nach oben

Wireless Personal Communications

Erschienen in:

09.08.2016

Power Optimization of Three Dimensional Turbo Code Using a Novel Modified Symbiotic Organism Search (MSOS) Algorithm

verfasst von: Subhabrata Banerjee, Sudipta Chattopadhyay

Erschienen in: Wireless Personal Communications | Ausgabe 3/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In modern communication system error-control coding scheme is used to elevate the immunity of noisy communication channel. Turbo code (TC) is considered as one of the significant channel coding schemes which approaches to the Shannon limit. An upgraded version of TC named as 3 dimensional turbo code (3D-TC) has been emerged as a challenging research area in recent past. Meanwhile, considerable improvement in bit error rate (BER) performance of the TC has been achieved by incorporating suitable optimization algorithms. Motivated by above research trends, a modified symbiotic organisms search (MSOS) algorithm has been proposed by changing the organism structure and selection criteria of a newly developed symbiotic organisms search (SOS) algorithm. Subsequently the proposed MSOS has been used to design an improved 3D-TC. Here an optimal power allocation scheme of a new class of 3 dimensional turbo encoder has been investigated to improve its BER characteristics mainly in high SNR regions. Furthermore, the BER performance of the proposed 3D-TC code has been compared with conventional 2D serially concatenated and parallel concatenated turbo code as well as conventional 3D-TC. Finally, the BER performance of the proposed MSOS optimized 3D-TC has been compared with the SOS optimized 3D-TC and harmony search optimized 3D-TC.

Vorheriger Artikel Improving Web Performance in Home Broadband Access Networks

Nächster Artikel Outage Probability of Cognitive Selective DF Relay Networks with Multiple Primary Nodes and Heterogenous Non-Identical Constraints

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Berrou, C., Glavieux, A., & Thitimajshima, P. (1993). Near Shannon limit error correcting coding and decoding: Turbo codes. In Proceeding of IEEE international conference on communications (ICC’93), Geneva (Vol. 2, pp. 1064–1070). doi:10.1109/ICC.1993.397441.

Benedetto, S., & Montorsi, G. (1996). Design of parallel concatenated convolutional codes. IEEE Transactions on Communications, 44(5), 591–600. doi:10.1109/26.494303.CrossRefMATH

Benedetto, S., & Montorsi, G. (1996). Serial concatenation of interleaved codes: analytical performance bounds. In Proceeding of IEEE global telecommunications conference, (GLOBECOM’96) (Vol 1, pp. 106–110). doi:10.1109/GLOCOM.1996.594342.

Perez, L. C., Seghers, J., & Costello, D. J. (1996). A distance spectrum interpretation of turbo codes. IEEE Transactions on Information Theory, 42(6), 1698–1709. doi:10.1109/18.556666.MathSciNetCrossRefMATH

Hokfelt, J., & Maseng, T. (1996). Optimizing the energy of different bit streams of turbo codes. In Turbo coding seminar proceedings, Lund, Sweden (pp. 59–63).

Duman, T. M., & Salehi, M. (1997). On optimal power allocation for turbo codes. In Proceeding of IEEE international symposium on information theory, Ulm., Germany (p. 104). doi:10.1109/ISIT.1997.613019.

Takeshita, O. Y., Collins, O. M., Massey, P. C., & Costello, D. J. (1999). A note on asymmetric turbo-codes. IEEE Communication Letter, 3(3), 69–71. doi:10.1109/4234.752905.CrossRef

Salah, M. M., Raines, R. A., Temple, M. A., & Bailey, T. G. (2000). Energy allocation strategies for turbo codes with short frames. In Proceedings of IEEE information technology: coding and computing (pp. 408–11). doi:10.1109/ITCC.2000.844262.

Ahuja, S. S., & Sharma, V. (2002). Optimal power control for convolutional and turbo codes over fading channels. In Proceedings of IEEE global telecommunications conference, (GLOBECOM’02) (Vol. 2, pp. 1249–1253). doi:10.1109/GLOCOM.2002.1188397.

10.

Rangarajan, A., Singh, S. K., & Sharma, V. (2003). Power allocation policies for convolutional and turbo coded systems over fading channels. In Proceedings of conference on convergent technologies for the Asia-Pacific Region (Vol. 1, pp. 155–159). doi:10.1109/TENCON.2003.1273302.

11.

Ramasamy, K., Balamuralithara, B., & Siddiqi, M. U. (2009). Optimal power allocation for the proposed asymmetric turbo code for 3G systems. International Journal of Electronics and Communication (AEÜ), 63(7), 551–561. doi:10.1016/j.aeue.2008.04.003.CrossRef

12.

Li, J., Narayanan, K. R., & Georghiades, C. N. (2004). Product accumulate codes: A class of codes with near-capacity performance and low decoding complexity. IEEE Transactions on Information Theory, 50(1), 31–46. doi:10.1109/TIT.2003.821995.MathSciNetCrossRefMATH

13.

Gonzalez, H., Berrou, C., & Kerouédan, S. (2004). Serial/parallel (s/p) turbo codes for low error rates. In Proceedings of IEEE international conference on communication (ICC’04), Paris, France (Vol. 1, pp. 346–350). doi:10.1109/ICC.2004.1312508.

14.

Berrou, C., i Amat, A. G., Ould-Cheikh-Mouhamedou, Y., Douillard, C., & Saouter, Y. (2007). Adding a rate-1 third dimension to turbo codes. In Proceedings of IEEE information theory workshop (ITW’07), Lake Taho, CA (pp. 156–161). doi:10.1109/ITW.2007.4313066.

15.

Rosnes, E. (2008). Minimum distance upper bounds for 3-dimensional turbo codes using quadratic permutation polynomial interleavers. In Proceedings of IEEE 5th international symposium on turbo codes and related topics (pp. 420–425). doi:10.1109/TURBOCODING.2008.4658736.

16.

Ismail, D. K. B., Douillard, C., & Kerouédan, S. (2009). Improving 3-dimensional turbo codes using 3GPP2 interleavers. In Proceedings of IEEE 1st international conference on communications and networking (pp. 1–7). doi:10.1109/COMNET.2009.5373557.

17.

Berrou, C., i Amat, A. G., Ould-Cheikh-Mouhamedou, Y., & Saouter, Y. (2009). Improving the distance properties of turbo codes using a third component code: 3D turbo codes. IEEE Transactions on Communication, 57(9), 2505–2509. doi:10.1109/TCOMM.2009.09.070521.CrossRef

18.

i Amat, A. G., & Rosnes, E. (2010). Analysis of 3-dimensional turbo code ensembles. In Proceedings of IEEE information theory workshop (ITW 2010), Cairo, (pp. 1–5). doi:10.1109/ITWKSPS.2010.5503177.

19.

Feldman, J. (2003). Decoding error-correcting codes via linear programming. Ph.D. dissertation, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT), Cambridge, MA.

20.

Rosnes, E., Helmling, M., & i Amat, A. G. (2011). Pseudo code words of linear programming decoding of 3-dimensional turbo codes. In Proceedings of IEEE international symposium on information theory (ISIT), (pp. 1643–1647). doi:10.1109/ISIT.2011.6033823.

21.

Kbaier, D., Douillard, C., & Kerouedan, S. (2012). Analysis of three-dimensional turbo codes. Annales des Telecommunications, 67(5–6), 257–268.CrossRef

22.

Rosnes, E., Helmling, M., & i Amat, A. G. (2014). Minimum pseudoweight analysis of 3-dimensional turbo codes. IEEE Transactions on Communications, 62(7), 2170–2182. doi:10.1109/TCOMM.2014.2329690.CrossRef

23.

Snášel, V., Platoš, J., Krömer, P., & Ouddane, V. (2008). Genetic algorithms searching for turbo code interleaver, and solving linear ordering problem. In Proceedings of IEEE 7th computer information systems and industrial management applications (CISIM’08), (pp. 71–77). doi:10.1109/CISIM.2008.32.

24.

Snasel, V., Platos, J., Kromer, P., Ouddane, N., & Abraham, A. (2010). Interleaver optimization by population based metaheuristics. In Proceedings of IEEE 2nd world congress on nature and biologically inspired computing (NaBIC) (pp. 672–677). doi:10.1109/NABIC.2010.5716363.

25.

Banerjee, S., & Chattopadhyay, S. (2014). Design of parallel concatenated convolution turbo code using harmony search algorithm. In Proceedings of IEEE international conference on power, control and embedded systems (ICPCES) (pp. 1–6). doi:10.1109/ICPCES.2014.7062810.

26.

Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A new heuristic optimization algorithm: Harmony search. Simulation, 76(2), 60–68.CrossRef

27.

Banerjee, S., & Chattopadhyay, S. (2014). A novel asymmetric turbo code using cuckoo search algorithm. In Proceedings of IEEE India conference (INDICON) (pp. 1–6). doi:10.1109/INDICON.2014.7030640.

28.

Yang, X.-S., & Deb, S. (2009). Cuckoo search via levy flights. In Proceedings of IEEE world congress on nature & biologically inspired computing (NaBIC 2009), USA (pp. 210–214) doi:10.1109/NABIC.2009.5393690.

29.

Cheng, M.-Y., & Prayogo, D. (2014). Symbiotic organisms search: A new meta-heuristic optimization algorithm. Computers and Structures, 139(15), 98–112. doi:10.1016/j.compstruc.2014.03.007.CrossRef

30.

Andersen, J. D. (1999). Selection of component codes for turbo coding based on convergence properties. Annals of Telecommunications, 54(3), 208–213.

31.

Benedetto, S., & Montorsi, G. (1996). Unveiling turbo codes: Some results on parallel concatenated coding schemes. IEEE Transactions on Information Theory, 42(2), 409–429. doi:10.1109/18.485713.CrossRefMATH

Titel: Power Optimization of Three Dimensional Turbo Code Using a Novel Modified Symbiotic Organism Search (MSOS) Algorithm
verfasst von: Subhabrata Banerjee
Sudipta Chattopadhyay
Publikationsdatum: 09.08.2016
Verlag: Springer US
Erschienen in: Wireless Personal Communications / Ausgabe 3/2017
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-016-3586-0

Neuer Inhalt

Bildnachweise

VDI-Icon, Profil Icon, inhalt2, Springer Professional Modul/© Springer Fachmedien Wiesbaden GmbH, Nachhaltigkeitsaward Key Visual/© Cometis AG/Global ESG Monitor | Daniel Rupp | Generiert mit KI, Search Icon, Banner Hanser, Beijing Auto Show 2024: Deutsche Hersteller wollen angreifen./© EKH-Pictures / Generated with AI / Stock.adobe.com, Buchstaben, die aus einem Megaphon kommen/© MicroStockHub/Getty Images/iStock, Digitale Lieferkette/© zapp2photo / stock.adobe.com, Zeitschrift Wissensmanagement Cover, PatentFit-Logo/© Springer Fachmedien Wiesbaden GmbH, Sustainibility Finance/© Robert Kneschke / stock.adobe.com / Springer Fachmedien Wiesbaden GmbH, Zukunftswerkstatt Sales Excellence 2024/© AndreyPopov / Getty Images / iStock, 2023_Antrieb/© supervisuell

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 3/2017

End-to-End Link Reliable Energy Efficient Multipath Routing for Mobile Ad Hoc Networks

Sensing Transmission Tradeoff Over Penalty for Miss Detection in Cognitive Radio Network

The Implications of Cognitive Femtocell Based Spectrum Allocation Over Macrocell Networks

PSO Based Sum Rate Optimization for MU-MIMO Linear Precoder with Imperfect CSI

Environment-Driven Opportunity Forwarding Cross-Layer Optimization for Ubiquitous Wireless Networks

PRIN: A Priority-Based Energy Efficient MAC Protocol for Wireless Sensor Networks Varying the Sample Inter-Arrival Time

Neuer Inhalt

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.