Pipelined architectures for the Frequency Domain linear equalizer

George Glentis; Kristina Georgoulakis

International Journal of Applied Mathematics and Computer Science (2006)

  • Volume: 16, Issue: 4, page 525-535
  • ISSN: 1641-876X

Abstract

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In this paper, novel pipelined architectures for the implementation of the frequency domain linear equalizer are presented. The Frequency Domain (FD) LMS algorithm is utilized for the adaptation of equalizer coefficients. The pipelining of the FD LMS linear equalizer is achieved by introducing an amount of time delay into the original adaptive scheme, and following proper delay retiming. Simulation results are presented that illustrate the performance of the effect of the time delay introduced into the adaptation algorithm. The proposed architectures for efficient pipelining of the FD LMS linear equalization algorithm are suitable for implementation on special purpose hardware by means of the ASIC, ASIP or FPGA VLSI processors.

How to cite

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Glentis, George, and Georgoulakis, Kristina. "Pipelined architectures for the Frequency Domain linear equalizer." International Journal of Applied Mathematics and Computer Science 16.4 (2006): 525-535. <http://eudml.org/doc/207811>.

@article{Glentis2006,
abstract = {In this paper, novel pipelined architectures for the implementation of the frequency domain linear equalizer are presented. The Frequency Domain (FD) LMS algorithm is utilized for the adaptation of equalizer coefficients. The pipelining of the FD LMS linear equalizer is achieved by introducing an amount of time delay into the original adaptive scheme, and following proper delay retiming. Simulation results are presented that illustrate the performance of the effect of the time delay introduced into the adaptation algorithm. The proposed architectures for efficient pipelining of the FD LMS linear equalization algorithm are suitable for implementation on special purpose hardware by means of the ASIC, ASIP or FPGA VLSI processors.},
author = {Glentis, George, Georgoulakis, Kristina},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {pipelined implementation; frequency domain LMS; adaptive equalization},
language = {eng},
number = {4},
pages = {525-535},
title = {Pipelined architectures for the Frequency Domain linear equalizer},
url = {http://eudml.org/doc/207811},
volume = {16},
year = {2006},
}

TY - JOUR
AU - Glentis, George
AU - Georgoulakis, Kristina
TI - Pipelined architectures for the Frequency Domain linear equalizer
JO - International Journal of Applied Mathematics and Computer Science
PY - 2006
VL - 16
IS - 4
SP - 525
EP - 535
AB - In this paper, novel pipelined architectures for the implementation of the frequency domain linear equalizer are presented. The Frequency Domain (FD) LMS algorithm is utilized for the adaptation of equalizer coefficients. The pipelining of the FD LMS linear equalizer is achieved by introducing an amount of time delay into the original adaptive scheme, and following proper delay retiming. Simulation results are presented that illustrate the performance of the effect of the time delay introduced into the adaptation algorithm. The proposed architectures for efficient pipelining of the FD LMS linear equalization algorithm are suitable for implementation on special purpose hardware by means of the ASIC, ASIP or FPGA VLSI processors.
LA - eng
KW - pipelined implementation; frequency domain LMS; adaptive equalization
UR - http://eudml.org/doc/207811
ER -

References

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  1. Arslan H. and Bottomley G.E. (2001): Channel estimation in narrowband wireless communication systems. - Wireless Comm. Mobile Comput., Vol. 1, No. 2, pp. 201-219. 
  2. Azadet K. and Nicole C. (1998): Low-power equalizer architectures forhigh-speed modems. - IEEE Comm. Mag., Vol. 36, No. 10, pp. 118-126. 
  3. Benedetto S. and Biglieri E. (1999): Principles of Digital Transmission:Width: Wireless Applications. - New York: Kluwer. Zbl0954.94004
  4. Benvenuto N. and Tomasin S. (2001): Frequency domain DFE: System design and comparison with OFDM. -Proc. IEEE 8-th Symp. Commun. and Vehic. Tech., SCVT, Benelux, Delft, The Netherlands. 
  5. Berberidis K., Rantos S. and Palicot J. (2004): A step-by-step quasi-Newton algorithm in the frequency domain and its application to adaptive channel equalization. - IEEE Trans. Signal Process., Vol. 52, No. 12, pp. 3335-3344. 
  6. Bilcu R., Kuosmanen P. and Egiazarian K. (2002): Channel equalization using a new transform domain LMS algorithm with adaptive step-size. - WSEAS Trans.Circ., Vol. 1, No. 1, pp. 113-118. 
  7. Bilcu R., Kuosmanen P. and Egiazarian K. (2003): Tracking time-varying channels with adaptive step-size transform domain LMS algorithm, In: Recent Advances in Intelligent Systems and Signal Processing (Mastorakis N. et al., Eds.). - Athens: WSEAS Press, pp. 104-109. 
  8. Chen S. and Zhang T. (2005): Self-timed dynamically pipelined adaptive signal processing system: A case study of DLMS equalizer for real channel. - IEEE Trans. Circuits Syst. I, Vol. 52, No. 7, pp. 1338-1347. 
  9. Denyer P. and Renshaw D. (1985): VLSI Signal Processing. A bit serialapproach. - Boston, MA: Addison-Wesley. 
  10. Douglas S.C., Zhu Q. and Smith K. (1998): A pipelined LMS adaptive FIR filter architecture without adaptation delay. - IEEE Trans. Signal Process.,Vol. 46, No. 3, pp. 775-779. 
  11. Farhang-Boroujeny B., Lee Y. and Ko C.C. (1996): Sliding transforms forefficient implementation of transform domain adaptive filters. - SignalProcess., Vol. 52, pp. 83-96. Zbl0872.94008
  12. Glentis G. (2001): Pipelined architectures for the TD LMS adaptive filter. - Proc. IEEE Int. Conf. s Acoust. Speech, Signal Proc., ICASSP, Salt Lake City, USA, pp. 1081-1084. 
  13. Glentis G. (2005): Pipelined architectures for transform domain LMS adaptive filtering. - J. Circ. Syst. Comput., Vol. 14, No. 3, pp. 553-580. 
  14. Glentis G., Berberidis K. and Theodoridis S. (1999): Efficient least squares adaptive algorithms for FIR transversal filtering: A unified view. - IEEE Signal Process. Mag., Vol. 16, No. 4, pp. 13-42. 
  15. Hadara A., Nishikawa K. and Kiya H. (1998): Pipelined architecture of the LMS adaptive digital filter with the mimimum output latency. - IEICE Trans. Fundam., Vol. E81-A, No. 8, pp. 1578-1584. 
  16. Haykin S. (1996): Adaptive Filter Theory, 3rd Edition. - New Jersey: Prentice Hall. Zbl0723.93070
  17. Huang Y. and Benesty J. (2003): A class of frequency-domain adaptive approaches to blind multichannel identification. - IEEE Trans. Signal Process., Vol. 51, No. 1, pp. 11-24. 
  18. Kalouptsidis N. and Theodoridis S. (1993): Adaptive System Identification andSignal Processing Algorithms. - Englewood Cliffs: Prentice Hall. Zbl0787.93096
  19. Kim C.H., Soeleman H. and Oy K. (2003): Ultra-low-power DLMS adaptive filter for hearing aid applications. - IEEE Trans. VLSI Syst., Vol. 11, No. 6, pp. 1058-1067. 
  20. Long G., Ling F. and Proakis J. (1989): The LMS algorithm with delayedcoefficients adaptation. - IEEE Trans. Acoust. Speech Signal Process., pp. 1397-1405. Zbl0693.93088
  21. Maginot S., Balestro F., Joanblanq C., Senn P. and Palicot J. (1991): A general-purpose high speed equalizer.- IEEE J. Solid State Circ., Vol. 26, pp. 209-215. 
  22. Matsubara K., Nishikawa K. and Kiya H. (1999): Pipelined LMS adaptive filter using a new look-ahead transformation. - IEEE Trans. Circuits Syst. II,Vol. 46, No. 1, pp. 61-55. 
  23. Moreli M., Sanguinetti L. and Mengali U. (2005): Channel estimation for adaptive frequency domain equalization. - IEEE Trans. Wireless Comm., Vol. 4, No. 5,pp. 2508-2518. 
  24. Narayan S., Peterson A.M. and Narasimba M.J. (1983): Transform domain LMS algorithm. - IEEE Trans. Acoust. Speech, Signal Processing, Vol. 31, pp. 609-615. 
  25. Quereshi S.U.H. (1985): Adaptive equalization. - Proc. IEEE,Vol. 73, No. 9, pp. 1349-1387. 
  26. Parhi K. (1999): VLSI Digital Signal Processing Systems: Design andImplementation. - New York: Wiley. 
  27. Picchi G. and Prati G. (1984): Self-orthogonalizing adaptive equalization in the discrete frequency domain. - IEEE Trans. Commun., Vol. 32, No. 4, pp. 371-379. 
  28. Pirsch P. (1998): Architectures for Digital Signal Processing. - Chichester: Wiley. 
  29. Proakis J. (1995): Digital Communications. 3-rd Ed. -New York: McGraw-Hill. 
  30. Ramanathan S. and Visvanathan V. (1999): Low-power pipelined LMS adaptive filter architectures with minimal adaptation delay. - Integration VLSI, Vol. 27, No. 1, pp. 1-32. Zbl0909.68022
  31. Rofougaran A., Chang G., Rael J.J., Chang J. Y.-C., Rofougaran M., Chang P.J., Djafari M., Min J.,Roth E.W., Abidi A.A. and Samueli H. (1998): A single chip 900 MHz spread spectrum wireless transceiver in iμm CMOS. Parts I and II. - IEEE J. Solid-State Circuits, Vol. 33, No. 4, pp. 515-547. 
  32. Santha K.R. and Vaidehi V. (2004): Design of synchronous and asynchronous architectures for DFT based adaptive equalizer. -Proc. IEEE Conf. SoutheastCon, Greensboro, NC, pp. 383-389. 
  33. Shamma M. (2002): Improving the speed and performance of adaptive equalizers via transform based adaptive filtering. - 14-th Int. Conf. Digital Signal Processing, DSP, Santorini-Hellas, Greece, Vol. 2, pp. 1301-1305. 
  34. Shanbhag N. and Im G.H. (1998): VLSI systems design of 51.84 Mb/s transceivers for ATM-LAN and broadband access. - IEEE Trans. Signal Process., Vol. 46, Issue 5, pp. 1403-1416. 
  35. Shynk J. (1992): Frequency-domain and multirate adaptive filtering. -IEEE Signal Process. Mag., Vol. 9, Issue 1, pp. 14-37. 
  36. Son S., Kim J., Lee Y., Kim H. and Park S. (2006): Frequency-domain equalization for distributed terrestrial DTV transmission environments. - IEEE Trans. Consum. Electron., Vol. 52, No. 1, pp. 59-67. 
  37. Thomas J. (1996): Pipelined systolic architectures for DLMS adaptive filtering.- J. VLSI Signal Process., Vol. 12, No. 3, pp. 223-246. 
  38. Ting L., Woods R. and Cowan C. (2005): Virtex FPGA implementation of a pipelined adaptive LMS predictor for electronic support measures receivers. - IEEE Trans. VLSI Syst., Vo. 13, No. 1, pp. 86-95. 
  39. Van L. and Feng W. (2001): An efficient systolic architecture for the DLMS adaptive filter and its applications. - IEEE Trans. Circ. Syst. II,Vol. 48, No. 4, pp. 359-366. 
  40. Yang Y., Park C. and Song J. (2004): Fast constant modulus in the DFT domain.- Proc. IEEE Conf. Radio and Wireless, RAWCON2004, Atlanta, GA, pp. 19-22. 
  41. Yi Y. and Woods R. (2006): Hierarchical synthesis of complex DSP functions using IRIS. - IEEE Trans. Computer. Aided Des. Integr. Circ. Syst.,Vol. 25, No. 5, pp. 806-820. 

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