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Journal articles on the topic 'Intersymbol Interference'

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Published: 4 June 2021
Last updated: 29 January 2023

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1

Crotty, Patrick, and William B. Levy. "Intersymbol interference in axonal transmission." Neurocomputing 69, no. 10-12 (June 2006): 1006–9. http://dx.doi.org/10.1016/j.neucom.2005.12.034.

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2

Huleihel, Wasim, Salman Salamatian, Neri Merhav, and Muriel Medard. "Gaussian Intersymbol Interference Channels With Mismatch." IEEE Transactions on Information Theory 65, no. 7 (July 2019): 4499–517. http://dx.doi.org/10.1109/tit.2019.2900222.

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3

Franck, T., P. B. Hansen, T. N. Nielsen, and L. Eskildsen. "Duobinary transmitter with low intersymbol interference." IEEE Photonics Technology Letters 10, no. 4 (April 1998): 597–99. http://dx.doi.org/10.1109/68.662606.

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4

Huang, Cui Cui, Liang Jun Yu, and Li Hua Sun. "Design of Mobile Communication Non Intersymbol Interference System Based on Calman Filter and PID Control." Applied Mechanics and Materials 716-717 (December 2014): 1257–61. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.1257.

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In the digital baseband transmission system, the intersymbol interference is one of the main factors affecting the performance. Therefore, how to overcome its influence, making the system error rate reduction must study and solve the problems in the digital baseband system. This paper designs a new mobile communication non intersymbol interference filtering system based on MATLAB numerical simulation, the system is the integration of the Calman filter theory, and combining the genetic algorithm and PID control algorithm to achieve the rapidity and stability of the system filter. The filter design and validation simulation can be seen that the filter can effectively eliminate the measurement and observation error in the mobile communication process, to avoid the signal fluctuation caused by intersymbol interference. Through the system response curve, it can be seen that the system does not appear overshoot, fast convergence speed, and good response stability will provide the technical reference for the research of mobile communication system.
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5

Metzger, K. "On the Probability Density of Intersymbol Interference." IEEE Transactions on Communications 35, no. 4 (1987): 396–402. http://dx.doi.org/10.1109/tcom.1987.1096789.

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6

Huleihel, Wasim, and Neri Merhav. "Universal Decoding for Gaussian Intersymbol Interference Channels." IEEE Transactions on Information Theory 61, no. 4 (April 2015): 1606–18. http://dx.doi.org/10.1109/tit.2015.2405534.

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7

Bayat, Oguz. "Intersymbol interference cancellation in CDMA 1xEVDO network." International Journal of Communication Systems 27, no. 10 (September 25, 2012): 1553–60. http://dx.doi.org/10.1002/dac.2418.

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8

Zhao, Hongxia, Erik Agrell, and Magnus Karlsson. "Intersymbol interference in DQPSK fibre-optic systems." European Transactions on Telecommunications 20, no. 8 (December 2009): 758–69. http://dx.doi.org/10.1002/ett.1354.

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9

Douillard, Catherine, Michel Jézéquel, Claude Berrou, Département Electronique, Annie Picart, Pierre Didier, and Alain Glavieux. "Iterative correction of intersymbol interference: Turbo-equalization." European Transactions on Telecommunications 6, no. 5 (September 1995): 507–11. http://dx.doi.org/10.1002/ett.4460060506.

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10

SUZUKI, Toshiaki, and Toshiyuki TANAKA. "Study on Canceling Intersymbol Interference of Inverse-GPS." Transactions of the Society of Instrument and Control Engineers 39, no. 7 (2003): 694–96. http://dx.doi.org/10.9746/sicetr1965.39.694.

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11

Yellia, D., A. Vardy, and O. Amrani. "Joint equalization and coding for intersymbol interference channels." IEEE Transactions on Information Theory 43, no. 2 (March 1997): 409–25. http://dx.doi.org/10.1109/18.556102.

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12

Helstrom, C. "Calculating Error Probabilities for Intersymbol and Cochannel Interference." IEEE Transactions on Communications 34, no. 5 (May 1986): 430–35. http://dx.doi.org/10.1109/tcom.1986.1096562.

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13

Metzger, K., and R. Valentin. "Intersymbol interference due to linear and nonlinear distortion." IEEE Transactions on Communications 44, no. 7 (July 1996): 809–16. http://dx.doi.org/10.1109/26.508300.

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14

Doan, D. N., and K. R. Narayanan. "Iterative packet combining schemes for intersymbol interference channels." IEEE Transactions on Communications 50, no. 4 (April 2002): 560–70. http://dx.doi.org/10.1109/26.996070.

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15

Xie, Zedong, Xihong Chen, Xiaopeng Liu, and Yu Zhao. "MMSE-NP-RISIC-Based Channel Equalization for MIMO-SC-FDE Troposcatter Communication Systems." Mathematical Problems in Engineering 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/5158406.

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The impact of intersymbol interference (ISI) on single-carrier frequency-domain equalization with multiple input multiple output (MIMO-SC-FDE) troposcatter communication systems is severe. Most of the channel equalization methods fail to solve it completely. In this paper, given the disadvantages of the noise-predictive (NP) MMSE-based and the residual intersymbol interference cancellation (RISIC) equalization in the single input single output (SISO) system, we focus on the combination of both equalization schemes mentioned above. After extending both of them into MIMO system for the first time, we introduce a novel MMSE-NP-RISIC equalization method for MIMO-SC-FDE troposcatter communication systems. Analysis and simulation results validate the performance of the proposed method in time-varying frequency-selective troposcatter channel at an acceptable computational complexity cost.
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16

Golani, Ori, Daniel Elson, Domaniç Lavery, Lidia Galdino, Robert Killey, Polina Bayvel, and Mark Shtaif. "Experimental characterization of nonlinear interference noise as a process of intersymbol interference." Optics Letters 43, no. 5 (February 28, 2018): 1123. http://dx.doi.org/10.1364/ol.43.001123.

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17

Degtyaryov, Andrey. "The criterion for the existence of the weight of the orthogonality of equidistant elementary signals." ITM Web of Conferences 30 (2019): 04015. http://dx.doi.org/10.1051/itmconf/20193004015.

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To reduce the level of intersymbol interference and interchannel interference, it is proposed to form the transmitted signals using the basis functions obtained by shifting the impulse responses of linear systems by multiple time intervals. An algorithm for calculating the weight of the orthogonality of basis functions is proposed. A criterion for the existence of the indicated weight of orthogonality is formulated.
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18

Zorba, Nizar, and Faouzi Bader. "Spatial Diversity Scheme to Efficiently Cancel ISI and ICI in OFDM-OQAM Systems." Journal of Computer Systems, Networks, and Communications 2010 (2010): 1–10. http://dx.doi.org/10.1155/2010/576243.

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This paper is based on an Offset Quadrature Amplitude Modulation (OQAM) Orthogonal Frequency Division Multiplexing (OFDM) transmission scheme that is operated without a Cyclic Prefix (CP), where the multiple transmitting antennas are employed to substantially reduce the inherent intersymbol and intercarrier interference. The proposed scheme avoids the use of the CDMA technology to get rid of the interference. The nonemployment of the CP increases the spectral efficiency in comparison with classical CP-OFDM systems, as it does not employ the CP for its correct performance. On the other hand, the non-employment of the CP comes at cost of Intersymbol Interference (ISI). This paper presents a method which cancels the interference terms by employing a multiantenna precoding strategy based on spatial diversity OQAM-OFDM scheme, so that the overall system can get the advantage of the CP removal while no ISI is generated. Moreover, the proposed system benefits from the multiuser gain through an opportunistic scheduler at the transmitter side to select the user with the best channel characteristics at each instant. The resultant scheme OQAM-OFDM-MIMO data rate is obtained in a closed form expression and proved to be higher than the classical CP-OFDM systems.
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19

Jeong, Seongkwon, and Jaejin Lee. "Two Dimensional Intersymbol Interference Compensation for Bit Patterned Media." Journal of the Institute of Electronics and Information Engineers 52, no. 6 (June 25, 2015): 15–20. http://dx.doi.org/10.5573/ieie.2015.52.6.015.

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20

Duman, Tolga M., and Milica Stojanovic. "Information Rates of Energy Harvesting Communications With Intersymbol Interference." IEEE Communications Letters 23, no. 12 (December 2019): 2164–67. http://dx.doi.org/10.1109/lcomm.2019.2945766.

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21

Yunxin Li, B. Vucetic, and Y. Sato. "Optimum soft-output detection for channels with intersymbol interference." IEEE Transactions on Information Theory 41, no. 3 (May 1995): 704–13. http://dx.doi.org/10.1109/18.382016.

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22

Laroia, R. "Coding for intersymbol interference channels-combined coding and precoding." IEEE Transactions on Information Theory 42, no. 4 (July 1996): 1053–61. http://dx.doi.org/10.1109/18.508832.

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23

Karabed, R., P. H. Siegel, and E. Soljanin. "Constrained coding for binary channels with high intersymbol interference." IEEE Transactions on Information Theory 45, no. 6 (1999): 1777–97. http://dx.doi.org/10.1109/18.782099.

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24

Zamkotsian, Martin, Kostas P. Peppas, F. Lazarakis, and Panayotis G. Cottis. "Layered Offset Hierarchical QAM Modulation for Intersymbol Interference Reduction." IEEE Communications Letters 17, no. 11 (November 2013): 2176–79. http://dx.doi.org/10.1109/lcomm.2013.091213.131697.

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25

Cryan, R. A., and M. J. N. Sibley. "Minimising intersymbol interference in optical-fibre dicode PPM systems." IEE Proceedings - Optoelectronics 153, no. 3 (June 1, 2006): 93–100. http://dx.doi.org/10.1049/ip-opt:20050028.

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26

Lin, Shou-Sheu, and Wen-Rong Wu. "Interpolated decision feedback equalization for long intersymbol interference channels." Signal Processing 87, no. 11 (November 2007): 2673–85. http://dx.doi.org/10.1016/j.sigpro.2007.04.020.

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27

Oehme, W. F., and K. Enk. "A two step detection scheme for high intersymbol interference." IEEE Transactions on Magnetics 30, no. 2 (March 1994): 948–50. http://dx.doi.org/10.1109/20.312455.

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28

KURKOSKI, B. M. "Towards Efficient Detection of Two-Dimensional Intersymbol Interference Channels." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E91-A, no. 10 (October 1, 2008): 2696–703. http://dx.doi.org/10.1093/ietfec/e91-a.10.2696.

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29

Stoica, Petre, and Erik Lindskog. "Space–Time Block Coding for Channels with Intersymbol Interference." Digital Signal Processing 12, no. 4 (October 2002): 616–27. http://dx.doi.org/10.1006/dspr.2001.0418.

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30

Sastry, K. Seshadri, K. Baburao, A. V. Prabu, and G. Naveen Kumar. "Comparison of SPS and FA methods for Blind Carrier Frequency Offset Estimation in OFDM systems." International Journal of Mathematical Models and Methods in Applied Sciences 16 (January 10, 2022): 7–11. http://dx.doi.org/10.46300/9101.2022.16.2.

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In orthogonal frequency-division multiplexing (OFDM) systems, synchronization issues are of great importance since synchronization errors might destroy the orthogonality among all subcarriers and, therefore, introduce intercarrier interference (ICI) and intersymbol interference (ISI). Several schemes of frequency offset estimation in OFDM systems have been investigated. This paper compares performance and computational complexity of Smoothing Power Spectrum (SPS) and Frequency Analysis (FA) methods for blind carrier frequency offset (CFO) estimation in OFDM systems.
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31

DEGTYAREV, ANDREY N., ALEXANDER S. KOZHEMYAKIN, IGOR L. AFONIN, GENNADY V. SLEZKIN, and ALEXANDER L. POLYAKOV. "TWO-STAGE ALGORITHM FOR CONSISTENT SIGNALS FILTERING." H&ES Research 14, no. 3 (2022): 32–38. http://dx.doi.org/10.36724/2409-5419-2022-14-3-32-38.

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Introduction. Introduction. To combat inter-symbol interference resulting from multipath signal propagation, spreading of the signal frequency spectrum, channel equalizing, OFDM-multiplexing with orthogonal frequency division of channels is used. To reduce the influence of non-linear signal distortions, methods of pre-distortion, diversity reception, as well as special algorithms for digital processing of the demodulator output signal are used. The effect of additive noise is reduced by using a filter matched to the signal. Objective. It is advisable to develop a matched filtering algorithm that allows one to simultaneously reduce the influence of additive noise, non-linear signal distortions and its multipath propagation on the correct message reception. The idea of selecting the orthogonality weight can also be used to achieve the goal. Result. To reduce the influence of non-linear distortions on the correct reception of a message under conditions of multipath signal propagation and additive interference, it is proposed to use two stages of signal processing. The first step is to minimize the noise dispersion caused by intersymbol interference and non-linear signal distortions. The specified dispersion is minimized by determining the orthogonality weight of the basis-functions that make up the signal. The second step is to use a classic matched filter. The proposed two-stage matched filtering algorithm makes it possible to simultaneously reduce the influence of non-linear distortions, intersymbol interference resulting from multipath propagation, and additive interference on the correct signal reception. Signals distorted and delayed in time relative to the main signal are proposed to be considered as additive interference.
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32

YOON, Taeung, Youngpo LEE, So Ryoung PARK, Suk Chan KIM, Iickho SONG, and Seokho YOON. "Analysis of Intersymbol Interference due to Overlap in DM-BPSK." IEICE Transactions on Communications E93-B, no. 5 (2010): 1310–12. http://dx.doi.org/10.1587/transcom.e93.b.1310.

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33

Lu, Ying, Quan Yuan Xu, and Zhi Gang Liu. "Realization of the Viterbi Algorithm in MLSE with Intersymbol Interference." Applied Mechanics and Materials 214 (November 2012): 208–12. http://dx.doi.org/10.4028/www.scientific.net/amm.214.208.

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Optimum receiver model for channels with Intersymbol Interference (ISI) and Additive White Gaussian Noise (AWGN) are introduced to deduce the Viterbi algorithm in the Maximum-Likelihood Sequence Estimation (MLSE). Finally, we use Matlab to simulate the algorithm in three different channels and analyze the experiment results. Analyses show that the Viterbi algorithm is applicable for any channel which is optimum from a probability of error viewpoint; the MLSE for channels with ISI has a computational complexity that grows exponentially with the length of channels time dispersion L; the loss of performance is negligible when the decoding delay achieves 5L.
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34

Pechetti, Sasi Vinay, and Ranjan Bose. "Channel-Aware Artificial Intersymbol Interference for Enhancing Physical Layer Security." IEEE Communications Letters 23, no. 7 (July 2019): 1182–85. http://dx.doi.org/10.1109/lcomm.2019.2915076.

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35

Smith, W. S., P. H. Wittke, and L. L. Campbell. "Error probabilities on fading channels with intersymbol interference and noise." IEEE Transactions on Information Theory 39, no. 5 (1993): 1598–607. http://dx.doi.org/10.1109/18.259643.

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36

Balachandran, K., and J. B. Anderson. "Reduced complexity sequence detection for nonminimum phase intersymbol interference channels." IEEE Transactions on Information Theory 43, no. 1 (1997): 275–80. http://dx.doi.org/10.1109/18.567703.

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37

Hirt, W., and J. L. Massey. "Capacity of the discrete-time Gaussian channel with intersymbol interference." IEEE Transactions on Information Theory 34, no. 3 (May 1988): 38. http://dx.doi.org/10.1109/18.6015.

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38

Masamura, T. "Intersymbol interference reduction for differential MSK by nonredundant error correction." IEEE Transactions on Vehicular Technology 39, no. 1 (1990): 27–36. http://dx.doi.org/10.1109/25.54953.

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39

Beaulieu, N. C. "The evaluation of error probabilities for intersymbol and cochannel interference." IEEE Transactions on Communications 39, no. 12 (December 1991): 1740–49. http://dx.doi.org/10.1109/26.120161.

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40

Xiong, F., Q. Dai, and E. Shwedyk. "Computational complexity of sequential sequence estimation for intersymbol interference channels." IEEE Transactions on Communications 41, no. 2 (1993): 332–37. http://dx.doi.org/10.1109/26.216508.

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41

Fuqin Xiong. "Sequential decoding of convolutional codes in channels with intersymbol interference." IEEE Transactions on Communications 43, no. 2/3/4 (February 1995): 828–36. http://dx.doi.org/10.1109/26.380115.

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42

Carlisle, C. J., D. P. Taylor, W. K. Kennedy, and M. Shafi. "The probability density of intersymbol interference for trellis-coded modulation." IEEE Transactions on Communications 43, no. 1 (1995): 44–51. http://dx.doi.org/10.1109/26.385943.

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43

Levy, A. "Fast Error Rate Evaluation in the Presence of Intersymbol Interference." IEEE Transactions on Communications 33, no. 5 (May 1985): 479–81. http://dx.doi.org/10.1109/tcom.1985.1096323.

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44

Van Beneden, S., J. Riani, J. W. M. Bergmans, and A. H. J. Immink. "Cancellation of linear intersymbol interference for two-dimensional storage systems." IEEE Transactions on Magnetics 42, no. 8 (August 2006): 2096–106. http://dx.doi.org/10.1109/tmag.2006.876972.

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45

Huber, K. "A design method for pulseshaping filters having small intersymbol interference." IEEE Transactions on Circuits and Systems 34, no. 9 (September 1987): 1137–38. http://dx.doi.org/10.1109/tcs.1987.1086257.

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46

Fischer, R. F. H., and C. Siegl. "Lattice-reduction-aided equalisation for transmission over intersymbol-interference channels." Electronics Letters 41, no. 17 (2005): 969. http://dx.doi.org/10.1049/el:20051526.

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47

Kong, Lingjun, Yunxiang Jiang, Guojun Han, Francis C. M. Lau, and Yong Liang Guan. "Improved Min-Sum Decoding for 2-D Intersymbol Interference Channels." IEEE Transactions on Magnetics 50, no. 11 (November 2014): 1–4. http://dx.doi.org/10.1109/tmag.2014.2317749.

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48

Heanue, John F., Korhan Gürkan, and Lambertus Hesselink. "Signal detection for page-access optical memories with intersymbol interference." Applied Optics 35, no. 14 (May 10, 1996): 2431. http://dx.doi.org/10.1364/ao.35.002431.

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49

Peng, Rong-Hui, Rong-Rong Chen, and Behrouz Farhang-Boroujeny. "Markov Chain Monte Carlo Detectors for Channels With Intersymbol Interference." IEEE Transactions on Signal Processing 58, no. 4 (April 2010): 2206–17. http://dx.doi.org/10.1109/tsp.2009.2038958.

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50

Ying Zhu, Taikun Cheng, K. Sivakumar, and B. J. Belzer. "Markov Random Field Detection on Two-Dimensional Intersymbol Interference Channels." IEEE Transactions on Signal Processing 56, no. 7 (July 2008): 2639–48. http://dx.doi.org/10.1109/tsp.2008.917344.

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