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

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

Автор: Grafiati

Опубліковано: 26 січня 2023

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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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Анотація:

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).

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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.

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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.

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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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Анотація:

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.

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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.

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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.

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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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Анотація:

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.

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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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Анотація:

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.

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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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11

Marsella, D., M. Secondini, and E. Forestieri. "Maximum Likelihood Sequence Detection for Mitigating Nonlinear Effects." Journal of Lightwave Technology 32, no. 5 (March 2014): 908–16. http://dx.doi.org/10.1109/jlt.2013.2294457.

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12

Hart, B. D. "Maximum likelihood sequence detection using a pilot tone." IEEE Transactions on Vehicular Technology 49, no. 2 (March 2000): 550–60. http://dx.doi.org/10.1109/25.832986.

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13

Walsh, John MacLaren, Phillip A. Regalia, and C. Richard Johnson. "Turbo Decoding as Iterative Constrained Maximum-Likelihood Sequence Detection." IEEE Transactions on Information Theory 52, no. 12 (December 2006): 5426–37. http://dx.doi.org/10.1109/tit.2006.885535.

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14

Boon Chong Ng, M. Cedervall, and A. Paulraj. "A structured channel estimator for maximum-likelihood sequence detection." IEEE Communications Letters 1, no. 2 (March 1997): 52–55. http://dx.doi.org/10.1109/4234.559362.

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15

Ordentlich, Erik, and Ron M. Roth. "Two-Dimensional Maximum-Likelihood Sequence Detection Is NP Hard." IEEE Transactions on Information Theory 57, no. 12 (December 2011): 7661–70. http://dx.doi.org/10.1109/tit.2011.2170108.

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16

Giannakis, Georgios B., and Jerry M. Mendel. "Entropy interpretation of maximum‐likelihood deconvolution." GEOPHYSICS 52, no. 12 (December 1987): 1621–30. http://dx.doi.org/10.1190/1.1442279.

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Entropy concepts are embodied in the maximum‐likelihood deconvolution (MLD) method, just as they are in minimum‐entropy (MED) methods. MLD asymptotically minimizes Shannon’s entropy of the reflectivity sequence (which, in MLD, is modeled as a Bernoulli‐Gaussian random sequence). Study of maximum‐ likelihood detection and estimation of the reflectivity sequence reveals that MLD is embodied in the general framework of the “adaptive” MED methods. Comparisons based on similarities and differences between MLD and various existing MED techniques show that MLD is robust due to explicit inclusion of noise in its statistical model.

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17

Song, Shiming, Kyojin D. Choo, Thomas Chen, Sunmin Jang, Michael P. Flynn, and Zhengya Zhang. "A Maximum-Likelihood Sequence Detection Powered ADC-Based Serial Link." IEEE Transactions on Circuits and Systems I: Regular Papers 65, no. 7 (July 2018): 2269–78. http://dx.doi.org/10.1109/tcsi.2017.2775619.

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18

Fossorier, M. P. C. "Dynamic quantization for maximum likelihood sequence detection of PAM signaling." IEEE Transactions on Communications 44, no. 11 (1996): 1444–54. http://dx.doi.org/10.1109/26.544461.

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19

Dubey, V., and D. Taylor. "Maximum Likelihood Sequence Detection for QPSK on Nonlinear, Band-Limited Channels." IEEE Transactions on Communications 34, no. 12 (December 1986): 1225–35. http://dx.doi.org/10.1109/tcom.1986.1096483.

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20

Chatzidiamantis, N. D., M. Uysal, T. A. Tsiftsis, and G. K. Karagiannidis. "Iterative Near Maximum-Likelihood Sequence Detection for MIMO Optical Wireless Systems." Journal of Lightwave Technology 28, no. 7 (April 2010): 1064–70. http://dx.doi.org/10.1109/jlt.2009.2038724.

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21

Xu, Zhuoran, Pooi-Yuen Kam, and Changyuan Yu. "Adaptive Maximum Likelihood Sequence Detection for QPSK Coherent Optical Communication System." IEEE Photonics Technology Letters 26, no. 6 (March 2014): 583–86. http://dx.doi.org/10.1109/lpt.2014.2300148.

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22

Fagan, A. D., and F. D. O'Keane. "Performance comparison of detection methods derived from maximum-likelihood sequence estimation." IEE Proceedings F Communications, Radar and Signal Processing 133, no. 6 (1986): 535. http://dx.doi.org/10.1049/ip-f-1.1986.0087.

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23

Zhang, Lei, Bin Hu, Jun Wu, and Zhong Hua Liu. "Complexity Constrained Detection of Continuous Phase Modulation Based on Breadth-First Method." Applied Mechanics and Materials 263-266 (December 2012): 331–34. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.331.

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Анотація:

This paper solves the problem of high detection complexity of continuous phase modulation (CPM) signals over additive white Gaussian noise (AWGN) channel. A complexity constrained sequence detection method for CPM is provided using breadth-first maximum-likelihood sequence detection. The derived result is to reserve only those states which are closest to the received signal in the Euclidean distance after retain one best path for every state. Compared with the maximum-likelihood detector based on Viterbi Algorithm (VA), a significant reduction in complexity is obtained by the suggested detector while maintaining good performances.

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24

Shao, Xuguang, Pooi-Yuen Kam, and Changyuan Yu. "Maximum likelihood sequence detection in laser phase noise-impaired coherent optical systems." Optics Express 19, no. 23 (October 25, 2011): 22600. http://dx.doi.org/10.1364/oe.19.022600.

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25

Katz, Gilad. "Channel estimators for maximum-likelihood sequence estimation in direct-detection optical communications." Optical Engineering 47, no. 4 (April 1, 2008): 045003. http://dx.doi.org/10.1117/1.2904827.

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26

Chatzidiamantis, Nestor D., George K. Karagiannidis, and Murat Uysal. "Generalized Maximum-Likelihood Sequence Detection for Photon-Counting Free Space Optical Systems." IEEE Transactions on Communications 58, no. 12 (December 2010): 3381–85. http://dx.doi.org/10.1109/tcomm.2010.093010.090116a.

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27

Zhang, Lu, and Zhiyong Wu. "Closed-form suboptimal maximum-likelihood sequence detection for free-space optical communications." Applied Optics 51, no. 27 (September 11, 2012): 6441. http://dx.doi.org/10.1364/ao.51.006441.

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28

Boon Chong Ng, M. Cedervall, and A. Paulraj. "A structured channel estimator for maximum likelihood sequence detection in multipath fading channels." IEEE Transactions on Vehicular Technology 48, no. 4 (July 1999): 1216–28. http://dx.doi.org/10.1109/25.775370.

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29

Dolivo, F., R. Hermann, and S. Olcer. "Performance and sensitivity analysis of maximum-likelihood sequence detection on magnetic recording channels." IEEE Transactions on Magnetics 25, no. 5 (1989): 4072–74. http://dx.doi.org/10.1109/20.42526.

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30

Sabapathi, T., and G. Jaya Brindha. "Impact of SRS in WDM Systems and Its Mitigation by Maximum Likelihood Sequence Detection." International Journal of Scientific Engineering and Technology 4, no. 4 (April 1, 2015): 239–42. http://dx.doi.org/10.17950/ijset/v4s4/404.

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31

Lin, D. B., P. H. Chiang, and H. J. Li. "Performance of Noncoherent Maximum-Likelihood Sequence Detection for Differential OFDM Systems With Diversity Reception." IEEE Transactions on Broadcasting 52, no. 1 (March 2006): 62–70. http://dx.doi.org/10.1109/tbc.2005.857604.

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32

Vazquez, M. A., and J. Miguez. "Maximum-Likelihood Sequence Detection in Time- and Frequency-Selective MIMO Channels With Unknown Order." IEEE Transactions on Vehicular Technology 58, no. 1 (January 2009): 499–504. http://dx.doi.org/10.1109/tvt.2008.924996.

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33

Wing-Kin Ma, K. M. Wong, and P. C. Ching. "On computing Verdu's upper bound for a class of maximum-likelihood multiuser detection and sequence detection problems." IEEE Transactions on Information Theory 47, no. 7 (2001): 3049–53. http://dx.doi.org/10.1109/18.959286.

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34

Reboiro-Jato, David, Miguel Reboiro-Jato, Florentino Fdez-Riverola, Cristina P. Vieira, Nuno A. Fonseca, and Jorge Vieira. "ADOPS - Automatic Detection Of Positively Selected Sites." Journal of Integrative Bioinformatics 9, no. 3 (December 1, 2012): 18–32. http://dx.doi.org/10.1515/jib-2012-200.

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Summary Maximum-likelihood methods based on models of codon substitution have been widely used to infer positively selected amino acid sites that are responsible for adaptive changes. Nevertheless, in order to use such an approach, software applications are required to align protein and DNA sequences, infer a phylogenetic tree and run the maximum-likelihood models. Therefore, a significant effort is made in order to prepare input files for the different software applications and in the analysis of the output of every analysis. In this paper we present the ADOPS (Automatic Detection Of Positively Selected Sites) software. It was developed with the goal of providing an automatic and flexible tool for detecting positively selected sites given a set of unaligned nucleotide sequence data. An example of the usefulness of such a pipeline is given by showing, under different conditions, positively selected amino acid sites in a set of 54 Coffea putative S-RNase sequences. ADOPS software is freely available and can be downloaded from http://sing.ei.uvigo.es/ADOPS.

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35

Verdu, S. "Maximum likelihood sequence detection for intersymbol interference channels: A new upper bound on error probability." IEEE Transactions on Information Theory 33, no. 1 (January 1987): 62–68. http://dx.doi.org/10.1109/tit.1987.1057271.

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36

Jaekyun Moon and Jaewook Lee. "Timing Recovery in Conjunction With Maximum Likelihood Sequence Detection in the Presence of Intersymbol Interference." IEEE Transactions on Circuits and Systems I: Regular Papers 55, no. 9 (October 2008): 2884–97. http://dx.doi.org/10.1109/tcsi.2008.920985.

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37

Horikoshi, K., E. Yamazaki, T. Kobayashi, E. Yoshida, and Y. Miyamoto. "Spectrum-narrowing tolerant signal-processing algorithm using maximum-likelihood sequence estimation for coherent optical detection." Electronics Letters 47, no. 10 (2011): 609. http://dx.doi.org/10.1049/el.2011.0960.

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38

Harrold, W. "A new approximation to the symbol error probability for coded modulation schemes with maximum likelihood sequence detection." IEEE Transactions on Communications 37, no. 4 (April 1989): 340–52. http://dx.doi.org/10.1109/26.20114.

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39

Sibley, M. "Performance analysis of a dicode PPM system, operating over plastic optical fibre, using maximum likelihood sequence detection." IEE Proceedings - Optoelectronics 152, no. 6 (December 1, 2005): 337–43. http://dx.doi.org/10.1049/ip-opt:20050009.

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40

Nikolaidis, K., and M. J. N. Sibley. "Optimum mapping in an optical multiple pulse position modulation link using a maximum likelihood sequence detection scheme." IET Optoelectronics 3, no. 1 (February 1, 2009): 47–53. http://dx.doi.org/10.1049/iet-opt:20080002.

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41

Xiaoming Zhu and J. M. Kahn. "Markov chain model in maximum-likelihood sequence detection for free-space optical communication through atmospheric turbulence channels." IEEE Transactions on Communications 51, no. 3 (March 2003): 509–16. http://dx.doi.org/10.1109/tcomm.2003.809787.

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42

Foggi, T., E. Forestieri, G. Colavolpe, and G. Prati. "Maximum-likelihood sequence detection with closed-form metrics in OOK optical systems impaired by GVD and PMD." Journal of Lightwave Technology 24, no. 8 (August 2006): 3073–87. http://dx.doi.org/10.1109/jlt.2006.876898.

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43

Hu, Zhongfeng, and Xiaodi Huang. "A Novel Vehicle Gearbox Fault Diagnosis Approach Based on Collective Anomaly Detection." E3S Web of Conferences 252 (2021): 01052. http://dx.doi.org/10.1051/e3sconf/202125201052.

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Targeting the problem of gearbox fault diagnosis, we proposed a novel semi-supervised approach based on collective anomaly detection. Based on the limited sample data, the principle of the approach is to detect whether a test dataset contains abnormal patterns by using data distribution as the metric. The sequence obeying unexpected distribution will be identified as collective anomaly, which may be generated by fault patterns. The approach consists of three steps. First, the mixture of multivariate Gaussian distribution is used to fit the structure of sample dataset and test dataset. Then, based on maximum likelihood estimate algorithm, we hope to search the optimal parameters which can fit the data distribution with the highest degree. Finally, the fixed point iteration algorithm is used to solve likelihood estimate functions. Experimental results demonstrate that the proposed approach can be used to find fault patterns of gearbox without the prior knowledge of their generated mechanisms.

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44

Gazor, S., M. Derakhtian, and A. A. Tadaion. "Computationally Efficient Maximum Likelihood Sequence Estimation and Activity Detection for $M$-PSK Signals in Unknown Flat Fading Channels." IEEE Signal Processing Letters 17, no. 10 (October 2010): 871–74. http://dx.doi.org/10.1109/lsp.2010.2062891.

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45

KIM, JAN T., JAN E. GEWEHR, and THOMAS MARTINETZ. "BINDING MATRIX: A NOVEL APPROACH FOR BINDING SITE RECOGNITION." Journal of Bioinformatics and Computational Biology 02, no. 02 (June 2004): 289–307. http://dx.doi.org/10.1142/s0219720004000569.

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Recognition of protein-DNA binding sites in genomic sequences is a crucial step for discovering biological functions of genomic sequences. Explosive growth in availability of sequence information has resulted in a demand for binding site detection methods with high specificity. The motivation of the work presented here is to address this demand by a systematic approach based on Maximum Likelihood Estimation. A general framework is developed in which a large class of binding site detection methods can be described in a uniform and consistent way. Protein-DNA binding is determined by binding energy, which is an approximately linear function within the space of sequence words. All matrix based binding word detectors can be regarded as different linear classifiers which attempt to estimate the linear separation implied by the binding energy function. The standard approaches of consensus sequences and profile matrices are described using this framework. A maximum likelihood approach for determining this linear separation leads to a novel matrix type, called the binding matrix. The binding matrix is the most specific matrix based classifier which is consistent with the input set of known binding words. It achieves significant improvements in specificity compared to other matrices. This is demonstrated using 95 sets of experimentally determined binding words provided by the TRANSFAC database.

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46

Bagde, Vandana, and Dethe C. G. "Performance improvement of space diversity technique using space time block coding for time varying channels in wireless environment." International Journal of Intelligent Unmanned Systems 10, no. 2/3 (June 8, 2020): 278–86. http://dx.doi.org/10.1108/ijius-04-2019-0026.

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PurposeA recent innovative technology used in wireless communication is recognized as multiple input multiple output (MIMO) communication system and became popular for quicker data transmission speed. This technology is being examined and implemented for the latest broadband wireless connectivity networks. Though high-capacity wireless channel is identified, there is still requirement of better techniques to get increased data transmission speed with acceptable reliability. There are two types of systems comprising of multi-antennas placed at transmitting and receiving sides, of which first is diversity technique and another is spatial multiplexing method. By making use of these diversity techniques, the reliability of transmitting signal can be improved. The fundamental method of the diversity is to transform wireless channel such as Rayleigh fading into steady additive white Gaussian noise (AWGN) channel which is devoid of any disastrous fading of the signal. The maximum transmission speed that can be achieved by spatial multiplexing methods is nearly equal to channel capacity of MIMO. Conversely, for diversity methods, the maximum speed of broadcasting is much lower than channel capacity of MIMO. With the advent of space–time block coding (STBC) antenna diversity technique, higher-speed data transmission is achievable for spatially multiplexed multiple input multiple output (SM-MIMO) system. At the receiving end, detection of the signal is a complex task for system which exhibits SM-MIMO. Additionally, a link modification method is implemented to decide appropriate coding and modulation scheme such as space diversity technique STBC to use two-way radio resources efficiently. The proposed work attempts to improve detection of signal at receiving end by employing STBC diversity technique for linear detection methods such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC) and maximum likelihood detection (MLD). The performance of MLD has been found to be better than other detection techniques.Design/methodology/approachAlamouti's STBC uses two transmit antennas regardless of the number of receiver antennas. The encoding and decoding operation of STBC is shown in the earlier cited diagram. In the following matrix, the rows of each coding scheme represent a different time instant, while the columns represent the transmitted symbols through each different antenna. In this case, the first and second rows represent the transmission at the first and second time instant, respectively. At a time t, the symbol s1 and symbol s2 are transmitted from antenna 1 and antenna 2, respectively. Assuming that each symbol has duration T, then at time t + T, the symbols –s2* and s1*, where (.)* denotes the complex conjugate, are transmitted from antenna 1 and antenna 2, respectively. Case of one receiver antenna: The reception and decoding of the signal depend on the number of receiver antennas available. For the case of one receiver antenna, the received signals are received at antenna 1 , hij is the channel transfer function from the jth transmit antenna and the ith receiver antenna, n1 is a complex random variable representing noise at antenna 1 and x (k) denotes x at time instant k ( at time t + (k – 1)T.FindingsThe results obtained for maximal ratio combining (MRC) with 1 × 4 scheme show that the BER curve drops to 10–4 for signal-to-noise (SNR) ratio of 10 dB, whereas for MRC 1 × 2 scheme, the BER drops down to 10–5 for SNR of 20 dB. Results obtained in Table 1 show that when STBC is employed for MRC with 1 × 2 scheme (one antenna at transmitter node and two antennas at receiver node), BER curve comes down to 0.0076 for Eb/N0 of 12. Similarly, when MRC with 1 × 4 antenna scheme is implemented, BER drops down to 0 for Eb/N0 of 12. Thus, it can be concluded from the obtained graph that the performance of MRC with STBC gives improved results. When STBC technique is used with 3 × 4 scheme, at SNR of 10 dB, BER comes nearer to 10–6 (figure 7.3). It can be concluded from the analytics observed between AWGN and Rayleigh fading channel that for AWGN channel, BER is found to be equal to 0 for SNR value of 13.5 dB, whereas for Rayleigh fading channel, BER is observed nearer to 10–3 for Eb/N0 = 15. Simulation results (in figure 7.2) from the analytics show BER drops to 0 for SNR value of 12 dB.Research limitations/implicationsOptimal design and successful deployment of high-performance wireless networks present a number of technical challenges. These include regulatory limits on useable radio-frequency spectrum and a complex time-varying propagation environment affected by fading and multipath. The effect of multipath fading in wireless systems can be reduced by using antenna diversity. Previous studies show the performance of transmit diversity with narrowband signals using linear equalization, decision feedback equalization, maximum likelihood sequence estimation (MLSE) and spread spectrum signals using a RAKE receiver. The available IC techniques compatible with STBC schemes at transmission require multiple antennas at the receiver. However, if this not a strong constraint at the base station level, it remains a challenge at the handset level due to cost and size limitation. For this reason, SAIC technique, alternative to complex ML multiuser demodulation technique, is still of interest for 4G wireless networks using the MIMO technology and STBC in particular. In a system with characteristics similar to the North American Digital mobile radio standard IS-54 (24.3 K symbols per sec. with an 81 Hz fading rate), adaptive retransmission with time deviation is not practical.Practical implicationsThe evaluation of performance in terms of bit error rate and convergence time which estimates that MLD technique outperforms in terms of received SNR and low decoding complexity. MLD technique performs well but when higher number of antennas are used, it requires more computational time and thereby resulting in increased hardware complexity. When MRC scheme is implemented for singe input single output (SISO) system, BER drops down to 10–2 for SNR of 20 dB. Therefore, when MIMO systems are employed for MRC scheme, improved results based on BER versus SNR are obtained and are used for detecting the signal; comparative study based on different techniques is done. Initially ZF detection method is utilized which was then modified to ZF with successive interference cancellation (ZFSIC). When successive interference cancellation scheme is employed for ZFSIC, better performance is observed as compared to the estimation of ML and MMSE. For 2 × 2 scheme with QPSK modulation method, ZFSIC requires more computational time as compared to ZF, MMSE and ML technique. From the obtained results, the conclusion is that ZFSIC gives the improved results as compared to ZF in terms of BER ratio. ZF-based decision statistics can be produced by the detection algorithm for a desired sub-stream from the received vector whichs consist of an interference which occurred from previous transmitted sub-streams. Consequently, a decision on the secondary stream is made and contribution of the noise is regenerated and subtracted from the vector received. With no involvement of interference cancellation, system performance gets reduced but computational cost is saved. While using cancellation, as H is deflated, coefficients of MMSE are recalculated at each iteration. When cancellation is not involved, the computation of MMSE coefficients is done only once, because of H remaining unchanged. For MMSE 4 × 4 BPSK scheme, bit error rate of 10–2 at 30 dB is observed. In general, the most thorough procedure of the detection algorithm is the computation of the MMSE coefficients. Complexity arises in the calculation of the MMSE coefficients, when the antennas at the transmitting side are increased. However, while implementing adaptive MMSE receivers on slow channel fading, it is probable to recover the signal with the complications being linear in the antennas of transmitter node. The performance of MMSE and successive interference cancellation of MMSE are observed for 2 × 2 and 4 × 4 BPSK and QPSK modulation schemes. The drawback of MMSE SIC scheme is that the first detected signal observes the noise interference from (NT-1) signals, while signals processed from every antenna later observe less noisy interference as the process of cancellation progresses. This difficulty could be overcome by using OSIC detection method which uses successive ordering of the processed layers in the decreasing power of the signal or by power allocation to the signal transmitted depending on the order of the processing. By using successive scheme, a computation of NT delay stages is desired to bring out the abandoned process. The work also includes comparison of BER with various modulation schemes and number of antennas involved while evaluating the performance. MLD determines the Euclidean distance among the vector signal received and result of all probable transmitted vector signals with the specified channel H and finds the one with the minimum distance. Estimated results show that higher order of the diversity is observed by employing more antennas at both the receiving and transmitting ends. MLD with 8 × 8 binary phase shift keying (BPSK) scheme offers bit error rate near to 10–4 for SNR (16 dB). By using Altamonti space ti.Social implicationsIt should come as no surprise that companies everywhere are pushing to get products to market faster. Missing a market window or a design cycle can be a major setback in a competitive environment. It should be equally clear that this pressure is coming at the same time that companies are pushing towards “leaner” organizations that can do more with less. The trends mentioned earlier are not well supported by current test and measurement equipment, given this increasingly high-pressure design environment: in order to measure signals across multiple domains, multiple pieces of measurement equipment are needed, increasing capital or rental expenses. The methods available for making cross-domain, time-correlated measurements are inefficient, reducing engineering efficiency. When only used on occasion, the learning curve to understand how to use equipment for logic analysis, time domain and RF spectrum measurements often requires an operator to re-learn each piece of separate equipment. The equipment needed to measure wide bandwidth, time-varying spectral signals is expensive, again increasing capital or rental expenses. What is needed is a measurement instrument with a common user interface that integrates multiple measurement capabilities into a single cost-effective tool that can efficiently measure signals in the current wide-bandwidth, time-correlated, cross-domain environments. The market of wireless communication using STBCs has large scope of expansion in India. Therefore, the proposed work has techno-commercial potential and the product can be patented. This project shall in turn be helpful for remote areas of the nearby region particularly in Gadchiroli district and Melghat Tiger reserve project of Amravati district, Nagjira and so on where electricity is not available and there is an all the time problem of coverage in getting the network. In some regions where electricity is available, the shortage is such that they cannot use it for peak hours. In such cases, stand-alone space diversity technique, STBC shall help them to meet their requirements in making connection during coverage problem, thereby giving higher data transmission rates with better QOS (quality of service) with least dropped connections. This trend towards wireless everywhere is causing a profound change in the responsibilities of embedded designers as they struggle to incorporate unfamiliar RF technology into their designs. Embedded designers frequently find themselves needing to solve problems without the proper equipment needed to perform the tasks.Originality/valueWork is original.

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Shen, Zhi Xiang, Hong Yi Yu, Xiao Yi Zhang, and Yun Peng Hu. "Iterative ML Symbol Detection without Timing and Phase Synchronization." Advanced Materials Research 998-999 (July 2014): 878–83. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.878.

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This paper deals with maximum-likelihood (ML) detection of symbol sequence in the absence of synchronization information. A novel iterative scheme is proposed to obtain the ML estimates of the symbols without an estimation of synchronization parameters. Instead of the optimal sampling point recovery and explicit carrier phase compensation, the detection of symbols employs the direct calculation of the matched filter output, eliminating the need for a separate synchronizer. The detection problem is treated as ML estimation from incomplete data, which is solved by means of an iterative scheme based on the expectation-maximization algorithm. The proposed scheme is compared with conventional non-data-aided and iterative ML synchronizers. Accordingly, the simulation results indicate that the proposed detector enables improvements on both the bit error rate and convergence property.

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Ansari, I., and R. Viswanathan. "Performance study of maximum likelihood receivers and transversal filters for the detection of direct sequence spread spectrum signal in narrowband interference." IEEE Transactions on Communications 42, no. 2/3/4 (February 1994): 1939–46. http://dx.doi.org/10.1109/tcomm.1994.582904.

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Arisuryanti, Tuty, Yenita Rumahorbo, Febrina Amaliya Rha’ifa, and Lukman Hakim. "Detection of 16S mitochondrial sequence polymorphism and haplotype network of Ophiocara porocephala (Valenciennes, 1837) from Tekolok Estuary (NTB, Indonesia) using DnaSP and NETWORK." BIO Web of Conferences 28 (2020): 01002. http://dx.doi.org/10.1051/bioconf/20202801002.

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The two genetic software, DnaSP and NETWORK, is commonly used to analyse gene polymorphism and haplotype network which is useful for the understanding pattern of genetic variation and genetic relationship. In this study, the two software were applied to detect polymorphism of 16S sequence gene of Ophiocara paracephala from Tekolok Estuary (NTB, Indonesia) which has not been investigated. This study used a PCR method with 16Sar and 16Sbr primers. The results revealed two haplotypes and two variable sites with one parsimony informative within O.paracephala from Tekolok Estuary population. Next, if the 16S sequence data of O.paracephala from Tekolok Estuary was combined with the 16S gene data of O.paracephala from GenBank, three haplotypes were detected with five variables sites and one parsimony informative. This finding showed intra-population and intraspecific genetic variation of O.paracephala. In addition, haplotype network using NETWORK and a phylogenetic tree using Neighbor Joining and Maximum Likelihood methods exhibited that O.paracephala from Tekolok Estuary has a close genetic relationship with O.paracephala from Japan.

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Ma, Bo, Mingyang Wu, Zhilu Wu, Zhendong Yin, and Tao Shen. "GMM-MUD: An Effective Multiuser Detection Algorithm for DS-UWB-Based Space Formation Flying Systems." Mathematical Problems in Engineering 2019 (November 20, 2019): 1–10. http://dx.doi.org/10.1155/2019/4350794.

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In this paper, an effective multiuser detection (MUD) is proposed for direct sequence ultrawideband- (DS-UWB-) based space formation flying systems. The proposed method called GMM-MUD is based on Gaussian mixture models (GMMs) to suppress multiple access interference. The GMM describes probability distributions of the hypothesis testing problem which is used for bit classification. To reveal the difference between correct bits and error bits, the preprocessing operation applies a mapping function based on optimal multiuser detection. The parameters of GMM are estimated by using expectation-maximization (EM) algorithm. EM algorithm employs iterative operation to simplify the complexity of maximum likelihood estimation method and considers the mapping values of received bits as the observations. Simulation results demonstrate that the proposed GMM-MUD algorithm achieves good performances in terms of bit error rate performance, user capacity, and near-far resistance. Moreover, the computational complexity is low enough for space formation flying applications.

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