Готові списки джерел за темами / Maximum likelihood sequence detection (MLSD)

Добірка наукової літератури з теми "Maximum likelihood sequence detection (MLSD)"

Автор: Grafiati
Опубліковано: 26 січня 2023

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  1. Статті в журналах
  2. Дисертації
  3. Частини книг
  4. Тези доповідей конференцій

Статті в журналах з теми "Maximum likelihood sequence detection (MLSD)":

1

Maggio, Gabriel N., Mario R. Hueda, and Oscar E. Agazzi. "Maximum Likelihood Sequence Detection Receivers for Nonlinear Optical Channels." Journal of Electrical and Computer Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/736267.

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The space-time whitened matched filter (ST-WMF) maximum likelihood sequence detection (MLSD) architecture has been recently proposed (Maggio et al., 2014). Its objective is reducing implementation complexity in transmissions over nonlinear dispersive channels. The ST-WMF-MLSD receiver (i) drastically reduces the number of states of the Viterbi decoder (VD) and (ii) offers a smooth trade-off between performance and complexity. In this work the ST-WMF-MLSD receiver is investigated in detail. We show that thespace compressionof the nonlinear channel is an instrumental property of the ST-WMF-MLSD which results in a major reduction of the implementation complexity in intensity modulation and direct detection (IM/DD) fiber optic systems. Moreover, we assess the performance of ST-WMF-MLSD in IM/DD optical systems with chromatic dispersion (CD) and polarization mode dispersion (PMD). Numerical results for a 10 Gb/s, 700 km, and IM/DD fiber-optic link with 50 ps differential group delay (DGD) show that the number of states of the VD in ST-WMF-MLSD can be reduced ~4 times compared to an oversampled MLSD. Finally, we analyze the impact of the imperfect channel estimation on the performance of the ST-WMF-MLSD. Our results show that the performance degradation caused by channel estimation inaccuracies is low and similar to that achieved by existing MLSD schemes (~0.2 dB).
2

Kumar, Ghanendra, and Chakres Kumar. "Effect of NAVA for Dense Optical Communication System." Science & Technology Journal 7, no. 1 (January 1, 2019): 78–81. http://dx.doi.org/10.22232/stj.2019.07.01.10.

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Viterbi Algorithm (VA) is basically an algorithm that is implemented for the detection & estimation of a sequence of symbols in digital communication and signal processing. It calculates a survivor path with minimum metric value, but cannot detect any error. The VA is scrutinized to upgrade the transmission process and provide the plate form in terms of the existence, linear phase noise as well as non-linear phase noise. In contradiction to non-adaptive MLSD (Maximum Likelihood Sequence Detection), the Viterbi algorithm renders the exemplary performance.
3

Zhou, Ke, Shilian Wang, and Eryang Zhang. "Coherent RAKE Receiver for CPM-Based Direct Sequence Spread Spectrum." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/6971083.

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Direct sequence spread spectrum (DSSS) using continuous phase modulation (CPM) inherits the techniques’ benefits, constant envelope, anti-interference, and spectral efficiency. To get diversity gains over a Rayleigh-fading multipath channel as in conventional direct sequence spread-spectrum binary phase shift keying (DSSS-BPSK) system, a new class of coherent RAKE receivers is proposed in this work. By introducing chip branch metric to the receiver scheme, despreading and data detection can be done meanwhile based on Maximum Likelihood Sequence Detection (MLSD). Compared to the conventional RAKE receiver which sums decision metrics symbol-by-symbol, the proposed DSSS-CPM RAKE receiver accumulates symbol branch metric increments over every phase state of multiple paths after chip phase synchronization. Numerical results show that DSSS-CPM using the synchronous despreading and demodulation algorithm has no performance loss compared to CPM system that employs MLSD algorithm under the same test conditions. Moreover, the proposed RAKE receiver outperforms conventional RAKE receiver and achieves a remarkable diversity gain of bit error rate (BER) under the Rayleigh-fading multipath channel.
4

El-Mahdy, Ahmed El-Sayed. "Adaptive Selection Combining Receiver over Time Varying Frequency Selective Fading Channel in Class-A Noise." ISRN Signal Processing 2013 (May 13, 2013): 1–6. http://dx.doi.org/10.1155/2013/894542.

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An adaptive selection combining (SC) scheme is proposed for time varying mobile communication channel in Class-A impulsive noise. The receiver adaptively selects a diversity branch out of the available branches and discards the others. This is performed by computing the maximum likelihood (ML) metric of each diversity branch and selects the branch with the maximum metric. The proposed adaptive SC scheme dynamically adjusts the threshold value according to the time variations of the channel. Equalization and data detection are performed after combining using maximum likelihood sequence estimation implemented by Viterbi algorithm (MLSE-VA). The minimum survivor technique is employed to reduce the complexity of the receiver.
5

Cao, Minghua, Ruifang Yao, Jieping Xia, Kejun Jia, and Huiqin Wang. "LSTM Attention Neural-Network-Based Signal Detection for Hybrid Modulated Faster-Than-Nyquist Optical Wireless Communications." Sensors 22, no. 22 (November 20, 2022): 8992. http://dx.doi.org/10.3390/s22228992.

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In order to improve the accuracy of signal recovery after transmitting over atmospheric turbulence channel, a deep-learning-based signal detection method is proposed for a faster-than-Nyquist (FTN) hybrid modulated optical wireless communication (OWC) system. It takes advantage of the long short-term memory (LSTM) network in the recurrent neural network (RNN) to alleviate the interdependence problem of adjacent symbols. Moreover, an LSTM attention decoder is constructed by employing the attention mechanism, which can alleviate the shortcomings in conventional LSTM. The simulation results show that the bit error rate (BER) performance of the proposed LSTM attention neural network is 1 dB better than that of the back propagation (BP) neural network and outperforms by 2.5 dB when compared with the maximum likelihood sequence estimation (MLSE) detection method.
6

Zhang, Jialiang, Guanjun Gao, Jingwen Li, Ziqi Ma, and Yonggang Guo. "Experimental Demonstration and Simulation of Bandwidth-Limited Underwater Wireless Optical Communication with MLSE." Photonics 9, no. 3 (March 12, 2022): 182. http://dx.doi.org/10.3390/photonics9030182.

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Underwater wireless optical communication (UWOC) is able to provide large bandwidth, low latency, and high security. However, there still exist bandwidth limitations in UWOC systems, with a lack of effective compensation methods. In this paper, we systematically study the bandwidth limitation due to the transceiver and underwater channel through experiments and simulations, respectively. Experimental results show that by using the 7-tap maximum likelihood sequence estimation (MLSE) detection, the maximum bitrate of the simple rectangular shape on–off-keying (OOK) signaling is increased from 2.4 Gb/s to 4 Gb/s over 1 GHz transceiver bandwidth, compared to the conventional symbol-by-symbol detection. For the bandwidth limitation caused by the underwater channel, we simulate the temporal dispersion in the UWOC by adopting a Monte Carlo method with a Fournier–Forand phase function. With MLSE adopted at the receiver, the maximum available bitrate is improved from 0.4 to 0.8 Gb/s in 12 m of harbor water at the threshold of hard-decision forward-error-correction (HD-FEC, 3.8 × 10−3). Moreover, when the bitrate for 0.4 Gb/s 12 m and 0.8 Gb/s 10 m OOK transmission remains unchanged, the power budget can be reduced from 33.8 dBm to 30 dBm and from 27.8 dBm to 23.6 dBm, respectively. The results of both experiments and simulations indicate that MLSE has great potential for improving the performance of bandwidth-limited communication systems.
7

Makarov, S. B., S. V. Zavjalov, D. C. Nguyen, and A. S. Ovsyannikova. "Coherent Detection of Non-Orthogonal Spectrally Efficient Multicarrier Signals Using a Decision Feedback Algorithm." Journal of the Russian Universities. Radioelectronics 24, no. 5 (November 29, 2021): 22–35. http://dx.doi.org/10.32603/1993-8985-2021-24-5-22-35.

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Introduction. Spectrally efficient frequency division multiplexing (SEFDM) is a promising technology for improving spectral efficiency. Since SEFDM signals transmitted on subcarriers are not orthogonal, interchannel interference occurs due to the mutual influence of signals transmitted on adjacent subcarriers. Algorithms for receiving SEFDM signals can be distinguished into element-by-element coherent detection and maximum-likelihood sequence estimation (MLSE). The former method, although being simpler, is characterized by a low bit error rate performance. The latter method, although providing for a higher energy efficiency, is more complicated and does not allow high absolute message rates.Aim. To consider a trade-off solution to the problem of coherent detection of SEFDM signals under the condition of significant interchannel interference, namely, the use of an iterative algorithm of element-by-element processing with decision feedback at each subcarrier frequency.Materials and methods. Analytical expressions for the operation of a demodulator solver were derived. A simulation model for transmission of SEFDM signals was built in the MatLab environment, including element-by-element detection with decision feedback.Results. The simulation results confirmed the efficiency of the proposed algorithm. For error probabilities p =102…103, the energy gains reach values from 0.2 to 7.5 dB for different values of the non-orthogonal subcarrier spacing. At the same time, the efficiency of the detection algorithm with decision feedback turns out to be significantly lower than that when using the detection algorithm MLSE.Conclusion. The proposed detection algorithm can be used in future generations of mobile communications, which require high transmission rates. By reducing the computational complexity of the algorithm, it is possible to provide for a lower power consumption of mobile devices.
8

Broto, Wisnu, Noor Suryaningsih, and Adhi Mahendra. "WORKING ANALYSIS OF SPACE TIME TRELLIS CODE ON WIFI MIMO(2X2) SYSTEM OFDM." Spektra: Jurnal Fisika dan Aplikasinya 6, no. 3 (December 30, 2021): 159–74. http://dx.doi.org/10.21009/spektra.063.03.

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Wireless communication nowadays requires a system with reliable performance, efficient use of bandwidth, efficient power, and better coverage because it is in line with human needs for applications that require high and fast data rates. One of the concepts and methods to meet these needs is using an antenna technique with many transmitters and receivers or often called Multiple Input Multiple Output (MIMO), by adding a strategy at the time of delivery, namely the Space-Time Coding (STC) technique. In addition, the application of Orthogonal Frequency Division Multiplexing (OFDM) on MIMO-STC will more efficiently use bandwidth. The Space-Time Trellis Code (STTC) method is one of the diverse techniques in sending data with complex coding so that coding reinforcement is achieved and applied to the OFDM MIMO system. It is hoped that a system with reliable performance can be achieved. The simulation that is carried out presents the STTC and OFDM schemes on multi antennas (2 transmitters x 2 receivers) with a Combiner and Maximum Likelihood Sequence Estimator (MLSE) detection algorithm on the receiver. It is to get the quality of the sending signal in the performance analysis of Bit Error Rate (BER) with Signal to Noise Ratio (SNR). The simulation results are shown by modulation with M-array Phase Shift Keying (MPSK) and the number of symbols sent by giving different input parameter values. The results show that the number of carriers and the size of the Fast Fourier Transform (FFT) is large, and the modulation type with a small constellation produces a low BER and throughput at high SNR.
9

Aulin, T. M. "Breadth-first maximum-likelihood sequence detection: geometry." IEEE Transactions on Communications 51, no. 12 (December 2003): 2071–80. http://dx.doi.org/10.1109/tcomm.2003.813255.

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10

Aulin, T. M. "Breadth-first maximum likelihood sequence detection: basics." IEEE Transactions on Communications 47, no. 2 (1999): 208–16. http://dx.doi.org/10.1109/26.752126.

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Статті в журналах

Дисертації з теми "Maximum likelihood sequence detection (MLSD)":

1

Lin, Jin-Son, and Kamilo Feher. "NONCOHERENT AND DIFFERENTIAL DETECTION OF FQPSK WITH MAXIMUM-LIKELIHOOD SEQUENCE ESTIMATION IN NONLINEAR CHANNELS." International Foundation for Telemetering, 2002. http://hdl.handle.net/10150/606381.

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International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California
This paper presents noncoherent limiter-discriminator detection and differential detection of FQPSK (Feher quadrature phase-shift-keying) with maximum-likelihood sequence estimation (MLSE) techniques. Noncoherent FQPSK systems are suitable for fast fading and cochannel interference channels and channels with strong phase noise, and they can offer faster synchronization and reduce outage events compared with conventional coherent systems. In this paper, both differential detection and limiter-discriminator detection of FQPSK are discussed. We use MLSE with lookup tables to exploit the memory in noncoherently detected FQPSK signals and thus significantly improve the bit error rate (BER) performance in an additive white Gaussian noise (AWGN) channel.
2

Kasan, Karim. "Performance of a new single sideband (SSB) continuous phase modulation (CPM)." Thesis, CentraleSupélec, 2021. http://www.theses.fr/2021CSUP0010.

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Dans cette thèse, nous étudions la modulation par déplacement de fréquence à bande latérale unique (SSB-FSK), un schéma de modulation de phase continue (CPM) ayant, par essence, la caractéristique original du spectre à bande latérale unique (BLU). Tout d’abord, nous présentons l’origine du signal à partir de la physique quantique. Ensuite, nous proposons un détecteur de séquence à maximum de vraisemblance (MLSD) simplifié pour les schémas CPM conventionnels, basé sur le réarrangement montré dans le modèle de signal SSB-FSK. Pour exploiter pleinement les performances de la SSB-FSK, nous examinons la probabilité d’erreur du signal, l’occupation de la bande passante et la complexité du récepteur. Étant donné que différentes mesures de performance sont prises en compte, nous avons utilisé une optimisation multi-objectifs pour obtenir de nouveaux schémas SSB-FSK plus performants que les schémas CPM classiques. En outre, nous proposons une solution pour simplifier la complexité des signaux SSB-FSK en utilisant la décomposition de la modulation d’amplitude d’impulsion (PAM). Les impulsions PAM ont été obtenues à partir d’un algorithme que nous avons développé. En outre, nous proposons une séquence d’entraînement générique optimale pour l’estimation conjointe de la synchronisation des symboles, du décalage de fréquence et de la phase de la porteuse pour la synchronisation en mode burst. La séquence d’entraînement a été obtenue en utilisant les bornes de Cramér-Rao
In this PhD thesis, we investigate the single-sideband frequency shift keying (SSB-FSK), a continuous phase modulation (CPM) scheme having, by essence, the original feature of the single-sideband (SSB) spectrum. First, we present the origin of the signal from quantum physics. Then, we propose a simplified Maximum likelihood sequence detection (MLSD) detector for conventional CPM schemes based on the rearrangement shown in the SSB-FSK signal model. To fully exploit the SSB-FSK performance, we examine the signal error probability, bandwidth occupancy, and receiver complexity. Since different performance metrics are considered, we employed a multi-objective optimization to achieve new SSB-FSK schemes that outperform conventional CPM schemes. Moreover, we propose a solution to simplify the complexity of SSB-FSK signals using the pulse amplitude modulation (PAM) decomposition. The PAM pulses were achieved from an algorithm we developed. Furthermore, we offer an optimum generic training sequence for the joint estimation of symbol timing, frequency offset, and carrier phase for burst mode synchronization. The training sequence was obtained using the Cramér-Rao bounds
3

Cho, Jin Woo. "Advanced optical receivers using cross layer optimization and maximum-likelihood sequence detection /." May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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4

Park, Hyung Chul, Kwyro Lee, and Kamilo Feher. "NON-COHERENTLY DETECTED FQPSK: RAPID SYNCHRONIZATION AND COMPATIBILITY WITH PCM/FM RECEIVERS." International Foundation for Telemetering, 2001. http://hdl.handle.net/10150/606461.

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International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada
A new class of non-coherent detection techniques for recently standardized Feher patented quadrature phase-shift keying (FQPSK) systems is proposed and studied by computer aided design/simulations and also verified by experimental hardware measurements. The theoretical concepts of the described non-coherent techniques are based on an interpretation of the instantaneous frequency deviation or phase transition characteristics of FQPSK-B modulated signal at the front end of the receiver. These are accomplished either by Limiter-Discriminator (LD) or by Limiter-Discriminator followed by Integrate-and-Dump (LD I&D) methods. It is shown that significant BER performance improvements can be obtained by increasing the received signal’s observation time over multiple symbols as well as by adopting trellis-demodulation. For example, our simulation results show that a BER=10^-4 can be obtained for an E(b)/N(0)=12.7 dB.
5

Tsai, Song-Feng, and 蔡松峰. "Nonlinear Maximum-Likelihood Sequence Detector (MLSD) for High Recording Density Magneto-Optical Disk Drive." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/73486908250904556213.

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碩士
國立交通大學
電信研究所
85
To implement a high recording density MO (magneto-optical) disk drive, the priorknowledge about the MO read/write channel is needed. An accurate channel model will make an optimal system design possible. Linear MO channel models which are often used in low density recording systems are not suitable for describing the channel effect in a high density recording system. Nonlinear channel characteristic which is caused mainly by the interaction between the two closely allocated recorded domains must be taken into account. It is known that this nonlinear effect will seriously degrade theperformance of a linear receiver no matter how complicated the associated equalizer is. he first part of this thesis deals with the MO channel identification problem. Both linear and nonlinear methods are used. We find that the linear method using PN sequence as the input is not stable. Channel responses using three linear algorithms are not consistent. There are indications that strong nonlinearity does exit in the MO channel. We then use a Volterra-decomposed nonlinear model to identify MO channels. Numerical results show that this nonlinear model can charaterize the MO channel to a very high degree of accuracy. In fact, as far as mean-squared identification error (MSIE) is concerned, the nonlinear method yields MSIE 20 times smaller than that resulted from any linear model. The second part concentrates on the detector design, assuming a nonlinear channel characteristic. We derive a maximum-likelihood sequence detector and evaluate the resulting performance. Based upon the nonlinear channel model, we derive two nonlinear Viterbi detectors, one for an NRZ-coded (non- return zero) channel and the other for a (2,7) RLL-coded nonlinear MODD channel. Using the SAM (sequenced amplitude margin) scheme we are able to predict the error rate performance up to 10^-9 with only about 10^5 ~ 10^6 sample bits. Due to the practical limitation of hardware resolution for both the transimitter (pattern generator) and front-end digitizer (digital oscilloscope), there are only finite number of clock rate from which we can choose. Experiment results indicate that the error rate performance of the NRZ-coded nonlinear Viterbi detector is around 10^-6 while the (2,7) RLL-coded nonlinear Viterbi detector can be almost 10^-9. The selected recording density is at least 1.15 times higher than the original specification; in other words, there are almost 15% capacity enhancement for the (2,7) RLL-coded nonlinear Viterbi detector over the original linear detector.
6

Reader, David. "Blind maximum likelihood sequence detection over fast fading communication channels." 1996. http://arrow.unisa.edu.au:8081/1959.8/85004.

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Частини книг з теми "Maximum likelihood sequence detection (MLSD)":

1

Zhang, J. L., C. Xu, G. J. Gao, H. D. Liu, and Z. Yang. "Direct detection of a single-channel 112 Gb/s PAM-4 signal using an 18 GHz directly modulated laser and Maximum-Likelihood Sequence Estimation (MLSE) equalization." In Frontier Research and Innovation in Optoelectronics Technology and Industry, 385–91. London, UK : CRC Press/Balkema, an imprint of the Taylor & Francis Group, [2019]: CRC Press, 2018. http://dx.doi.org/10.1201/9780429447082-56.

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2

O’Sullivan, J. A. "Iterative Algorithms for Maximum Likelihood Sequence Detection." In The Kluwer International Series in Engineering and Computer Science, 137–56. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0895-3_8.

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3

"Maximum Likelihood Sequence Detection (MLSD)." In Encyclopedia of Ocean Engineering, 986. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-10-6946-8_300450.

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4

"Maximum Likelihood Sequence Detection." In Encyclopedia of Wireless Networks, 795. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_300356.

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5

"Maximum Likelihood Sequence Detection." In Channel Equalization for Wireless Communications, 115–49. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118105283.ch6.

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Тези доповідей конференцій з теми "Maximum likelihood sequence detection (MLSD)":

1

Wu, Ting, and Haris Vikalo. "Maximum likelihood DNA sequence detection via sphere decoding." In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495564.

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2

Luo, Jie. "Fast Maximum Likelihood Sequence Detection Over Vector Intersymbol Interference Channels." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366573.

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3

Meehan, Tim, James Hicks, and Frank Kragh. "Maximum Likelihood Sequence Detection of a Bit-stuffed Data Source." In 2006 IEEE International Conference on Communications. IEEE, 2006. http://dx.doi.org/10.1109/icc.2006.255025.

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4

Xu, Zhuoran, Changyuan Yu, and Pooi-Yuen Kam. "Performance of Adaptive Maximum Likelihood Sequence Detection with Nonlinear Phase Noise." In OptoElectronics and Communications Conference and Photonics in Switching. Washington, D.C.: OSA, 2013. http://dx.doi.org/10.1364/oecc_ps.2013.tupr_16.

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5

Xu, Zhuoran, Pooi-Yuen Kam, and Changyuan Yu. "Performance of Pilot-Assisted Maximum Likelihood Sequence Detection for QAM Signals." In Signal Processing in Photonic Communications. Washington, D.C.: OSA, 2014. http://dx.doi.org/10.1364/sppcom.2014.sw1c.2.

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6

Chatzidiamantis, N. D., M. Uysal, T. A. Tsiftsis, and G. K. Karagiannidis. "EM-Based Maximum-Likelihood Sequence Detection for MIMO Optical Wireless Systems." In ICC 2009 - 2009 IEEE International Conference on Communications. IEEE, 2009. http://dx.doi.org/10.1109/icc.2009.5198982.

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7

Sabapathi, T., and G. Jaya Brindha. "Mitigation of fiber non linear effects by Maximum Likelihood Sequence Detection." In 2014 International Conference on Communication and Network Technologies (ICCNT). IEEE, 2014. http://dx.doi.org/10.1109/cnt.2014.7062744.

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8

Zhou, Hanbing, Haitao Liu, Daoben Li, and Gang Li. "A Novel Adaptive Maximum Likelihood Sequence Detection Receiver for MIMO-OFDM System." In 2006 International Conference on Communications, Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/icccas.2006.284827.

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9

McCarthy, M. E., J. Zhao, P. Gunning, and A. D. Ellis. "A novel field-detection maximum-likelihood sequence estimation for chromatic-dispersion compensation." In 2008 34th European Conference on Optical Communication. IEEE, 2008. http://dx.doi.org/10.1109/ecoc.2008.4729322.

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10

Dolivo, F., R. Hermann, and S. Olcer. "Performance and sensitivity analysis of maximum-likelihood sequence detection on magnetic recording channels." In International Magnetics Conference. IEEE, 1989. http://dx.doi.org/10.1109/intmag.1989.690308.

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