Skip to content

Advertisement

  • Research Article
  • Open Access

Optimal Design of Noisy Transmultiplexer Systems

EURASIP Journal on Advances in Signal Processing20062006:064645

https://doi.org/10.1155/ASP/2006/64645

  • Received: 31 October 2004
  • Accepted: 19 September 2005
  • Published:

Abstract

An optimal design method for noisy transmultiplexer systems is presented. For a transmultiplexer system with given transmitters and desired crosstalk attenuation, we address the problem of minimizing the reconstruction error while ensuring that the crosstalk of each band is below a prescribed level. By employing the mixed optimization, we will ensure that the system with suboptimal reconstruction error is more robust and less sensitive to the changes of input signals and channel noises. Due to the overlapping of adjacent subchannels, crosstalk between adjacent channels is expected. And the problem of crosstalk attenuation is formulated as an optimization problem, solved in terms of linear matrix inequalities (LMIs). The simulation examples demonstrate that the proposed design performs better than existing design methods.

Keywords

  • Attenuation
  • Information Technology
  • Optimal Design
  • Input Signal
  • Quantum Information

Authors’ Affiliations

(1)
Signal Processing Group, Institute of Physics, University of Oldenburg, Oldenburg, 26111, Germany
(2)
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore

References

  1. Bellanger M, Daguet JL: TDM-FDM transmultiplexer: digital polyphase and FFT. IEEE Transactions on Communications 1974, 22(9):1199–1205. 10.1109/TCOM.1974.1092391View ArticleGoogle Scholar
  2. Lin Y-P, Phoong S-M: ISI-free FIR filterbank transceivers for frequency-selective channels. IEEE Transactions on Signal Processing 2001, 49(11):2648–2658. 10.1109/78.960412View ArticleGoogle Scholar
  3. Vetterli M: A theory of multirate filter banks. IEEE Transactions on Acoustics, Speech, and Signal Processing 1987, 35(3):356–372. 10.1109/TASSP.1987.1165137View ArticleGoogle Scholar
  4. Scheuermann H, Göckler H: A comprehensive survey of digital transmultiplexing methods. Proceedings of the IEEE 1981, 69(11):1419–1450.View ArticleGoogle Scholar
  5. Vaidyanathan PP: Multirate Systems and Filter Banks. Prentice-Hall, Englewood Cliffs, NJ, USA; 1993.MATHGoogle Scholar
  6. Vetterli M: Perfect transmultiplexers. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '86), April 1986, Tokyo, Japan 11: 2567–2570.View ArticleGoogle Scholar
  7. Koilpillai RD, Nguyen TQ, Vaidyanathan PP: Some results in the theory of crosstalk-free transmultiplexers. IEEE Transactions on Signal Processing 1991, 39(10):2174–2183. 10.1109/78.91174View ArticleGoogle Scholar
  8. Critchley J, Rayner PJW: Design methods for periodically time varying digital filters. IEEE Transactions on Acoustics, Speech, and Signal Processing 1988, 36(5):661–673. 10.1109/29.1576View ArticleGoogle Scholar
  9. Prater JS, Loeffler CM: Analysis and design of periodically time-varying IIR filters, with applications to transmultiplexing. IEEE Transactions on Signal Processing 1992, 40(11):2715–2725. 10.1109/78.165658View ArticleGoogle Scholar
  10. Liu T, Chen T: optimization applied to general transmultiplexer design. Proceedings of the 39th IEEE Conference on Decision and Control, December 2000, Sydney, NSW, Australia 5: 4314–4319.Google Scholar
  11. Lin Y-P, Phoong S-M: Perfect discrete multitone modulation with optimal transceivers. IEEE Transactions on Signal Processing 2000, 48(6):1702–1711. 10.1109/78.845928View ArticleGoogle Scholar
  12. Chen B-S, Chen L-M: Optimal reconstruction in multirate transmultiplexer systems under channel noise: Wiener separation filtering approach. Signal Processing 2000, 80(4):637–657. 10.1016/S0165-1684(99)00158-9View ArticleGoogle Scholar
  13. Chen B-S, Lin C-W, Chen Y-L: Optimal signal reconstruction in noisy filter bank systems: multirate Kalman synthesis filtering approach. IEEE Transactions on Signal Processing 1995, 43(11):2496–2504. 10.1109/78.482101View ArticleGoogle Scholar
  14. Chen B-S, Lin C-W: Optimal design of deconvolution filters for stochastic multirate signal systems. Signal Processing 1995, 47(3):287–305. 10.1016/0165-1684(95)00116-6MathSciNetView ArticleGoogle Scholar
  15. Lin C-W, Chen B-S: State space model and noise filtering design in transmultiplexer systems. Signal Processing 1995, 43(1):65–78. 10.1016/0165-1684(94)00144-OView ArticleGoogle Scholar
  16. Cheng Y-M, Chen B-S, Chen L-M: Minimax deconvolution design of multirate systems with channel noises: a unified approach. IEEE Transactions on Signal Processing 1999, 47(11):3145–3149. 10.1109/78.796451View ArticleGoogle Scholar
  17. Chen B-S, Tsai C-L, Chen Y-F: Mixedfiltering design in multirate transmultiplexer systems: LMI approach. IEEE Transactions on Signal Processing 2001, 49(11):2693–2701. 10.1109/78.960416View ArticleGoogle Scholar
  18. Gahinet P, Nemirovski A, Laub AJ, Chilali M: LMI Control Toolbox—for Use with MATLAB. The MathWorks, Natick, Mass, USA, 1995Google Scholar
  19. Al-Dhahir N, Cioffi JM: Optimum finite-length equalization for multicarrier transceivers. IEEE Transactions on Communications 1996, 44(1):56–64. 10.1109/26.476097View ArticleGoogle Scholar
  20. Boyd S, El Ghaoui L, Feron E, Balakrishnan V: Linear Matrix Inequalities in System and Control Theory. SIAM, Philadelphia, Pa, USA; 1994.View ArticleGoogle Scholar
  21. Chu LC, Brooke M: A study on multiuser DSL channel capacity with crosstalk environment. Proceedings of the IEEE Pacific Rim Conference on Communications, Computers and signal Processing (PACRIM '01), August 2001, Victoria, BC, Canada 1: 176–179.Google Scholar
  22. Zhang C, Liao Y: A sequentially operated periodic FIR filter for perfect reconstruction. Circuits, Systems, and Signal Processing 1997, 16(4):475–486. 10.1007/BF01198063MathSciNetView ArticleGoogle Scholar

Copyright

© Zhou and Xie 2006

Advertisement