Performance Evaluation of MC-CDMA Systems with Single User Detection Technique using Kernel and Linear Adaptive Method

• Autorzy: Fateh Rachid , Darif Anouar , Safi Said

Identyfikatory

DOI

10.26636/jtit.2021.151621

• Języki publikacji: EN

Abstrakty

EN

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 channel.

Słowa kluczowe

EN

BRAN channels; equalization; kernel method; MC-CDMA; reproducing kernel Hilbert space

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2021
• Tom: nr 4
• Strony: 1--11
• Opis fizyczny: Bibliogr. 45 poz., rys., tab.

Twórcy

autor

Fateh Rachid

• Laboratory of Innovation in Mathematics, Applications and Information Technologies (LIMATI), Multidisciplinary Faculty, Sultan Moulay Slimane University, Beni Mellal, Morocco

• https://orcid.org/0000-0002-0574-2105

autor

Darif Anouar

• Laboratory of Innovation in Mathematics, Applications and Information Technologies (LIMATI), Multidisciplinary Faculty, Sultan Moulay Slimane University, Beni Mellal, Morocco

• https://orcid.org/0000-0001-8026-9189

autor

Safi Said

• Laboratory of Innovation in Mathematics, Applications and Information Technologies (LIMATI), Multidisciplinary Faculty, Sultan Moulay Slimane University, Beni Mellal, Morocco

• https://orcid.org/0000-0003-3390-9037

Bibliografia

• [1] M. Pouliquen, T. Menard, E. Pigeon, O. Gehan, and A. Goudjil, „Recursive system identification algorithm using binary measurements", in European Control Conference (ECC), Aalborg, Denmark, 2016, pp. 1353-1358 (DOI: 10.1109/ECC.2016.7810477).
• [2] M. Zidane, S. Safi, M. Sabri, and A. Boumezzough, „Impulse response identification of minimum and non minimum phase channels", Int. J. of Adv. Sci. and Technol., vol. 64, 2014, pp. 59-72 (DOI: 10.14257/ijast.2014.64.06).
• [3] U. Soverini and T. Söderstr öm, „Frequency domain identification of FIR models in the presence of additive input-output noise", Automatica, vol. 115, pp. 108879, 2020 (DOI: 10.1016/j.automatica.2020.108879).
• [4] H. Zhang, T. Wang, and Y. Zhao, „Asymptotically efficient recursive identification of FIR systems with binary-valued observations", IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 51, no. 5, pp. 2687-2700, 2021 (DOI: 10.1109/TSMC.2019.2916022).
• [5] U. Soverini and T. Söderstr öm, „Frequency domain identification of ARX models in the presence of additive input-output noise", IFAC-PapersOnLine, vol. 50, no. 1, pp. 6226-6231, 2017 (DOI: 10.1016/j.ifacol.2017.08.1023).
• [6] R. Fateh and A. Darif, „Mean square convergence of reproducing kernel for channel identification: application to BRAN D channel impulse response", in Int. Conf. on Business Intell., Springer: Cham, Switzerland, 2021, pp. 284-293 (DOI: 10.1007/978-3-030-76508-8 20).
• [7] R. Fateh, A. Darif, and S. Safi, „Channel Identification of Non-linear Systems with Binary-Valued Output Observations Based on Positive Definite Kernels", in E3S Web of Conferences, EDP Sciences, vol. 297, pp. 01020, 2021 (DOI: 10.1051/e3sconf/202129701020).
• [8] S. Van Vaerenbergh, „Kernel methods for nonlinear identification, equalization and separation of signals", Ph.D. dissertation, Universidad de Cantabria, Santander, Spain, 2010 [Online]. Available: https://gtas.unican.es/files/pub/tesis Steven.pdf
• [9] R. Castro Garcia, „Structured nonlinear system identification Rusing kernel-based methods", Ph.D. dissertation, Faculty of Engineering Science, KU Leuven, Belgium, 2017 [Online]. Available: https://lirias.kuleuven.be/retrieve/473580
• [10] S. Gupta, A. K. Sahoo, and U. K. Sahoo, „Volterra and Wiener model based temporally and spatio-temporally coupled nonlinear system identification: a synthesized review", IETE Technical Review, 2020, pp. 1-25 (DOI: 10.1080/02564602.2020.1732233).
• [11] F. Pérez-Cruz and O. Bousquet, „Kernel methods and their potential use in signal processing", IEEE Signal Process. Mag., vol. 21, no. 3, pp. 57-65, 2004 (DOI: 10.1109/MSP.2004.1296543).
• [12] W. Liu, J. C. Principe, and S. Haykin, „Kernel adaptive filtering: a comprehensive introduction", vol. 57, John Wiley & Sons, 2011 (ISBN: 9780470447536).
• [13] N. Aronszajn, „Theory of reproducing kernels", Trans. of the American mathematical society, vol. 68, no. 3, pp. 337-404, 1950 (DOI: 10.2307/1990404).
• [14] S. Van Vaerenbergh and L. A. Azpicueta-Ruiz, „Kernel-based identification of Hammerstein systems for nonlinear acoustic echocancellation", in IEEE Int. Conf. on Acoustics, Speech and Signal Process. (ICASSP), Florence, Italy, 2014. pp. 3739-3743 (DOI: 10.1109/ICASSP.2014.6854300).
• [15] C. Richard, J. C. M. Bermudez, and P. Honeine, „Online Prediction of Time Series Data With Kernels", IEEE Trans. on Signal Process., vol. 57, no. 3, pp. 1058-1067, 2009 (DOI: 10.1109/TSP.2008.2009895).
• [16] O. A. Arqub and H. Rashaideh, „The RKHS method for numerical treatment for integrodifferential algebraic systems of temporal twopoint BVPs", Neural Computing and Applications, vol. 30, no. 8, pp. 2595-2606, 2018 (DOI: 10.1007/s00521-017-2845-7).
• [17] M. Boutalline, J. Antari, M. Gouskir, B. Bouikhalene, and S. Safi, „A robust approach for Proakis and BRAN channel identification and equalization of MC-CDMA systems", in 5th Int. Conf. on Optimization and App. (ICOA), Kenitra, Morocco, 2019, pp. 1-9 (DOI: 10.1109/ICOA.2019.8727665).
• [18] S. Safi, M. Frikel, M. Pouliquen, I. Badi, Y. Khmou, and M. Boutalline, „MC-CDMA system identification and equalization using the LMS algorithm and Takagi-Sugeno fuzzy system", IFAC Proc. Volumes, vol. 46, no. 11, pp. 599-604, 2013 (DOI: 10.3182/20130703-3-FR-4038.00027).
• [19] M. Zidane, S. Safi, M. Sabri, and A. Boumezzough, „Blind identification channel using higher order cumulants with application to equalization for MC-CDMA system", Int. J. of Elec., Robot., Electron. and Commun. Engin., vol. 8, no. 2, pp. 369-375, 2014 (DOI: 10.5281/zenodo.1091694).
• [20] M. S. Sakib and M. R. Ferdous, „Performance evaluation of MC-CDMA system for the next generation wireless network"', In Int. Conf. on Innovation in Engin. and Technol. (ICIET), Dhaka, Bangladesh, 2018, pp. 1-5 (DOI: 10.1109/CIET.2018.8660783).
• [21] M. Zidane, S. Safi, M. Sabri, A. Boumezzough, and M. Frikel, „Broadband radio access network channel identification and down link MC-CDMA equalization", Int. J. of Energy, Inform. and Commun., vol. 5, no. 2, pp. 13-34, 2014 (DOI: 10.14257/ijeic.2014.5.2.02).
• [22] S. Safi, M. Frikel, M. M'Saad, and A. Zeroual, „Blind identification and equalization of downlink TCM coded MC-CDMA systems using cumulants", in 16th European Signal Process. Conf., IEEE. Lausanne, Switzerland, 2008, pp. 1-5, 2008 (ISSN: 22195491).
• [23] M. Zidane, Mohammed, S. Safi, and M. Sabri, „Measured and estimated data of non-linear BRAN channels using HOS in 4G wireless communications", Data in brief, vol. 17, pp. 1136-1148, 2018 (DOI: 10.1016/j.dib.2018.02.005).
• [24] M. Zidane, S. Safi, and M. Sabri, „Compensation of fading channel using partial combining equalizer in MC-CDMA systems", J. of Telecommun. and Informat. Technol., no. 1, pp. 5-11, 2017 [Online]. Available: http://dlibra.itl.waw.pl/dlibra-webapp/Content/1962/ISSN 1509-4553 1 2017 5.pdf
• [25] S. Chitra, and N. Kumaratharan, „Multimedia transmission in MCCDMA using adaptive subcarrier power allocation and CFO compensation", Int. J. of Electron., vol. 105, no. 2, pp. 289-302, 2018 (DOI: 10.1080/00207217.2017.1357201).
• [26] S. Hara and R. Prasad, „Overview of multicarrier CDMA", IEEE Commun. Mag., vol. 35, no. 12, pp. 126-133, 1997 (DOI: 10.1109/35.642841).
• [27] „Broadband radio access networks (BRAN); High performance radio logical area network (HIPERLAN) Type 2; Requirements and architectures for wireless broadband access", ETSI, 1999 [Online]. Available: https://www.etsi.org/deliver/etsi tr/101000 101099/101031/02.02.01 60/tr 101031v020201p.pdf
• [28] „Broadband radio access networks (BRAN); HIPERLAN Type 2; Physical layer", ETSI, 2001 [Online]. Available: https://www.etsi.org/deliver/etsi ts/101400 101499/101475/01.02.02 60/ts 101475v010202p.pdf
• [29] R. Martinek, J. Rzidky, R. Jaros, P. Bilik, and M. Ladrova, „Least mean squares and recursive least squares algorithms for total harmonic distortion reduction using shunt active power filter control", Energies, vol. 12, no. 8, pp. 1545, 2019 (DOI: 10.3390/en12081545).
• [30] S. Haykin, „Adaptive filter theory (4-th edition)", Prentice Hall, 2001 (ISBN: 9780130901262).
• [31] C. Cortes and V. Vapnik, „Support-vector networks", Machine Learning, vol. 20, no. 3, pp. 273-297, 1995 (DOI: 10.1007/BF00994018).
• [32] B. Schŏlkopf, A. J. Smola, and F. Bach, „Learning with Kernels: Support vector machines, regularization, optimization, and beyond", MIT Press, 2002 [Online]. Available: https://alex.smola.org/papers/2001/SchHerSmo01.pdf
• [33] B. Schŏlkopf, H. Ralf, and A. J. Smola, „A generalized representer theorem", Int. Conf. on Comput. Learning Theory, vol. 2111, Berlin, Springer, Heidelberg, pp. 416-426, 2001 (DOI: 10.1007/3-540-44581-1 27).
• [34] K. Slavakis, B. Pantelis, and S. Theodoridis, „Online learning In reproducing kernel Hilbert spaces", Signal Process. Theory and Machine Learning, pp. 883-987, 2013 (DOI: 10.1016/B978-0-12-396502-8.00017-6).
• [35] D. P. Wemerson, C. M. B. Jose, R. Cédric, and T. Jean-Yves, „Stochastic behavior analysis of the Gaussian kernel least-meansquare algorithm", IEEE Trans. on Signal Process., vol. 60, no. 5, pp. 2208-2222, 2012 (DOI: 10.1109/TSP.2012.2186132).
• [36] M. Kallas, „Méthodes à noyaux en reconnaissance de formes, prédiction et classification. Applications aux biosignaux", Ph.D. dissertation. Université de Technologie de Troyes, 2012 [Online]. Available: https://hal.archives-ouvertes.fr/tel-01088936 [in French].
• [37] W. Liu, P. P. Pokharel, and J. C. Principe, „The kernel least-meansquare algorithm", IEEE Trans. on Signal Process., vol. 56, no. 2, pp. 543-554, 2008 (DOI: 10.1109/TSP.2007.907881).
• [38] P. Kumari and R. Wadhvani, „Wind Power Prediction Using KLMS Algorithm", in Int. Conf. on Inventive Res. in Comput. App. (ICIRCA), Coimbatore, India, pp. 154-161, 2018 (DOI: 10.1109/ICIRCA.2018.8597419).
• [39] K. Li and C. P. Jose, „No-trick (treat) kernel adaptive filtering Rusing deterministic features", arXiv preprint arXiv:1912.04530, 2019 [Online]. Available: https://arxiv.org/pdf/1912.04530
• [40] J. Ahmed, and K. A. Hamdi, „Spectral efficiency of asynchronous MC-CDMA with frequency offset over correlated fading", IEEE Trans. On Vehicular Technol., vol. 62, no. 7, pp. 3423-3429, 2013 (DOI: 10.1109/TVT.2013.2253339).
• [41] M. Zidane and R. Dinis, „A new combination of adaptive channel estimation methods and TORC equalizer in MC-CDMA systems", Int. J. of Commun. Systems, vol. 33, no. 11, pp. e4429, 2020 (DOI: 10.1002/dac.4429).
• [42] M. S. Sakib and M. R. Ferdous, „Performance evaluation of MCCDMA system for the next generation wireless networks", In Int. Conf. on Innovation in Engin. and Technol. (ICIET), Dhaka, Bangladesh, pp. 1-5, 2018 (DOI: 10.1109/CIET.2018.8660783).
• [43] S. Safi, M. Frikel, A. Zeroual, and M. M'Saad, „Higher order cumulants for identification and equalization of multicarrier spreading spectrum systems", J. of Telecommun. and Informat. Technol., vol. 2, no. 1, pp. 74-84, 2011 [Online]. Available: https://www.itl.waw.pl/czasopisma/JTIT/2011/2/74.pdf
• [44] V. Le Nir, J. M. Auffray, M. Hélard, J. F. Hélard, and R. Le Gouable, „Combination of Space-Time Block Coding with MC-CDMA Technique for MIMO systems with two, three and four transmit antennas", IST Mobile & Wireless Commun. Summit, Aveiro, Portugal, 2003 [Online]. Available: https://hal.archives-ouvertes.fr/hal-00005810/document
• [45] S. Nobilet, „Etude et optimisation des techniques MC-CDMA pour les futures générations de systemes de communications hertziennes". Doctoral dissertation, INSA de Rennes, 2003 [Online]. Available: https://tel.archives-ouvertes.fr/tel-00004081/document [in French].

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).