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Journal articles on the topic 'Channel equalization'

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Author: Grafiati

Published: 4 June 2021

Last updated: 28 January 2023

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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11

Laot, C., A. Glavieux, and J. Labat. "Turbo equalization: adaptive equalization and channel decoding jointly optimized." IEEE Journal on Selected Areas in Communications 19, no. 9 (2001): 1744–52. http://dx.doi.org/10.1109/49.947038.

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12

Manhas, Pratima, and M. K. Soni. "Comparison of various channel equalization techniques in OFDM system using different digital modulations." Indonesian Journal of Electrical Engineering and Computer Science 3, no. 3 (September 1, 2016): 634. http://dx.doi.org/10.11591/ijeecs.v3.i3.pp634-638.

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<p>The nature of future wireless applications requires high data rates and for this OFDM technique is used. OFDM stands for orthogonal frequency division multiplexing and is a type of multi-carrier transmission where all the subcarriers are orthogonal to each other. At high data rates, the channel distortion to the data is very important and it is somewhat impossible to recover the transmitted data with a simple receiver. So a complex receiver structure is needed which uses computationally expensive equalization and channel estimation algorithms to estimate the channel. These estimations can be used within the received data to recover the originally transmitted data. OFDM can simplify the equalization problem by changing the frequency-selective channel into a flat channel. The radio channels in mobile radio systems are usually multipath fading channels that results in intersymbol interference (ISI) in the received signal. To remove ISI from the signal, many kind of equalizers can be used. The need for equalizers arises from the fact that the channel has amplitude and phase dispersion which results in the interference of the transmitted signals with one another which is known as ISI .So, to solve this problem equalizers are designed. Equalizer is intend to work in such a way that Bit Error Rate (BER) should be low and Signal-to-Noise Ratio (SNR) should be high. An equalizer within a receiver compensates for the average range of expected channel amplitude and delay characteristics. This paper deals with the various equalization techniques (LMS, RLS and CMA) used for OFDM system .A comparative analysis of different equalization technique in terms of BER is done using MATLAB Simulink.</p>

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13

Hassan, Shahzad, Noshaba Tariq, Rizwan Ali Naqvi, Ateeq Ur Rehman, and Mohammed K. A. Kaabar. "Performance Evaluation of Machine Learning-Based Channel Equalization Techniques: New Trends and Challenges." Journal of Sensors 2022 (January 6, 2022): 1–14. http://dx.doi.org/10.1155/2022/2053086.

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Wireless communication systems have evolved and offered more smart and advanced systems like ad hoc and sensor-based infrastructure fewer networks. These networks are evaluated with two fundamental parameters including data rate and spectral efficiency. To achieve a high data rate and robust wireless communication, the most significant task is channel equalization at the receiver side. The transmitted data symbols when passing through the wireless channel suffer from various types of impairments, such as fading, Doppler shifts, and Intersymbol Interference (ISI), and degraded the overall network performance. To mitigate channel-related impairments, many channel equalization algorithms have been proposed for communication systems. The channel equalization problem can also be solved as a classification problem by using Machine Learning (ML) methods. In this paper, channel equalization is performed by using ML techniques in terms of Bit Error Rate (BER) analysis and comparison. Radial Basis Functions (RBFs), Multilayer Perceptron (MLP), Support Vector Machines (SVM), Functional Link Artificial Neural Network (FLANN), Long-Short Term Memory (LSTM), and Polynomial-based Neural Networks (NNs) are adopted for channel equalization.

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14

Bastian, Jose Ambrosio, Mariko Nakano Miyatake, and Hector Manuel Perez-Meana. "Neurofuzzy Algorithm For Channel Equalization." Telecommunications and Radio Engineering 56, no. 4-5 (2001): 10. http://dx.doi.org/10.1615/telecomradeng.v56.i4-5.130.

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15

Sarangi, Archana, Bijay Ketan Panigrahi, and Siba Prasada Panigrahi. "Evolutionary MPNN for Channel Equalization." Journal of Signal and Information Processing 02, no. 01 (2011): 11–17. http://dx.doi.org/10.4236/jsip.2011.21002.

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16

Orozco-lugo, Aldo, Giselle Galvan-tejada, Mauricio Lara, and Valeri Kontorovitch. "Noncoherent channel equalization for DDPSK." IEEE Transactions on Wireless Communications 6, no. 1 (January 2007): 269–81. http://dx.doi.org/10.1109/twc.2007.05166.

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17

Liu, Ruey-wen. "Direct multiple-channel blind equalization." Circuits System and Signal Processing 17, no. 1 (January 1998): 117–22. http://dx.doi.org/10.1007/bf01213973.

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18

Elkassimi, Said, Said Safi, and B. Manaut. "Blind Channel Estimation and Equalization." International Journal of Multimedia and Ubiquitous Engineering 11, no. 12 (December 31, 2016): 191–206. http://dx.doi.org/10.14257/ijmue.2016.11.12.18.

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19

Gracias, S., and V. U. Reddy. "Wavelet packet based channel equalization." Sadhana 21, no. 1 (February 1996): 75–89. http://dx.doi.org/10.1007/bf02781789.

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20

Lu, Jiazhong, Xiaolei Liu, Teng Hu, Jianwei Zhang, and Xiaosong Zhang. "Network Intrusion Feature Map Node Equalization Algorithm Based on Modified Variable Step-Size Constant Modulus." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 14 (May 8, 2019): 1955015. http://dx.doi.org/10.1142/s0218001419550152.

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When the network is subject to intrusion and attack, the node output channel equalization will be affected, resulting in bit error and distortion in the output of network transmission symbols. In order to improve the anti-attack ability and equalization of network node, a network intrusion feature map node equalization algorithm based on modified variable step-size constant modulus blind equalization algorithm (MISO-VSS-MCMA) is proposed. In this algorithm, the node transmission channel model after network intrusion is constructed, and sequential processing is performed to intruded nodes with the variable structure feedback link control method. With diversity spread spectrum technology, the channel loss after network intrusion is compensated and the network intrusion map feature is extracted. According to the extracted feature amount, channel equalization processing is performed for the cost function with the MISO-VSS-MCMA method to reduce the damage of network intrusion to the channel. Simulation results show that in node transmission channel equalization after network intrusion, this algorithm can reduce the error bit rate of signal transmission in network, and provide a good ability of correcting phase deflection in the output constellation, thus avoiding the error bit distortion and channel damage caused by network intrusion to the signal with a good equalization effect. This algorithm provides stronger convergence and map concentration, which demonstrates that its anti-interference and signal recovery capabilities are better, so it improves the anti-attack ability of the network.

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Sen Gupta, Ananya, Nathan Kofron, and Eva Riherd. "Recent results in shallow water acoustic channel estimation and equalization." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A40. http://dx.doi.org/10.1121/10.0015469.

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Shallow water acoustic channel estimation and equalization has been widely studied and explored across the last three decades, with several techniques being proposed that account for the rapidly time-varying nature of the channel. Despite advances in integrating robust channel equalization techniques with channel estimation, incorporating well-known models of acoustic propagation into the equalization setup has been hard. In this work, we will present some of our recent explorations in this regard involving a hybrid setting as well as a model-based simulation to test the performance of simple equalization schemes under a variety of channel conditions. The shallow water acoustic channel is first estimated from experimental field data, and the real-time channel estimates are used to simulate an end-to-end communication system with ambient noise at different signal-to-noise ratios (SNR). In tandem, we also simulate a time-varying shallow water acoustic channel under similar oceanic conditions using the Bellhop model, along with a communication system with similar signaling schemes and SNR variations. Equalization results from both the hybrid and model-based settings will be presented and implications of including machine learning to learn the channel parameters from both setups to inform the channel equalizers will be explored.

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22

Zhang, Xiao Qin, Yong Sheng Hu, and Li Yi Zhang. "Sixth-Second Order Normalized Cumulants Blind Equalization Algorithm Based on T/4 Oversampling." Applied Mechanics and Materials 719-720 (January 2015): 994–99. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.994.

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Most existing blind equalization algorithms rely on partial or complete channel identification, but the channel order estimation is always a difficult task. In this paper, higher order normalized cumulants analysis is applied to the blind equalization, and a new sixth-second order normalized cumulants blind equalization algorithm based on oversampling is proposed. The proposed method recovers the transmitted sequence adopting optimization algorithm of sixth-second order normalized cumulants without channel identification and channel order estimation. Simulation results show the algorithm's effectiveness.

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23

Sexton, T. A., and K. Pahlavan. "Channel modeling and adaptive equalization of indoor radio channels." IEEE Journal on Selected Areas in Communications 7, no. 1 (January 1989): 114–21. http://dx.doi.org/10.1109/49.16852.

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Boutalline, Mohammed, Belaid Bouikhalene, and Said Safi. "Channel Identification and Equalization based on Kernel Methods for Downlink Multicarrier-CDMA Systems." Journal of Electronic Commerce in Organizations 13, no. 2 (April 2015): 14–29. http://dx.doi.org/10.4018/jeco.2015040102.

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In this paper the authors are focused on channel identification and equalization for Multi-Carrier Code Division Multiple Access (MC-CDMA) system. For this, they identify the impulse response of two practical selective frequency fading channels called Broadband Radio Access Network (BRAN A and BRAN B) normalized by the European Telecommunications Standards Institute (ETSI). To identify the channel parameters, they have the positive definite kernels to build on algorithm. The simulations show that the presented method confirms the good performance for different SNR values. In part of equalization, the authors use the Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) equalizers.

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Xie, Yong Gang, and Dong Ya Shen. "A Novel Hybrid Algorithm for Equalization of WBAN Channel." Applied Mechanics and Materials 543-547 (March 2014): 1868–71. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1868.

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Equalization technology is important in WBAN channels for resolving ISI problem. However, traditional algorithms, such as LMS and RBF are not suitable to be applied in WBAN channel, due to the fact that channels of WBAN are particularly time variable and have severe multipath effect. In this study, we proposed a novel hybrid algorithm by combining NFN and RBFN algorithms. Experimental results show better performance compared to both NFN and RBFN algorithms in prediction problem in WBAN Channels.

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Wang, Dan, and Chi Yun Xu. "Research on Adaptive Modulation and Coding Technology in LTE-A System." Applied Mechanics and Materials 513-517 (February 2014): 2534–37. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.2534.

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In order to further improve the throughput and performance of the LTE system in the LTE-A system,this paper proposes a kind of AMC before the channel equalization in the LTE-A system. The scheme will be the channel matrix rank, channel correlation and channel equalization of SNR together as parameter for MCS, through the CQI-SNR curve to find the channel equalization before the final CQI to complete the feedback.And it solves the problems that the traditional AMC only relies on the SNR, and the SNR accuracy requirements. The theory and simulation results show, this scheme can improve the system throughput and performance.

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27

Jiang, Jie, Jian Zuo, and Hao Feng. "Research on Equalization Technology of Broadband Satellite Communication Channel." Journal of Physics: Conference Series 2209, no. 1 (February 1, 2022): 012005. http://dx.doi.org/10.1088/1742-6596/2209/1/012005.

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Abstract Satellite channel is the representative non-linear channel with limited frequency band. The random change of the channel causes the communication stability to be affected. With the development of satellite communication technology, the bandwidth of satellite communication has increased and the data rate has also increased significantly, resulting in more serious code interference, which has become a key factor affecting communication quality. Finding an efficient equalization technology to eliminate channel inter-code interference is the key to ensuring satellite broadband communications. This article first briefly discusses the principle of eliminating inter-symbol interference and common equalizer algorithms, and summarizes the main factors that affect the performance of channel equalization algorithms. On this basis, an improved LSTM blind equalization algorithm is proposed.

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Simeone, O., and U. Spagnolini. "Combined linear pre-equalization and BLAST equalization with channel correlation feedback." IEEE Communications Letters 7, no. 10 (October 2003): 487–89. http://dx.doi.org/10.1109/lcomm.2003.818886.

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29

Khedim, Djilali, and Abdelkader Benyettou. "Optimum Channel Equalization with Template Compression." International Review of Electrical Engineering (IREE) 11, no. 4 (August 31, 2016): 370. http://dx.doi.org/10.15866/iree.v11i4.8739.

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Won, Y. K., G. H. Lee, R. H. Park, J. H. Park, and B. U. Lee. "Channel equalization techniques for HDTV systems." IEEE Transactions on Consumer Electronics 40, no. 4 (1994): 903–12. http://dx.doi.org/10.1109/30.338337.

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31

Baptista, David, Rafael Ferrari, and Romis Attux. "Channel Equalization Based on Decision Trees." Journal of Communication and Information Systems 35 (2020): 150–61. http://dx.doi.org/10.14209/jcis.2020.16.

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Kalantarova, Nargiz, Suleyman Serdar Kozat, and Alper T. Erdogan. "Robust Turbo Equalization Under Channel Uncertainties." IEEE Transactions on Signal Processing 60, no. 1 (January 2012): 261–73. http://dx.doi.org/10.1109/tsp.2011.2162505.

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33

Salamanca, Luis, Juan José Murillo-Fuentes, and Fernando Perez-Cruz. "Bayesian Equalization for LDPC Channel Decoding." IEEE Transactions on Signal Processing 60, no. 5 (May 2012): 2672–76. http://dx.doi.org/10.1109/tsp.2012.2184098.

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34

Rahnema, Moe. "Channel equalization for the GSM system." International Journal of Wireless Information Networks 3, no. 3 (July 1996): 181–85. http://dx.doi.org/10.1007/bf02365828.

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35

Tugnait, J. K., Lang Tong, and Zhi ding. "Single-user channel estimation and equalization." IEEE Signal Processing Magazine 17, no. 3 (May 2000): 17–28. http://dx.doi.org/10.1109/msp.2000.841720.

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36

Kaleh, G. K. "Channel equalization for block transmission systems." IEEE Journal on Selected Areas in Communications 13, no. 1 (1995): 110–21. http://dx.doi.org/10.1109/49.363140.

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Pradhan, A. K., S. K. Meher, and A. Routray. "Communication channel equalization using wavelet network." Digital Signal Processing 16, no. 4 (July 2006): 445–52. http://dx.doi.org/10.1016/j.dsp.2005.06.001.

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38

D.C., Diana, and Joy Vasantha Rani S.P. "Novel cat swarm optimization algorithm to enhance channel equalization." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 36, no. 1 (January 3, 2017): 350–63. http://dx.doi.org/10.1108/compel-08-2015-0289.

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Purpose Adaptive equalization plays an important role in digital communication to reduce the distortions due to inter-symbol interference. An adaptive filter is used as an equalizer model in channel equalization. An adaptive algorithm is the heart of the adaptive filter which finds the optimum coefficients of the filter. The choice of the adaptive algorithm improves the convergence rate and minimizes the mean square error (MSE). This paper aims to propose a cat swarm optimization (CSO)-based adaptive algorithm and its modification to improve the performance of a channel equalizer. Design/methodology/approach The input digital training data are transmitted through different channel conditions. A linear transversal filter is used as a channel and equalizer model. The equalizer coefficients are trained by the proposed simplified cat swarm optimization (SCSO) algorithm to find the estimated digital training data. Findings The performance of the proposed SCSO algorithm is compared with particle swarm optimization (PSO)-based channel equalization. The improvement in convergence rate and MSE is verified under linear and nonlinear channel conditions with different delay spreads. The optimum parameters of the SCSO are found using simulation-based sensitivity analysis. Originality/value This paper analyzes a CSO algorithm for adaptive channel equalization and proposes a SCSO algorithm to identify the optimum coefficients of a transversal equalizer. The seeking mode process is simplified in the proposed SCSO to achieve better performance in channel equalization. The proposed SCSO algorithm guarantees minimum MSE in all independent runs, whereas in PSO, few misses are possible.

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El-Mahdy, A. E. S. "Adaptive Channel Estimation and Equalization for Rapidly Mobile Communication Channels." IEEE Transactions on Communications 52, no. 7 (July 2004): 1126–35. http://dx.doi.org/10.1109/tcomm.2004.831391.

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40

Gopalaswamy, S., and B. V. K. Vijaya Kumar. "Multi-channel equalization for PWM channels in magneto-optical recording." IEEE Transactions on Magnetics 33, no. 5 (1997): 3265–67. http://dx.doi.org/10.1109/20.617912.

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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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Xu, Bo, Tianxin Min, and Chik Patrick Yue. "Design of PAM-8 VLC Transceiver System Employing Neural Network-Based FFE and Post-Equalization." Electronics 11, no. 23 (November 26, 2022): 3908. http://dx.doi.org/10.3390/electronics11233908.

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Wireless communication technology adopting electromagnetic waves in an unlicensed spectrum, such as visible light, for communication has attracted wide research efforts. Visible light communication (VLC) utilizes visible light as a communication medium to transmit signals but faces a limited communication bandwidth and low data rate, which is caused by the intrinsic characteristics of LEDs. This paper first studies a mathematical model of limited bandwidth and its effect on transmitted signals and then analyzes the free space and underwater channel loss. With the theoretical analysis, a VLC transceiver system is presented for solving bandwidth limitation by utilizing a pulse-amplitude modulation-8 (PAM-8) scheme and a hybrid equalization method. The proposed hybrid equalization combined a passive equalizer, a neural network (NN)-based feed-forward equalization (FFE), and a radial basis function neural network (RBF-NN). The feasibility of this VLC system was verified through a co-simulation platform with both free-space and underwater channels. Compared with a VLC system adopting a deep neural network (DNN)-based post-equalization method, the proposed VLC system could achieve a data rate of 3.6 Gbps with a bit error rate (BER) of 3.8 × 10−3 over a 3 m free-space channel. The RBF-NN achieved a reduced training time of 10 min, which was 86.7% lower than the conventional DNN-based post-equalization method.

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Wang, Wen Bin, Dao Yuan Liu, and Yu Qin Yao. "Research of Equalization Technology Based on Matlab." Applied Mechanics and Materials 513-517 (February 2014): 3786–89. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3786.

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In the modern digital communication system, inter-symbol interference (ISI) caused by the imperfectness of the channel is a major factor that degrades the performance of communication. In order to decrease the influence of ISI and improve communication quality, people usually use equalization technology. Generally, channel response is changing over time, so the adaptive equalizer is necessary. This paper firstly introduced the theoretical foundation and realization method of the adaptive equalization system. Then discuss the LMS algorithm. Finally, the SIMULINK tool is used to build a communication system. The set of simulation results by observing the eye diagrams of the signals before and after equalization have validated the equalization effect.

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Travediu, Ana-Maria. "Improve channel signal quality using adaptive filters." Scientific Bulletin of Naval Academy XXIII, no. 1 (July 15, 2020): 90–96. http://dx.doi.org/10.21279/1454-864x-20-i1-012.

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A channel can be modelled by trying to calculate the physical processes which modify the transmitted signal. In this article we simulated the adaptive equalization of some communication channels. A system of data transmission in the basic band will be considered in order to illustrate the principle of adaptive equalization. In such a system, the data sequence is applied, upon emission, to a formation filter( low pass filter), with the purpose of limiting the occupied bandwidth. A relatively wide band noise is also introduced on the communication channel. The transmission channel can also be modelled as a linear filter, this is represented by the distortion filter. We used another filter to avoid the distortion introduced by the channel, with the role of equalizer. This should compensate for the distortion introduced by the channel. The channel transfer function is not generally known, and in addition, it may vary slowly over time. Therefore, the need for this filter appears to be adaptive. In order to perform the adaptation initially, a training sequence, known at the reception, can be transmitted first and the output of the filter is compared with a locally generated reference signal, but identical to the one emitted. After this initial adaptation phase, the transmitter transmits the information symbols, the useful signal, thus the application can be used to improve the signal quality of maritime communications channels.

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Kumar Mohapatra, Pradyumna, Saroja Kumar Rout, Sukant Kishoro Bisoy, Sandeep Kautish, Muzaffar Hamzah, Muhammed Basheer Jasser, and Ali Wagdy Mohamed. "Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization." Symmetry 14, no. 10 (October 6, 2022): 2078. http://dx.doi.org/10.3390/sym14102078.

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The transmission of high-speed data over communication channels is the function of digital communication systems. Due to linear and nonlinear distortions, data transmitted through this process is distorted. In a communication system, the channel is the medium through which signals are transmitted. The useful signal received at the receiver becomes corrupted because it is associated with noise, ISI, CCI, etc. The equalizers function at the front end of the receiver to eliminate these factors, and they are designed to make them work efficiently with proper network topology and parameters. In the case of highly dispersive and nonlinear channels, it is well known that neural network-based equalizers are more effective than linear equalizers, which use finite impulse response filters. An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. Here, in this work, to develop the symmetry-based efficient channel equalization in wireless communication, this paper proposes a modified form of bat algorithm trained with ANN for channel equalization. It adopts a population-based and local search algorithm to exploit the advantages of bats’ echolocation. The foremost initiative is to boost the flexibility of both the variants of the proposed algorithm and the utilization of proper weight, topology, and the transfer function of ANN in channel equalization. To evaluate the equalizer’s performance, MSE and BER can be calculated by considering popular nonlinear channels and adding nonlinearities. Experimental and statistical analyses show that, in comparison with the bat as well as variants of the bat and state-of-the-art algorithms, the proposed algorithm substantially outperforms them significantly, based on MSE and BER.

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Simerjeet Kaur, Dr Kamal Kumar Sharma, and Mr. Navnidhi Sharma. "Analysis of BER Improvement of Adaptive Equalizer using CE and STB code." International Journal of Research in Informative Science Application & Techniques (IJRISAT) 3, no. 6 (June 25, 2019): 44–50. http://dx.doi.org/10.46828/ijrisat.v3i6.132.

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In a wireless communication channel, when the modulation bandwidth is exceeding the coherence bandwidth ISI takes place as the transmitted pulses are spread into the adjacent symbols. To combat the effects of ISI and noise and to reconstruct the signal and minimize Bit Error Rate (BER), the adaptive channel equalizer is used at the receiver end. Various kinds of interferences in a communication channel exists like Inter symbol Interference, Multipath Interference and Additive Interference which deals with the design of an Adaptive Equalizer. The idea of the equalizer is to build filter in the receiver that counter acts the effect of the channel. In essence, the equalizer must “unscatter” the impulse response and can be stated as the goal of designing the equalizer E so that the impulse response of the combined channel and equalizer CE has a single spike. We investigate channel equalization and introduce hierarchical and adaptive nonlinear channel equalization algorithms that are highly efficient and provide significantly enhanced 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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Farhang-Boroujeny, B. "Channel equalization via channel identification: algorithms and simulation results for rapidly fading HF channels." IEEE Transactions on Communications 44, no. 11 (1996): 1409–12. http://dx.doi.org/10.1109/26.544455.

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Zhao, Zhen, Shao Chuan Wu, and Shu Ying Gao. "A Direct Mode Operation Design and Simulation Applied to TD-LTE." Applied Mechanics and Materials 577 (July 2014): 998–1003. http://dx.doi.org/10.4028/www.scientific.net/amm.577.998.

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This paper offers a DMO (direct mode operation) design applied to TD-LTE. It can support point to point full-duplex communication in the no signal covered area and user switching according to their priority at the same time. The design divides channel into access channel and communication channel to improve the spectrum efficiency. When the SNR is higher than 16dB, the DMO design using QPSK modulation has a BER (bit error rate) reaching 10-4 under ITU-R M1225 channel B. Although at the same BER value, the SNR requirements of IFDMA has a 0.5dB lower than LFDMA, given that TD-LTE uses LFDMA and LFDMA has a good resistance to frequency offset and is much easier to realize, we adopt LFDMA as subcarrier mapping method in the DMO design. Besides, at the same BER value, the required SNR of MMSE (minimum mean square error) equalization is 1.0~1.5dB lower than the required SNR of the ZF (zero-forcing) equalization. Therefore DMO should use MMSE equalization in the low SNR environment and ZF equalization in the high SNR environment.

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Fateh, Rachid, Anouar Darif, and Said Safi. "Performance Evaluation of MC-CDMA Systems with Single User Detection Technique using Kernel and Linear Adaptive Method." Journal of Telecommunictions and Information Technology 4, no. 2021 (December 30, 2021): 1–11. http://dx.doi.org/10.26636/jtit.2021.151621.

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Among all the techniques combining multi-carrier modulation and spread spectrum, the multi-carrier code division multiple access (MC-CDMA) system is by far the most widely studied. In this paper, we present the performance of the MC-CDMA system associated with key single-user detection techniques. We are interested in problems related to identification and equalization of mobile radio channels, using the kernel method in Hilbert space with a reproducing kernel, and a linear adaptive algorithm, for MC-CDMA systems. In this context, we tested the efficiency of these algorithms, considering practical frequency selective fading channels, called broadband radio access network (BRAN), standardized for MC-CDMA systems. As far as the equalization problem encountered after channel identification is concerned, we use the orthogonality restoration combination (ORC) and the minimum mean square error (MMSE) equalizer techniques to correct the distortion of the channel. Simulation results demonstrate that the kernel algorithm is efficient for practical channels.

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YÜKSEKKAYA, Barış, and Cenk TOKER. "Joint transceiver FIR filter design for multiuser MIMO channel shortening equalization and full equalization using channel duality." TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 25 (2017): 4077–90. http://dx.doi.org/10.3906/elk-1610-320.

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