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Crosstalk-aware dynamic spectrum management algorithm for green DSL systems

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Abstract

Dynamic spectrum management (DSM) techniques mitigate crosstalk in digital subscriber line (DSL) networks by adapting the transmit spectra to the actual noise and channel conditions. Conventional DSM schemes are designed based on single-objective optimization, either belonging to the rate-adaptive or margin-adaptive category. In this paper, an efficient crosstalk-aware DSM (CA-DSM) algorithm which jointly considers both the data rate and power is proposed to search for the best rate-power tradeoff solution based on the network conditions. The crosstalk-aware power strategy prevents transmitters which contribute excessive crosstalk from being allocated high power, thereby reducing the aggregate crosstalk noise in the system. A convex cost function is used to formulate the DSM optimization problem wherein two coefficients are introduced to make the CA-DSM algorithm adaptive to different network conditions. An iterative power update strategy is proposed for the CA-DSM algorithm to minimize the cost function. Convergence properties of the CA-DSM algorithm along with existence and uniqueness of optimal power solutions are examined analytically and illustrated graphically. Simulation results show that the proposed CA-DSM algorithm can provide a significantly better rate-power tradeoff performance compared to existing spectrum management schemes.

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References

  1. Witold, A. K., & Thomas, D. B. (2007). Performance evaluation study of signal design and equalization options for high-bit-rate digital subscriber line transceivers. International Journal Communications Systems, 5(1), 15–28.

    Google Scholar 

  2. Lee, J., Chung, S. T., & Cioffi, J. M. (2006). Optimal discrete bit-loading for DMT-based DSL systems with equal-length loops. IEEE Transaction on Communications, 54(10), 1760–1764.

    Article  Google Scholar 

  3. ANSI Standard T1.417-2001 (2001). Spectrum management for loop transmission systems.

  4. Starr, T., Sorbara, M., Cioffi, J. M., & Silverman, P. J. (2003). DSL Advances. New Jersey: Prentice-Hall.

    Google Scholar 

  5. Huberman, S., Leung, C., & Le-Ngoc, T. (2010). Dynamic spectrum management (DSM) algorithms for multi-user xDSL. IEEE Communications Surveys & Tutorials, 14(1), 109–130.

    Article  Google Scholar 

  6. Leung, C., Huberman, S., Khuong, H., & Tho, L. (2013). Vectored DSL: potential, implemetation issues and challenges. IEEE Communications Surveys & Tutorials, 15(4), 1907–1923.

    Article  Google Scholar 

  7. Yu, W., Ginis, G., & Cioffi, J. M. (2002). Distributed multiuser power control for digital subscriber lines. IEEE Journal on Selected Areas in Communications, 20(5), 1105–1115.

    Article  Google Scholar 

  8. Liu, Y., & Su, Z. (2007). Distributed dynamic spectrum management for digital subscriber lines. IEICE Transactions on Communications, E90B(3), 491–498.

    Article  Google Scholar 

  9. Lee, W., Kim, Y., Brady, M. H., & Cioffi, J. M. (2006). Band-preference dynamic spectrum management in a DSL environment. In IEEE global telecommunication conference (GLOBECOM 2006) (pp. 1–5).

  10. Noam, Y., & Leshem, A. (2009). Iterative power pricing for distributed spectrum coordination in DSL. IEEE Transaction on Communications, 57(4), 948–953.

    Article  Google Scholar 

  11. Xu, Y., Panigrahi, S., & Le-Ngoc, T. (2007). Selective iterative water-filling for digital subscriber lines (DSL). EURASIP Journal on Applied Signal Processing, 2007, 1–11.

    Google Scholar 

  12. Sharma, S., & Sahu, P. (2016). A dynamic spectrum management algorithm in VDSL systems. Turkish Journal of Electrical Engineering & Computer Sciences, 2016(24), 3483–3491.

    Article  Google Scholar 

  13. Verdyck, J., Blondia, C., & Moonen, M. (2016). Derivative based real-time spectrum coordination for DSL. In European signal processing conference (EUSIPCO 2016) (pp. 305–309).

  14. Cendrillon, R., Yu, W., Moonen, M., Verlinden, J., & Bostoen, T. (2006). Optimal multiuser spectrum management for digital subscriber lines. IEEE Transaction on Communications, 54(5), 922–933.

    Article  Google Scholar 

  15. Wei, S., Youming, L., & Miaoliang, Y. (2009). Low-complexity grouping spectrum management in multi-user DSL networks. In IEEE international conference on communications and mobile computing (CMC 2009) (pp. 381–385).

  16. Lanneer, W., Tsiaflakis, P., Maes, J., & Moonen, M. (2017). Linear and nonlinear precoding based dynamic spectrum management for downstream vectored G.fast transmission. IEEE Transaction on Communications, 65(3), 1247–1259.

  17. Wolkerstorfer, M., Statovci, D., & Nordström, T. (2008). Dynamic spectrum management for energy-efficient transmission in DSL. In l1th IEEE international conference on communication system (pp. 1015–1020).

  18. Nordström, T., Wolkerstorfer, M., & Statovci, D. (2009). Energy efficient power back-off management for VDSL2 transmission. In European signal processing conference (EUSIPCO 2009) (pp. 2097–2101).

  19. Monteiro, M., Lindqvist, N., & Klautau, A. (2009). Spectrum balancing algorithms for power minimization in DSL networks. In IEEE international conference on communications (ICC 2009) (pp. 1–5).

  20. Guenach, M., Nuzman, C., Maes, J., & Peeters, M. (2009). On power optimization in DSL systems. In IEEE international conference on communications (ICC 2009) (pp. 1–5).

  21. Cioffi, J. M., Jagannathan, S., Lee, W., Zou, H., Chowdhery, A., Rhee, W., Ginis, G., & Silverman, P. (2008). Greener copper with dynamic spectrum management. In IEEE global telecommunication conference (GLOBECOM 2008) (pp. 1–5).

  22. Chen, M., Ginis, G., & Mohseni, M. (2014). Dynamic upstream power back-off for mixtures of vectored and non-vectored VDSL. In IEEE international conference on acoustics, speech and signal processing (ICASSP 2014) (pp. 1–5).

  23. Hoang, T. (1998). Convex analysis and global optimization. Norwell: Kluwer Academic Publishers.

    Google Scholar 

  24. Cendrillon, R., Huang, J. W., Chiang, M., & Moonen, M. (2007). Autonomous spectrum balancing for digital subscriber lines. IEEE Transactions on Signal Processing, 55(8), 4241–4257.

    Article  Google Scholar 

  25. Golden, P., Dedieu, H., & Jacobsen, K. S. (2006). Fundamentals of DSL technology. Boca Raton: Auerbach.

    Book  Google Scholar 

  26. ETSI TR 101 830-2. (2008). Transmission and multiplexing (TM); access networks; spectral management on metallic access networks; Part 2: Technical methods for performance evaluations.

  27. Sorbara, M., Duvaut, P., Shmulyian, F., Singh, S., & Mahadevan, A. (2007). Construction of a DSL-MIMO channel model for evaluation of FEXT cancellation systems in VDSL2. In IEEE Sarnoff symposium (pp. 1–6).

  28. Ortega, J. M., & Rheinboldt, W. C. (1970). Iterative solution of nonlinear equations in several variables. New York: Academic Press.

    Google Scholar 

  29. Yates, R. D. (1995). A framework for uplink power control in cellular radio systems. IEEE Journal on Selected Areas in Communications, 13(7), 1341–1347.

    Article  Google Scholar 

  30. Lafata, P., & Jareš, P. (2008). Increasing the transmission capacity of digital subscriber lines with phantom circuit and crosstalk cancelation. Telecommunication Systems, 59(4), 429–436.

    Article  Google Scholar 

  31. Itu-T G.993.2. (2011). Series G: Transmission systems and media, digital systems and networks: Very high speed digital subscriber line transceivers 2 (VDSL2).

  32. Franco, C., Ennio, G., Paola, P., & Susanna, S. (2007). Proposal and performance evaluation of a packet over VDSL protocol for increasing throughput in the transmission of IP packets. International Journal Communications Systems, 17(4), 363–374.

    Google Scholar 

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Acknowledgements

This work was funded by Telekom Malaysia Berhad under the research grant TMRND/M/RFQ-02/2015.

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Authors and Affiliations

  1. Faculty of Engineering, Multimedia University, Jalan Multimedia, 63100, Cyberjaya, Selangor Darul Ehsan, Malaysia

    Chee Keong Tan & Teong Chee Chuah

  2. Telekom Research & Development Malaysia Sdn Bhd, Lingkaran Teknokrat Timur, 63000, Cyberjaya, Selangor, Malaysia

    Mohd Saiful Bahri

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  1. Chee Keong Tan
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  2. Teong Chee Chuah
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  3. Mohd Saiful Bahri
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Correspondence to Chee Keong Tan.

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Tan, C.K., Chuah, T.C. & Bahri, M.S. Crosstalk-aware dynamic spectrum management algorithm for green DSL systems. Telecommun Syst 67, 717–732 (2018). https://doi.org/10.1007/s11235-017-0366-4

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  • DOI: https://doi.org/10.1007/s11235-017-0366-4

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