Relevant bibliographies by topics / Channel equalization

Academic literature on the topic 'Channel equalization'

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Published: 4 June 2021
Last updated: 28 January 2023

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Journal articles on the topic "Channel equalization"

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Dikhaminjia, Nana, Mikheil Tsiklauri, Zurab Kiguradze, Jiayi He, Arun Chada, Bhyrav Mutnury, and James L. Drewniak. "Analytical method for joint optimization of FFE and DFE equalizations for multi-level signals." Journal of Electrical Engineering 73, no. 4 (August 1, 2022): 284–91. http://dx.doi.org/10.2478/jee-2022-0037.

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Abstract Channel equalization is the efficient method for recovering distorted signal and correspondingly reducing bit error rate (BER). Different type of equalizations, like feed forward equalization (FFE) and decision feedback equalization (DFE) are canceling channel effect and recovering channel response. Separate optimization of tap coefficients for FFE and DFE does not give optimal result. In this case FFE and DFE tap coefficients are found separately and they are not collaborating. Therefore, the final equalization result is not global optimal. In the present paper new analytical method for finding best tap coefficients for FFE and DFE joint equalization is introduced. The proposed method can be used for both NRZ and PAM4 signals. The idea of the methodology is to combine FFE and DFE tap coefficients into one optimization problem and allow them to collaborate and lead to the global optimal solution. The proposed joint optimization method is fast, easy to implement and efficient. The method has been tested for several measured channels and the analysis of the results are discussed.
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Simerjeet Kaur, Dr Kamal Kumar Sharma, and Mr Navnidhi Sharma. "Literature Review on BER Improvement of Adaptive Equalizer." International Journal of Research in Informative Science Application & Techniques (IJRISAT) 3, no. 5 (May 15, 2019): 12–20. http://dx.doi.org/10.46828/ijrisat.v3i5.133.

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Channel equalization is an important aspect in high speed digital communication required for efficient and reliable data recovery and reception when the data is transmitted over band-limited channel subjected to noise and interference. We investigate channel equalization and introduce hierarchical and adaptive nonlinear channel equalization algorithms that are highly efficient and provide significantly improved bit error rate (BER) performance. Due to the high complexity of nonlinear equalizers and poor performance of linear ones, to equalize highly difficult channels, we employ piecewise linear equalizers.
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Litwin, L. R. "Blind channel equalization." IEEE Potentials 18, no. 4 (1999): 9–12. http://dx.doi.org/10.1109/45.796095.

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Panta, Jariya, Poompat Saengudomlert, and Keattisak Sripimanwat. "Performance Improvement of ACO-OFDM Indoor Optical Wireless Transmissions Using Partial Pre-Equalization." ECTI Transactions on Electrical Engineering, Electronics, and Communications 14, no. 1 (September 11, 2015): 1–11. http://dx.doi.org/10.37936/ecti-eec.2016141.171081.

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This paper analyzes the performances and presents the benets of partial pre-equalization for indoor optical wireless transmissions based on asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) with intensity modulation and direct detection (IM/DD). In particular, for diffuse indoor optical wireless channels, partial pre-equalization can reduce the optical transmit power over post-equalization at the same target bit error rate (BER) for point-to-point transmissions even with imperfect channel knowledge. To further im-prove its performance, bit loading is considered to minimize the optical transmit power of ACO-OFDM while maintaining a constant target BER. In addition, broadcast transmissions to multiple users with possibly dierent channel qualities are considered, where pre-equalization is not applicable. Finally, we specify an appropriate channel estimate at the transmitter for such broadcast transmissions.
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Liavas, A. P. "Least-squares channel equalization performance versus equalization delay." IEEE Transactions on Signal Processing 48, no. 6 (June 2000): 1832–35. http://dx.doi.org/10.1109/78.845949.

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Noori, Awab, Angela Amphawan, Alaan Ghazi, and S. A. Aljunid Ghazi. "Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexer for optical fiber transmission." Bulletin of Electrical Engineering and Informatics 8, no. 1 (March 1, 2019): 127–35. http://dx.doi.org/10.11591/eei.v8i1.1399.

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The performance of optical mode division multiplexer (MDM) is affected by inter-symbol interference (ISI), which arises from higher-order mode coupling and modal dispersion in multimode fiber (MMF). Existing equalization algorithms in MDM can mitigate linear channel impairments, but cannot tackle nonlinear channel impairments accurately. Therefore, mitigating the noise in the received signal of MDM in the presence of ISI to recover the transmitted signal is important issue. This paper aims at controlling the broadening of the signal from MDM and minimizing the undesirable noise among channels. A dynamic evolving neural fuzzy inference system (DENFIS) equalization scheme has been used to achieve this objective. Results illustrate that nonlinear DENFIS equalization scheme can improve the received distorted signal from an MDM with better accuracy than previous linear equalization schemes such as recursive‐least‐square (RLS) algorithm. Desirably, this effect allows faster data transmission rate in MDM. Additionally, the successful offline implementation of DENFIS equalization in MDM encourages future online implementation of DENFIS equalization in embedded optical systems.
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Shouyu, Sun. "Blind Adaptive Channel Equalization Using Modified CMA." Advanced Materials Research 658 (January 2013): 537–40. http://dx.doi.org/10.4028/www.scientific.net/amr.658.537.

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The constant modulus algorithm (CMA) equalizer is perhaps the best known and the most popular scheme for blind adaptive channel equalization. In this paper, a modified constant modulus algorithm (modified CMA or MCMA) is proposed by modifying its error function. We have discussed the MCMA to blind channel equalization for baud-rat sampling in single-user case. Computer simulations are provided for 8PSK signals in noise environments under frequency selective channels. Results demonstrate that the MCMA displays much superior performance to the CMA for both convergence-time and intersymbol interference (ISI) or mean square error (MSE).
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Wang, Xin, Zhe Jiang, and Xiao-Hong Shen. "Low Complexity Equalization of Orthogonal Chirp Division Multiplexing in Doubly-Selective Channels." Sensors 20, no. 11 (June 1, 2020): 3125. http://dx.doi.org/10.3390/s20113125.

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Orthogonal Chirp Division Multiplexing (OCDM) is a modulation scheme which outperforms the conventional Orthogonal Frequency Division Multiplexing (OFDM) under frequency selective channels by using chirp subcarriers. However, low complexity equalization algorithms for OCDM based systems under doubly selective channels have not been investigated yet. Moreover, in OCDM, the usage of different phase matrices in modulation will lead to extra storage overhead. In this paper, we investigate an OCDM based modulation scheme termed uniform phase-Orthogonal Chirp Division Multiplexing (UP-OCDM) for high-speed communication over doubly selective channels. With uniform phase matrices equipped, UP-OCDM can reduce the storage requirement of modulation. We also prove that like OCDM, the transform matrix of UP-OCDM is circulant. Based on the circulant transform matrix, we show that the channel matrices in UP-OCDM system over doubly selective channels have special structures that (1) the equivalent frequency-domain channel matrix can be approximated as a band matrix, and (2) the transform domain channel matrix in the framework of the basis expansion model (BEM) is a sum of the product of diagonal and circulant matrices. Based on these special channel structures, two low-complexity equalization algorithms are proposed for UP-OCDM in this paper. The equalization algorithms are based on block LDL H factorization and iterative matrix inversion, respectively. Numerical simulations are finally proposed to show the performance of UP-OCDM and the validity of the proposed low complexity equalization algorithms. It is shown that when the channel is doubly selective, UP-OCDM and OCDM have similar BER performance, and both of them outperform OFDM. Moreover, the proposed low complexity equalizers for UP-OCDM both show better BER performance than their OFDM counterparts.
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Wang, Liang, Peiyue Qiao, Junyan Liang, Tong Chen, Xinjie Wang, and Guang Yang. "Accurate Channel Estimation and Adaptive Underwater Acoustic Communications Based on Gaussian Likelihood and Constellation Aggregation." Sensors 22, no. 6 (March 10, 2022): 2142. http://dx.doi.org/10.3390/s22062142.

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Achieving accurate channel estimation and adaptive communications with moving transceivers is challenging due to rapid changes in the underwater acoustic channels. We achieve an accurate channel estimation of fast time-varying underwater acoustic channels by using the superimposed training scheme with a powerful channel estimation algorithm and turbo equalization, where the training sequence and the symbol sequence are linearly superimposed. To realize this, we develop a ‘global’ channel estimation algorithm based on Gaussian likelihood, where the channel correlation between (among) the segments is fully exploited by using the product of the Gaussian probability-density functions of the segments, thereby realizing an ideal channel estimation of each segment. Moreover, the Gaussian-likelihood-based channel estimation is embedded in turbo equalization, where the information exchange between the equalizer and the decoder is carried out in an iterative manner to achieve an accurate channel estimation of each segment. In addition, an adaptive communication algorithm based on constellation aggregation is proposed to resist the severe fast time-varying multipath interference and environmental noise, where the encoding rate is automatically determined for reliable underwater acoustic communications according to the constellation aggregation degree of equalization results. Field experiments with moving transceivers (the communication distance was approximately 5.5 km) were carried out in the Yellow Sea in 2021, and the experimental results verify the effectiveness of the two proposed algorithms.
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Wang, Laihe, Yueli Li, Wu Wang, and Daoxiang An. "Moving Target Indication for Dual-Channel Circular SAR/GMTI Systems." Sensors 20, no. 1 (December 25, 2019): 158. http://dx.doi.org/10.3390/s20010158.

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In a dual-channel circular synthetic aperture radar (CSAR) and ground moving target indication (GMTI) system, the antenna baseline is not parallel with the flight path due to a yaw angle. The angle causes a varying group-phase shift between the dual-channel signals and therefore degrades the correlation between the image pair. Therefore, the group-phase shift needs to be removed before channel equalization. To resolve the problem, the interferometric phase term was deduced and analyzed based on the geometry of a dual-channel CSAR system. Then, the varying phase term with respect to the Doppler frequency and the varying group-phase shift over the range were compensated for in the channel registration. Furthermore, blind channel equalization, including two-dimensional calibration and amplitude equalization, was applied to eliminate the amplitude and residual phase differences between the channels. Finally, the amplitude image obtained using a displaced phase center antenna (DPCA) was multiplied by the phase image obtained with along-track interferometry (ATI) to detect moving targets. The experimental results verified the effectiveness of the method for both uniform and non-uniform clutter suppression.
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Dissertations / Theses on the topic "Channel equalization"

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Shiao, Fu-Sheng. "Combined Channel Estimation and Turbo Equalization for Wireless Channels." Thesis, University of Canterbury. Electrical and Computer Engineering, 2007. http://hdl.handle.net/10092/1189.

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Single-carrier linear modulation techniques combined with frequency-domain equalization provide a viable alternative to multicarrier techniques for combating multipath fading in channels with large delay spread. Such modulations tolerate frequency offset and have well controlled peak to average power ratio. They have comparable complexity to orthogonal frequency division multiplexing (OFDM) systems, and are more robust to synchronization errors. If error correction coding is used, then information can be iteratively passed between the equalizer and the decoder to improve performance. This is referred to as turbo equalization. To date, several turbo equalization schemes have been proposed, but little work has been done to address the problem of channel estimation for the turbo equalization process. The work in this thesis considers frequency-domain turbo equalization with imperfect channel state information (CSI) at the receiver for different wireless channels. A receiver structure incorporating joint frequency-domain turbo equalization and time- domain channel estimation is developed. The novelty of this scheme lies in the combination of time-domain channel estimation and frequency-domain turbo equalization, and in its extension to high level modulation formats. The performance of the system is investigated by a combination of analysis and computer simulation. It is found that the system performs well over a range of dispersive channels.
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Lu, Biao. "Wireline channel estimation and equalization /." Full text (PDF) from UMI/Dissertation Abstracts International, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p3004324.

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Çiftçi, Mahmut. "Channel equalization for chaotic communications systems." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/15464.

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COSTA, BERNARDO RODRIGUES DA. "CHANNEL EQUALIZATION IN BLOCK TRANSMISSION SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=11845@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
A necessidade pela transmissão em altas taxas, por exemplo nos novos sistemas de TV Digital de alta definição, telefonia celular de terceira e quarta geração, DSL e etc, trazem consigo um problema: o aumento dos múltiplos percursos no canal de comunicações (principalmente nas interfaces áereas), dando origem ao fenômeno de interferência intersimbólica (IES). Este trabalho investiga o desempenho de sistemas de transmissão com uma única portadora (SC ou single-carrier) com equalização linear no domínio da freqüência. Diferentes algoritmos recursivos são apresentados para implementar estes filtros FIR. Além dos equalizadores lineares, uma estrutura não-linear é introduzida, onde decisões passadas do decisor de mínima distância são utilizadas para mitigar os efeitos da IES na detecção dos símbolos subseqüentes. Este arranjo é conhecido como equalização/filtragem com decisões realimentadas (DFE ou Decision Feedback Equalizers). Por último, os resultados obtidos com o sistema SC nas diferentes configurações de filtragem na recepção são comparados com os resultados do já estabelecido sistema OFDM. A transmissão OFDM se dá com múltiplas portadoras, onde as freqüências das sub-portadoras são ortogonais entre si, permitindo que a informação seja enviada de forma paralela. Resultados mostram que os sistemas SC-FDE tem desempenho superior aos sistemas OFDM.
The demand for high rate transmission systems, for example in HDTV, third and fourth generation cellular telephony, DSL and so on, causes the rise of a problem: The multipath communications channel (specially in wireless communications), which leads to intersymbol interference phenomenon (ISI). The present work investigates the performance of single-carrier (SC) transmission systems with frequency-domain linear equalization. Different recursive algorithms are presented in order to implement these FIR filters. Besides the linear equalizers, a non- linear structure is introduced, where the past decisions made by the detectors are used to mitigate the effect of ISI on the detection of the forthcoming symbols. This set is known as Decision Feedback Equalizers (DFE). Finally, the results of the aforementioned systems are compared to the well-known OFDM. OFDM transmission relies on sub-carriers, frequency orthogonal to each other, in which the data is sent in a parallel basis. The results obtained show that SC- FDE systems outperform OFDM systems.
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Gurrapu, Omprakash. "Adaptive filter algorithms for channel equalization." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-19219.

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Equalization techniques compensate for the time dispersion introduced bycommunication channels and combat the resulting inter-symbol interference (ISI) effect.Given a channel of unknown impulse response, the purpose of an adaptive equalizer is tooperate on the channel output such that the cascade connection of the channel and theequalizer provides an approximation to an ideal transmission medium. Typically,adaptive equalizers used in digital communications require an initial training period,during which a known data sequence is transmitted. A replica of this sequence is madeavailable at the receiver in proper synchronism with the transmitter, thereby making itpossible for adjustments to be made to the equalizer coefficients in accordance with theadaptive filtering algorithm employed in the equalizer design. This type of equalization isknown as Non-Blind equalization. However, in practical situations, it would be highlydesirable to achieve complete adaptation without access to a desired response. Clearly,some form of Blind equalization has to be built into the receiver design. Blind equalizerssimultaneously estimate the transmitted signal and the channel parameters, which mayeven be time-varying. The aim of the project is to study the performance of variousadaptive filter algorithms for blind channel equalization through computer simulations.
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Yao, Ning. "Iterative algorithms for channel estimation and equalization /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202005%20YAO.

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Mheidat, Hakam. "Channel Estimation and Equalization for Cooperative Communication." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2852.

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The revolutionary concept of space-time coding introduced in the last decade has demonstrated that the deployment of multiple antennas at the transmitter allows for simultaneous increase in throughput and reliability because of the additional degrees of freedom offered by the spatial dimension of the wireless channel. However, the use of antenna arrays is not practical for deployment in some practical scenarios, e. g. , sensor networks, due to space and power limitations.

A new form of realizing transmit diversity has been recently introduced under the name of user cooperation or cooperative diversity. The basic idea behind cooperative diversity rests on the observation that in a wireless environment, the signal transmitted by the source node is overheard by other nodes, which can be defined as "partners" or "relays". The source and its partners can jointly process and transmit their information, creating a "virtual antenna array" and therefore emulating transmit diversity.

Most of the ongoing research efforts in cooperative diversity assume frequency flat channels with perfect channel knowledge. However, in practical scenarios, e. g. broadband wireless networks, these assumptions do not apply. Frequency-selective fading and imperfect channel knowledge should be considered as a more realistic channel model. The development of equalization and channel estimation algorithms play a crucial element in the design of digital receivers as their accuracy determine the overall performance.

This dissertation creates a framework for designing and analyzing various time and frequency domain equalization schemes, i. e. distributed time reversal (D-TR) STBC, distributed single carrier frequency domain (D-SC-FDE) STBC, and distributed orthogonal frequency division multiplexing (D-OFDM) STBC schemes, for broadband cooperative communication systems. Exploiting the orthogonally embedded in D-STBCs, we were able to maintain low-decoding complexity for all underlying schemes, thus, making them excellent candidates for practical scenarios, such as multi-media broadband communication systems.

Furthermore, we propose and analyze various non-coherent and channel estimation algorithms to improve the quality and reliability of wireless communication networks. Specifically, we derive a non-coherent decoding rule which can be implemented in practice by a Viterbi-type algorithm. We demonstrate through the derivation of a pairwise error probability expression that the proposed non-coherent detector guarantees full diversity. Although this decoding rule has been derived assuming quasi-static channels, its inherent channel tracking capability allows its deployment over time-varying channels with a promising performance as a sub-optimal solution. As a possible alternative to non-coherent detection, we also investigate the performance of mismatched-coherent receiver, i. e. , coherent detection with imperfect channel estimation. Our performance analysis demonstrates that the mismatched-coherent receiver is able to collect the full diversity as its non-coherent competitor over quasi-static channels.

Finally, we investigate and analyze the effect of multiple antennas deployment at the cooperating terminals assuming different relaying techniques. We derive pairwise error probability expressions quantifying analytically the impact of multiple antenna deployment at the source, relay and/or destination terminals on the diversity order for each of the relaying methods under consideration.
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Jalali, Sammuel. "Wireless Channel Equalization in Digital Communication Systems." Scholarship @ Claremont, 2012. http://scholarship.claremont.edu/cgu_etd/42.

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Our modern society has transformed to an information-demanding system, seeking voice, video, and data in quantities that could not be imagined even a decade ago. The mobility of communicators has added more challenges. One of the new challenges is to conceive highly reliable and fast communication system unaffected by the problems caused in the multipath fading wireless channels. Our quest is to remove one of the obstacles in the way of achieving ultimately fast and reliable wireless digital communication, namely Inter-Symbol Interference (ISI), the intensity of which makes the channel noise inconsequential. The theoretical background for wireless channels modeling and adaptive signal processing are covered in first two chapters of dissertation. The approach of this thesis is not based on one methodology but several algorithms and configurations that are proposed and examined to fight the ISI problem. There are two main categories of channel equalization techniques, supervised (training) and blind unsupervised (blind) modes. We have studied the application of a new and specially modified neural network requiring very short training period for the proper channel equalization in supervised mode. The promising performance in the graphs for this network is presented in chapter 4. For blind modes two distinctive methodologies are presented and studied. Chapter 3 covers the concept of multiple "cooperative" algorithms for the cases of two and three cooperative algorithms. The "select absolutely larger equalized signal" and "majority vote" methods have been used in 2-and 3-algoirithm systems respectively. Many of the demonstrated results are encouraging for further research. Chapter 5 involves the application of general concept of simulated annealing in blind mode equalization. A limited strategy of constant annealing noise is experimented for testing the simple algorithms used in multiple systems. Convergence to local stationary points of the cost function in parameter space is clearly demonstrated and that justifies the use of additional noise. The capability of the adding the random noise to release the algorithm from the local traps is established in several cases.
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Barron, Richard J. (Richard John). "Channel equalization for self-synchronizing chaotic systems." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/38828.

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Song, Liying Tugnait Jitendra K. "Channel estimation and equalization for doubly-selective channels using basis expansion models." Auburn, Ala, 2008. http://repo.lib.auburn.edu/EtdRoot/2008/SPRING/Electrical_and_Computer_Engineering/Dissertation/Song_Liying_29.pdf.

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Books on the topic "Channel equalization"

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Bottomley, Gregory E. Channel Equalization for Wireless Communications. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118105283.

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Zhang, Wen Pian Paul. Transmitter-induced cyclostationarity for blind channel identification and equalization. Ottawa: National Library of Canada, 2000.

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Jiang, Yufei, Xu Zhu, Eng Gee Lim, Yi Huang, and Hai Lin. Semi-Blind Carrier Frequency Offset Estimation and Channel Equalization. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24984-1.

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Channel equalization for wireless communicatinos: From concepts to detailed mathematics. Piscatawsay, NJ: IEEE Press, 2011.

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Holden, Michael. Equalization: Implications of recent changes. Ottawa, Ont: Library of Parliament, 2006.

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Tse, Eloise. Blind equalization with differential detection for channels with ISI and fading. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1999.

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Lam, Stephen Wai-Bun. Sub-optimal equalizations of differentially detected PSK in fading channels. Ottawa: National Library of Canada, 2000.

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Gutiérrez, Alberto. Equalization and detection for digital communication over nonlinear bandlimited satellite communication channels. Las Cruces, N.M: New Mexico State University, 1995.

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Alberto, Gutiérrez. Equalization and detection for digital communication over nonlinear bandlimited satellite communication channels. Las Cruces, N.M: New Mexico State University, 1995.

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Sandoval, Luis Alberto Ortiz. Educación y desigualdad: Las clases desfavorecidas ante el sistema educativo paraguayo. Asunción, Paraguay: Centro de Estudios Antropológicos de la Universidad Católica (CEADUC), 2012.

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Book chapters on the topic "Channel equalization"

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Papagiannakis, Ioannis, G. Bosco, Daniel Fonseca, Dimitrios Klonidis, P. Poggiolini, Werner Rosenkranz, Antonio Luis Jesus Teixeira, Ioannis Tomkos, and Chunmin Xia. "Electronic Channel Equalization Techniques." In Towards Digital Optical Networks, 23–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01524-3_3.

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Kirkland, William R., and D. P. Taylor. "Neural Network Channel Equalization." In Neural Networks in Telecommunications, 143–71. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2734-3_8.

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Prasad, Ramjee, Muhammad Imadur Rahman, Suvra Sekhar Das, and Nicola Marchetti. "Channel Estimation and Equalization." In Single- And Multi-Carrier Mimo Transmission for Broadband Wireless Systems, 151–72. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339533-7.

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Cid-Sueiro, Jesús, and Aníbal R. Figueiras-Vidal. "Channel Equalization with Neural Networks." In Digital Signal Processing in Telecommunications, 257–312. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1019-4_6.

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Proakis, John G. "Adaptive Algorithms for Blind Channel Equalization." In Linear Algebra for Signal Processing, 139–51. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-4228-4_8.

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Park, Hyung-Min, Sang-Hoon Oh, and Soo-Young Lee. "Blind Equalization Using Direct Channel Estimation." In Independent Component Analysis and Blind Signal Separation, 562–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30110-3_72.

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Cantoni, A., B. Vo, Z. Zang, and K. L. Teo. "Analog Envelope Constrained Filters for Channel Equalization." In Information Technology: Transmission, Processing and Storage, 397–408. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1013-2_31.

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Broeck, Isabella, Marco Kullmann, and Uli Sorger. "Reduced State Joint Channel Estimation and Equalization." In Multi-Carrier Spread Spectrum & Related Topics, 287–94. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4463-0_33.

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Harrington, Edward. "Expert Mixture Methods for Adaptive Channel Equalization." In Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003, 538–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44989-2_64.

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Panazio, Cristiano M., Aline O. Neves, Renato R. Lopes, and Joao M. T. Romano. "Channel Equalization Techniques for Wireless Communications Systems." In Optimizing Wireless Communication Systems, 311–52. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0155-2_8.

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Conference papers on the topic "Channel equalization"

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Singh, Harmandeep, and S. S. Gill. "Approaches to Channel Equalization." In Communication Technologies (ACCT). IEEE, 2012. http://dx.doi.org/10.1109/acct.2012.31.

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Venkataramani, Raman, and Sundararajan Sankaranarayanan. "Optimal Channel Shortening Equalization for MIMO ISI Channels." In IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference. IEEE, 2008. http://dx.doi.org/10.1109/glocom.2008.ecp.638.

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Shaheem, Asri, Hans-Jurgen Zepernick, and Manora Caldera. "Enhanced channel shortened turbo equalization." In 2008 International Conference on Advanced Technologies for Communications (ATC). IEEE, 2008. http://dx.doi.org/10.1109/atc.2008.4760506.

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Burns, Vaidyanathan, Gay-Bellile, and Marchal. "Array processing for channel equalization." In IEEE International Conference on Acoustics Speech and Signal Processing ICASSP-02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.1005368.

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5

Burns, G., K. Vaidyanathan, O. Gay-Bellile, and X. Marchal. "Array processing for channel equalization." In Proceedings of ICASSP '02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.5745330.

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Li, Wenliang, Shanxiang Mu, and Feng Liu. "Channel equalization based convex optimization." In 2015 International Conference on Wireless Communications & Signal Processing (WCSP). IEEE, 2015. http://dx.doi.org/10.1109/wcsp.2015.7341262.

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Shiao, Fu-Sheng, Desmond P. Taylor, and Philippa A. Martin. "Combined Channel Estimation and Turbo Equalization on Wireless Channels." In 2008 IEEE 68th Vehicular Technology Conference (VTC 2008-Fall). IEEE, 2008. http://dx.doi.org/10.1109/vetecf.2008.179.

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Guha, Devi Rani, and Sarat Kumar Patra. "Channel equalization for ISI channels using Wilcoxon generalized RBF." In 2009 International Conference on Industrial and Information Systems (ICIIS). IEEE, 2009. http://dx.doi.org/10.1109/iciinfs.2009.5429878.

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Dong, Liang. "Turbo Equalization with Channel Prediction and Iterative Channel Estimation." In 2009 IEEE Wireless Communications and Networking Conference. IEEE, 2009. http://dx.doi.org/10.1109/wcnc.2009.4918006.

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10

Baig, Sobia, and Fazal-ur-Rehman. "Frequency Domain Channel Equalization Using Circulant Channel Matrix Diagonalization." In 2005 Pakistan Section Multitopic Conference. IEEE, 2005. http://dx.doi.org/10.1109/inmic.2005.334413.

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Reports on the topic "Channel equalization"

1

Barnett, S. J. Multiple-Channel Equalization of a Nearfield Sonar System. Fort Belvoir, VA: Defense Technical Information Center, February 1994. http://dx.doi.org/10.21236/ada276711.

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