linear equalizer and the decision-feedback equalizer that only feeds back the symbols already decided. The performance gain increases with SNR, but decreases with the number of active codes owned by the other users. When all the active codes are assigned to the desired user, the tentative-chip decision-feedback equalizer eliminates the multicode interference and achieves single-user performance at the high SNR, similarly, to the ideal decision-feedback equalizer. The asymptotic performance of the decision-feed-back equalizer is confirmed through the bit error rate (BER) simulation over various channels.

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2

Bergmans, J. W. M., J. O. Voorman, and H. W. Wong-Lam. "Dual decision feedback equalizer." IEEE Transactions on Communications 45, no. 5 (May 1997): 514–18. http://dx.doi.org/10.1109/26.592548.

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3

Sewter, Jonathan, and Anthony Chan Carusone. "Equalizer Architectures for 40-Gb/s Optical Systems Limited by Polarization-Mode Dispersion." International Journal of High Speed Electronics and Systems 15, no. 03 (September 2005): 549–66. http://dx.doi.org/10.1142/s0129156405003326.

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An analysis of first-order polarization-mode dispersion (PMD) effects in a 40-Gb/s optical system is used to compare different electronic equalizer architectures as potential PMD compensators. Both linear and nonlinear equalizers are considered employing symbol-spaced and fractionally-spaced taps. It is found that a decision feedback equalizer consisting of a 3-tap symbol-spaced feedforward equalizer and a 1-tap feedback equalizer effectively eliminates PMD as the dominant length-limiting factor in most 40-Gb/s optical systems. Such an equalizer would entail less complexity than several previously reported electronic PMD compensators.

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4

Kongara, G., D. P. Taylor, and P. A. Martin. "Space-Frequency Decision Feedback Equalizer." IEEE Transactions on Vehicular Technology 60, no. 4 (May 2011): 1626–39. http://dx.doi.org/10.1109/tvt.2011.2131159.

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5

HANUMOLU, PAVAN KUMAR, GU-YEON WEI, and UN-KU MOON. "EQUALIZERS FOR HIGH-SPEED SERIAL LINKS." International Journal of High Speed Electronics and Systems 15, no. 02 (June 2005): 429–58. http://dx.doi.org/10.1142/s0129156405003259.

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In this tutorial paper we present equalization techniques to mitigate inter-symbol interference (ISI) in high-speed communication links. Both transmit and receive equalizers are analyzed and high-speed circuits implementing them are presented. It is shown that a digital transmit equalizer is the simplest to design, while a continuous-time receive equalizer generally provides better performance. Decision feedback equalizer (DFE) is described and the loop latency problem is addressed. Finally, techniques to set the equalizer parameters adaptively are presented.

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6

Arie, Dana, and Gilad Katz. "Electrical Equalization Analysis of PAM-4 Transmission in Short-Reach Optical Systems." Applied Sciences 12, no. 4 (February 21, 2022): 2255. http://dx.doi.org/10.3390/app12042255.

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Inclusive and intensive performance analysis of electrical equalizers in a short-reach optical system using four-level pulse amplitude modulation (PAM-4) is presented in this paper. Two equalizers are used—a feedforward equalizer and decision feedback equalizer using the least mean square algorithm. The sensitivity to cut-off frequency for the transmitter and receiver filters, fiber length and number of equalizers taps in the means of the bit error rate vs. optical input power are shown. The analysis reveals the considerable impact of the filters’ bandwidth, particularly in the receiver, on the equalizer performance. These results and their reasons are analyzed and broadly discussed.

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7

Kim, D. W., S. H. Han, M. S. Eun, J. S. Choi, and Y. S. Cho. "An adaptive decision feedback equalizer using error feedback." IEEE Transactions on Consumer Electronics 42, no. 3 (1996): 468–77. http://dx.doi.org/10.1109/30.536144.

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8

Goupil, Alban, and Jacques Palicot. "An efficient blind decision feedback equalizer." IEEE Communications Letters 14, no. 5 (May 2010): 462–64. http://dx.doi.org/10.1109/lcomm.2010.05.092150.

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9

Chen, S., B. Mulgrew, and S. McLaughlin. "Adaptive Bayesian equalizer with decision feedback." IEEE Transactions on Signal Processing 41, no. 9 (1993): 2918–27. http://dx.doi.org/10.1109/78.236513.

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10

Zhang, Sumin, Shu Li, and Donglin Su. "Adaptive support vector machine decision feedback equalizer." Journal of Systems Engineering and Electronics 22, no. 3 (June 2011): 452–61. http://dx.doi.org/10.3969/j.issn.1004-4132.2011.03.013.

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11

Kim, Kyuhwan, Seung Hun Kim, Gyogwon Koo, Min Seok Seo, and Sang Woo Kim. "Decision feedback equalizer for holographic data storage." Applied Optics 57, no. 15 (May 15, 2018): 4056. http://dx.doi.org/10.1364/ao.57.004056.

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12

Kim, Y., and J. Moon. "CCK Demodulation via Symbol Decision Feedback Equalizer." IEEE Communications Letters 8, no. 10 (October 2004): 620–22. http://dx.doi.org/10.1109/lcomm.2004.836839.

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13

McEwen, P. A., and J. G. Kenney. "Allpass forward equalizer for decision feedback equalization." IEEE Transactions on Magnetics 31, no. 6 (1995): 3045–47. http://dx.doi.org/10.1109/20.490264.

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14

Yu Gong and C. F. N. Cowan. "A self-structured adaptive decision feedback equalizer." IEEE Signal Processing Letters 13, no. 3 (March 2006): 169–72. http://dx.doi.org/10.1109/lsp.2005.862601.

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15

Min, Woong-Ki, and Bai-Sun Kong. "High Speed Low Power Decision-Feedback Equalizer Techniques." Journal of IKEEE 20, no. 3 (September 30, 2016): 285–90. http://dx.doi.org/10.7471/ikeee.2016.20.3.285.

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16

Ariyavisitakul, S. "A decision feedback equalizer with time-reversal structure." IEEE Journal on Selected Areas in Communications 10, no. 3 (April 1992): 599–613. http://dx.doi.org/10.1109/49.127782.

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17

Le, M. Q., P. J. Hurst, and J. P. Keane. "An adaptive analog noise-predictive decision-feedback equalizer." IEEE Journal of Solid-State Circuits 37, no. 2 (2002): 105–13. http://dx.doi.org/10.1109/4.982416.

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18

Lin, H., and K. Yamashita. "Blind equalization using parallel Bayesian decision feedback equalizer." Mathematics and Computers in Simulation 56, no. 3 (June 2001): 247–57. http://dx.doi.org/10.1016/s0378-4754(01)00276-2.

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19

Palicot, Jacques, and Alban Goupil. "Performance analysis of the weighted decision feedback equalizer." Signal Processing 88, no. 2 (February 2008): 284–95. http://dx.doi.org/10.1016/j.sigpro.2007.07.021.

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20

Berberidis, K., T. A. Rontogiannis, and S. Theodoridis. "Efficient block implementation of the decision feedback equalizer." IEEE Signal Processing Letters 5, no. 6 (June 1998): 129–31. http://dx.doi.org/10.1109/97.681426.

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21

Weining Zeng and J. Moon. "Decision feedback equalizer with pattern dependent dynamic threshold." IEEE Transactions on Magnetics 32, no. 4 (July 1996): 3266–73. http://dx.doi.org/10.1109/20.508391.

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22

Kennedy, R. A., B. D. O. Anderson, and R. R. Bitmead. "Stochastic Dynamics of Blind Decision Feedback Equalizer Adaptation." IFAC Proceedings Volumes 23, no. 1 (April 1990): 579–84. http://dx.doi.org/10.1016/s1474-6670(17)52780-9.

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23

LIN, H. "Bayesian Decision Feedback Equalizer with Receiver Diversity Combining." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E88-A, no. 2 (February 1, 2005): 597–98. http://dx.doi.org/10.1093/ietfec/e88-a.2.597.

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24

Yongde, Wang, and Pang Xiaozhong. "A decision feedback equalizer for non-linear channels." Journal of Electronics (China) 12, no. 4 (October 1995): 352–58. http://dx.doi.org/10.1007/bf02729277.

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25

Zerdoumi, Zohra, Djamel Chikouche, and Djamel Benatia. "Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channels." International Journal of Mobile Computing and Multimedia Communications 7, no. 3 (July 2016): 16–31. http://dx.doi.org/10.4018/ijmcmc.2016070102.

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Neural network based equalizers can easily compensate channel impairments; such additive noise and inter symbol interference (ISI). The authors present a new approach to improve the training efficiency of the multilayer perceptron (MLP) based equalizer. Their improvement consists on modifying the back propagation (BP) algorithm, by adapting the activation function in addition to the other parameters of the MLP structure. The authors report on experiment results evaluating the performance of the proposed approach namely the back propagation with adaptive activation function (BPAAF) next to the BP algorithm. To further prove its effectiveness, the proposed approach is also compared beside a so known nonlinear equalizer explicitly the multilayer perceptron with decision feedback equalizer MLPDFE. The authors consider various performance measures specifically: signal resorted quality, lower steady state MSE reached and minimum bit error rate (BER) achieved, where nonlinear channel equalization problems are employed.

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26

LI, Chi-Min, Shao-Min WEN, Pao-Jen WANG, Jia-Chyi WU, and I.-Tseng TANG. "An Overlap-Cut Frequency Domain Equalizer with Decision Feedback." IEICE Transactions on Communications E92-B, no. 5 (2009): 1475–83. http://dx.doi.org/10.1587/transcom.e92.b.1475.

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27

Lee, Su-Kyoung, Yong-Hyun Park, and Bo-Seok Seo. "Noise Whitening Decision Feedback Equalizer for SC-FDMA Receivers." Journal of Broadcast Engineering 16, no. 6 (November 30, 2011): 986–95. http://dx.doi.org/10.5909/jeb.2011.16.6.986.

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28

Yang, T. C. "Correlation-Based Decision-Feedback Equalizer for Underwater Acoustic Communications." IEEE Journal of Oceanic Engineering 30, no. 4 (October 2005): 865–80. http://dx.doi.org/10.1109/joe.2005.862126.

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29

Kim, Nam-Yong. "Blind Equalizer Algorithms using Random Symbols and Decision Feedback." Journal of the Korea Academia-Industrial cooperation Society 13, no. 1 (January 31, 2012): 343–47. http://dx.doi.org/10.5762/kais.2012.13.1.343.

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30

Perreau, S., L. B. White, and P. Duhamel. "A blind decision feedback equalizer incorporating fixed lag smoothing." IEEE Transactions on Signal Processing 48, no. 5 (May 2000): 1315–28. http://dx.doi.org/10.1109/78.839979.

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31

Inkyu Lee and J. M. Cioffi. "A fast computation algorithm for the decision feedback equalizer." IEEE Transactions on Communications 43, no. 11 (1995): 2742–49. http://dx.doi.org/10.1109/26.481225.

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32

Razavi, Behzad. "The Decision-Feedback Equalizer [A Circuit for All Seasons]." IEEE Solid-State Circuits Magazine 9, no. 4 (2017): 13–132. http://dx.doi.org/10.1109/mssc.2017.2745939.

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33

Reuter, M., J. C. Allen, J. R. Zeidler, and R. C. North. "Mitigating error propagation effects in a decision feedback equalizer." IEEE Transactions on Communications 49, no. 11 (2001): 2028–41. http://dx.doi.org/10.1109/26.966079.

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34

Yang, J., and Y. Li. "Tentative chip decision-feedback equalizer for multicode wideband CDMA." IEEE Transactions on Wireless Communications 4, no. 1 (January 2005): 137–48. http://dx.doi.org/10.1109/twc.2004.840240.

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35

Chakraborty, Mrityunjoy, and Suraiya Pervin. "Pipelining the adaptive decision feedback equalizer with zero latency." Signal Processing 83, no. 12 (December 2003): 2675–81. http://dx.doi.org/10.1016/j.sigpro.2003.07.003.

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36

Sunghwan Ong, Sooyong Choi, Cheolwoo You, and Daesik Hong. "A decision feedback recurrent neural equalizer for digital communication." IEEE Transactions on Magnetics 33, no. 5 (1997): 2767–69. http://dx.doi.org/10.1109/20.617724.

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37

Qin, Lei, and Wen-jun Zhang. "A robust decision feedback equalizer for ATSC DTV receivers." Journal of Shanghai Jiaotong University (Science) 13, no. 1 (February 2008): 1–5. http://dx.doi.org/10.1007/s12204-008-0001-3.

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38

Hainz, Simon, and Dirk Hammerschmidt. "Compensation of Angular Errors Using Decision Feedback Equalizer Approach." IEEE Sensors Journal 8, no. 9 (September 2008): 1548–56. http://dx.doi.org/10.1109/jsen.2008.925456.

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39

Yungsoo Kim and Hwang-Soo Lee. "A decision-feedback equalizer with pattern-dependent feedback for magnetic recording channels." IEEE Transactions on Communications 49, no. 1 (2001): 9–13. http://dx.doi.org/10.1109/26.898242.

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40

Pola, Ariel L., Juan E. Cousseau, Oscar E. Agazzi, and Mario R. Hueda. "A Low-Complexity Decision Feedforward Equalizer Architecture for High-Speed Receivers on Highly Dispersive Channels." Journal of Electrical and Computer Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/587108.

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This paper presents an improved decision feedforward equalizer (DFFE) for high speed receivers in the presence of highly dispersive channels. This decision-aided equalizer technique has been recently proposed for multigigabit communication receivers, where the use of parallel processing is mandatory. Well-known parallel architectures for the typical decision feedback equalizer (DFE) have a complexity that grows exponentially with the channel memory. Instead, the new DFFE avoids that exponential increase in complexity by using tentative decisions to cancel iteratively the intersymbol interference (ISI). Here, we demostrate that the DFFE not only allows to obtain a similar performance to the typical DFE but it also reduces the compelxity in channels with large memory. Additionally, we propose a theoretical approximation for the error probability in each iteration. In fact, when the number of iteration increases, the error probability in the DFFE tends to approach the DFE. These benefits make the DFFE an excellent choice for the next generation of high-speed receivers.

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41

Liu, Zhixin, Ming Li, and Chun-Kit Chan. "Chromatic Dispersion Compensation With Feed Forward Equalizer and Decision Feedback Equalizer for Manchester Coded Signals." Journal of Lightwave Technology 29, no. 18 (September 2011): 2740–46. http://dx.doi.org/10.1109/jlt.2011.2163385.

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42

Oh, Young-Ho, Kyoung-Won Lee, and Dae-Jin Kim. "Performance analysis of decision feedback equalizer with dual-feedback in pre-ghost channel." Journal of Broadcast Engineering 12, no. 5 (September 29, 2007): 516–24. http://dx.doi.org/10.5909/jbe.2007.12.5.516.

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43

Kim, Nam-Yong. "Decision Feedback Equalizer based on Maximization of Zero-Error Probability." Journal of Korea Information and Communications Society 36, no. 8C (August 31, 2011): 516–21. http://dx.doi.org/10.7840/kics.2011.36c.8.516.

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44

Son, Ji-hong, and Ki-man Kim. "Tap-length Optimization of Decision Feedback Equalizer Using Genetic Algorithm." Journal of the Korea Institute of Information and Communication Engineering 19, no. 8 (August 31, 2015): 1765–72. http://dx.doi.org/10.6109/jkiice.2015.19.8.1765.

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45

Kim, Nam-Yong, and Young-Soo Hwang. "Communication Equalizer Algorithms with Decision Feedback based on Error Probability." Journal of the Korea Academia-Industrial cooperation Society 12, no. 5 (May 31, 2011): 2390–95. http://dx.doi.org/10.5762/kais.2011.12.5.2390.

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46

Hanzo, L., B. Mulgrew, and S. Chen. "Asymptotic Bayesian decision feedback equalizer using a set of hyperplanes." IEEE Transactions on Signal Processing 48, no. 12 (2000): 3493–500. http://dx.doi.org/10.1109/78.887042.

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47

Wen-Rong Wu and Yih-Ming Tsuie. "An LMS-based decision feedback equalizer for IS-136 receivers." IEEE Transactions on Vehicular Technology 51, no. 1 (2002): 130–43. http://dx.doi.org/10.1109/25.992074.

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48

Sheng Chen, S. McLaughlin, B. Mulgrew, and P. M. Grant. "Adaptive Bayesian decision feedback equalizer for dispersive mobile radio channels." IEEE Transactions on Communications 43, no. 5 (May 1995): 1937–46. http://dx.doi.org/10.1109/26.387409.

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49

Mastan Sharif, SK, K. Satya Prasad, and D. Venkata Rao. "Adaptive decision feedback equalizer with dynamic principle for echo cancellation." Transactions of the Institute of Measurement and Control 40, no. 16 (March 26, 2018): 4455–71. http://dx.doi.org/10.1177/0142331218755233.

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Adaptive decision feedback equalizer (ADFE) based on Least Mean square algorithm (LMS) has emerged as a novel tool for signal propagation without noise. However, it has the limitation of computational complexity. Since it has been reported that substantial echo cancellation leads to increased system quality and capacity, this paper proposes a dynamic LMS-based ADFE (DLMS-ADFE) to cancel the generation of the echo signal. The DLMS-ADFE has two dynamic principles in updating the coefficients. The first principle has varying step-size and the second principle has varying degree and magnitude of the signal. The comparison results show that the DLMS-ADFE is outperforming LMS-ADFE.

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50

Keane, J. P., M. Q. Le, and P. J. Hurst. "Analog timing recovery for a noise-predictive decision-feedback equalizer." IEEE Journal of Solid-State Circuits 38, no. 2 (February 2003): 338–42. http://dx.doi.org/10.1109/jssc.2002.807171.

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