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2003 | 13 | 4 | 549-566

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Implementation of adaptive generalized sidelobe cancellers using efficient complex valued arithmetic

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Low complexity realizations of Least Mean Squared (LMS) error, Generalized Sidelobe Cancellers (GSCs) applied to adaptive beamforming are considered. The GSC method provides a simple way for implementing adaptive Linear Constraint Minimum Variance (LCMV) beamformers. Low complexity realizations of adaptive GSCs are of great importance for the design of high sampling rate, and/or small size and low power adaptive beamforming systems. The LMS algorithm and its Transform Domain (TD-LMS) counterpart are considered for the adaptive processing task involved in the design of optimum GSC systems. Since all input signals are represented by complex variables, complex valued arithmetic is utilized for the realization of GSC algorithms, either on general purpose computers, or on dedicated VLSI ASICs. Using algorithmic strength reduction (SR) techniques, two novel algorithms are developed for efficient realizations of both LMS GSCs and TD-LMS GSC schemes. Both of the proposed algorithms are implemented using real valued arithmetic only, whilst reducing the number of multipliers by 25% and 20%, respectively. When VLSI implementation aspects are considered, both the proposed algorithms result in reduced power dissipation and silicon area realizations. The performance of the proposed realizations of the LMS based GSC methods is illustrated in the context of typical beamforming applications.








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  • TEI of Crete, Branch at Chania, Department of Electronics, 3 Romanou Str, Chania 73133, Crete, Greece


  • Ahlander A., Taveniku M. and Svensson B. (1996): A multiple SIMD approach to radar signal processing.—Proc. 10-th IEEE Region. Conf., Perth, Australia, pp. 852–857.
  • An J. and Champagne B. (1994): GSC realization using the twodimensional transform-domain LMS algorithm. — IEE Proc. Radar Sonar Navig., Vol. 141, No. 5, pp. 270–278.
  • Baghaie R. (1999): Applications of transformation techniques in CDMA receivers. — Proc. 42-nd IEEE Midwest Symp. Circuits and Systems’99, Conf., Las Cruces, Mexico, pp. 905–908.
  • Baghaie R. and Laakso T. (1998): Implementation of low-power CDMA RAKE receivers using strength reduction transformation. — Proc. IEEE Nordic Signal Processing Symp., Aalborg, Denmark, pp. 169–172.
  • Baillet S., Moscher J. and Leahy R. (2001): Electromagnetic brain mapping. — IEEE Signal Process. Mag., Vol. 18, No. 2, pp. 14–30.
  • Boukalov A. and Haggman S. (2000): System aspects of smartantenna technology in cellular wireless communications— An overview.—IEEE Trans. Micr. Theory Techn., Vol. 48, No. 6, pp. 919–929.
  • Buckley K. (1986): Broadband beamforming and the generalized sidelobe canceller. — IEEE Trans. Acoust. Speech Signal Process., Vol. 34, No. 5, pp. 1322–1323.
  • Buckley K. (1987): Spacial/spectral filtering with linearly constrained minimum variance beamformers. — IEEE Trans. Acoust. Speech Signal Process., Vol. 35, No. 3, pp. 249– 266.
  • Chang A. and Chiang C. (2002): Adaptive H1 robust beamforming for imperfect antenna array. — Signal Process., Vol. 82, No. 8, pp. 1183–1188.
  • Chandrakasan A. and Brodersen R. (1995): Minimizing power consumption in digital CMOS circuits. — Proc. IEEE, Vol. 83, No. 4, pp. 498–523, 12–31.
  • Chen Y.H. and Fang H.D. (1992): Frequency domain implementation of the Griffiths-Jim adaptive beamformer. — J. Acoust. Soc. Am., Vol. 91, No. 6, pp. 3354–3366.
  • Chryssomallis M. (2000): Smart antennas. — IEEE Antenn. Propag. Mag., Vol. 42, No. 3, pp. 129–136.
  • Chu Y. and Fang W. (1999): A novel wavelet-based generalized sidelobe canceller.—IEEE Antenn. Propag., Vol. 47, No. 9, pp. 1485–1494.
  • Compton R. (1988): Adaptive Antennas: Concepts and Applications. — Englewood Cliffs, NJ: Prentice-Hall.
  • Cox H., Zeskind R. and Owen M. (1987): Robust adaptive beamforming. — IEEE Trans. Acoust. Speech Sigal. Process., Vol. 35, No. 9, pp. 1365–1376.
  • Drabowitch S., Papiernik A., Griffiths H., Encinas J. and Smith B. (1998): Modern Antennas.— Chapman & Hall.
  • Farina R. (1992): Antenna-Based Signal Processing Techniques for Radar Systems. —Norwood, MA: Artech House.
  • Farina A., Saverione A. and Timmoneri, L., (1996): MVDR vectorial lattice applied to space-time processing for AEW radar with large instantaneous bandwidth. — IEE Proc. Radar Sonar Navig., Vol. 143, No. 1, pp. 41–46.
  • Farina A. and Timmoneri L. (1999): Real-time STAP techniques. — Electron. Comm. Eng. J., Vol. 11, No. 1, pp. 13–22.
  • Feldman D. and Griffiths L. (1994): A projection approach for robust adaptive beamforming. —IEEE Trans. Signal Process., Vol. 42, No. 4, pp. 867–876.
  • Frost O. (1972): An algorithm for linearly constrained adaptive array processing. — Proc. IEEE, Vol. 60, No. 8, pp. 926– 935.
  • Fudge G. and Linebarger D. (1994): A calibrated generalized sidelobe canceller for wideband beamforming. — IEEE Trans. Signal Process., Vol. 42, No. 10, pp. 2871–2875.
  • Haykin S. (1996): Adaptive Filter Theory, 3rd Ed.—Englewood Cliffs, NJ: Prentice Hall.
  • Hendon E. and Reed I. (1990): A new CFAR sidelobe canceller algorithm for radar. — IEEE Trans. Aerospace Electr. Syst., Vol. 26, No. 5, pp. 792–803.
  • Herbordt W. and Kellermann W. (2001): Efficient frequency domain realization of robust generalized sidelobe cancellers. — IEEE Conf. Multimedia Signal Process., Cannes, France, pp. 377–382.
  • Honig M. and Tsatsanis M. (2000): Multiuser CDMA receivers. —IEEE Signal Process. Mag., Vol. 17, No. 3, pp. 49–61.
  • Hoshuyama O., Sugiyama A. and Hirano A. (1999): A robust adaptive beamformer with a blocking matrix using coefficient constrained adaptive filters.—IEICE Trans. Fundament., Vol. E82-A, No. 4, pp. 640–647.
  • Hudson J. (1991): Adaptive Array Principles. — London, UK: IEE Press.
  • Huard K. and Yeh C. (1994): Gram-Schmidt forwardbackward Generalized Sidelobe Canceller.—IEEE Trans. Aerospace Electron. Syst., Vol. 30, No. 1, pp. 151–160.
  • Gannot S., Burshtein D. and Weinstein E. (2001): Signal enchancement using beamforming and nonstationarity with applications to speech. — IEEE Trans. Signal Process., Vol. 49, No. 8, pp. 1614–1626.
  • Gershman A. (1999): Robust adaptive beamforming in sensor arrays. — AEU-Int. J. Electron. Comm., Vol. 53, No. 6, pp. 305–314.
  • Ghorayeb S., Lord W. and Udpa S. (1994): Application of a beamforming technique to ultrasound imaging in nondestructive test. — IEEE Trans. Ultasonics Ferroel. Freq. Contr., Vol. 41, No. 2, pp. 199–208.
  • 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.
  • Godara L. (1997): Applications of antenna arrays to mobile communications, Part II: Beamforming and direction-ofarrival considerations. — Proc. IEEE, Vol. 85, No. 8, pp. 1195–1245.
  • Goldstein J., Williams D., Merserau R. and Holder E. (1994): Inter-space and intra-space transformation for sensor array processing.—Proc. Asilomar Conf. Signals, Systems, Computers, Pacific Grove, CA, pp. 638–642.
  • Griffiths L.J. and Jim C.W. (1982): An alternative approach to linearly constrained adaptive beamforming. — IEEE Trans. Antennas Propag., Vol. 30, No. 1, pp. 27–34.
  • Johnson D. and Dudgeon D. (1993): Array Signal Processing: Concepts and Techniques. — Prentice-Hall.
  • Joho M. and Moschytz G. (1997): Adaptive beamforming with partitioned frequency-domain filters.—Proc. IEEEWorkshop Applications of Signal Processing to Audio and Acoustics, NY, USA.
  • Kalouptsidis N. and Theodoridis S. (Eds.) (1993): Adaptive System Identification and Signal Processing Algorithms. — Prentice Hall.
  • Kim K., Park Y., Cha I. and Youn D. (1992): Adaptive multichannel lattice-escalator filter structure: An application to generalized sidelobe canceller. — IEEE Trans. Signal Process., Vol. 40, No. 7, pp. 1816–1819.
  • Kohno R. (1998): Spacial and temporal communication theory using adaptive antenna array. — IEEE Personal Comm., Vol. 5, No. 1, pp. 28–36.
  • Kogon S., Williams D. and Holder E. (1996): Beamspace techniques for hot clutter cancellation. — IEEE Int. Conf. Acoust. Speech Signal Process, Vol. 2, Atlanta, USA, pp. 1177–1180.
  • Krim H. and Viberg M. (1996): Two decades or array signal processing research: the parametric approach. — IEEE Signal Process. Mag., Vol. 13, No. 4, pp. 67–94.
  • Lamagna A. (1982): Fast computer algebra. — IEEE Comp., Vol. 15, No. 9, pp. 43–56.
  • Lee B., Chang B., Cha I., Kim W. and Youn D. (1987): Realization of a generalized sidelobe canceller. — IEEE Trans. Circ. Syst., Vol. 34, No. 7, pp. 759–764.
  • Lee T. and Tsai T. (2001): A beamspace-time interference canceling CDMA receiver for sectored communications in multipath environment. — IEEE J. Select. Areas Comm., Vol. 19, No. 7, pp. 1374–1384.
  • Leshem A., van der Veen A. and Boonstra A. (2000): Multichannel interference mitigation techniques in radio astronomy. — Astrophys. J. Suppl., Vol. 131, pp. 355–374.
  • Li L., Jeffs B., Poulsen A. and Warnick K. (2002): Analysis of adaptive array algorithm performance for satellite interference cancellation in radio astronomy. — Proc. XXVII URSI General Assembly, Maastricht, The Netherlands.
  • Li X. and Gaillard P. (1988): Broadband generalized sidelobe canceller using multichannel least squares lattice structure. — Proc. IEEE Conf. Acoust. Speach Signal Process, pp. 1248–1251.
  • Litva J. and Lo T. (1996): Digital Beamforming in Wireless Communications. —Norwood, MA: Artech House.
  • Long G., Ling F. and Proakis J. (1989): The LMS algorithm with delayed coefficients adaptation. — IEEE Trans. Acoust. Speech Sign. Process., Vol. 37, No. 9, pp. 1397–1405.
  • Long G., Ling F. and Proakis J. (1992): Corrections to ‘The LMS algorithm with delayed coefficients adaptation’. — IEEE Trans. Acoust. Speech Sign. Process., Vol. 40, No. 1, pp. 230–232.
  • Martinez D. (1999): Application of parallel processors to realtime sensor array processing. — Proc. 13th Int. Parallel Processing Symp. and 10th Symp. Parallel and Distrib. Process., San Juan, Puerto Rico, pp. 463–469.
  • Moon S., Han D. and Cho M., (2001): Frequency domain partially adaptive array algorithm conbined with CFAR technique. —Signal Process., Vol. 81, No. 9, pp. 1927–1934.
  • Monzingo R. and Miller T. (1980): Introduction to Adaptive Aarrays. —New York: Wiley.
  • Mucci R. (1984): A comparison of efficient beamforming algorithms, IEEE Trans. Acoust. Speech Signal Process., Vol. 32, No. 3, pp. 548–558.
  • Narayan S., Peterson A.M. and Narasimba M.J. (1983): Transform domain LMS algorithm. — IEEE Trans. Acoust. Speech Signal Process., Vol. 31, No. 3, pp. 609–615.
  • Nitzberg R. (1999): Radar Signal Processing and Adaptive Systems. —Norwood, MA: Artech House.
  • Parhi K. (1999): VLSI Digital Signal Processing Systems, Design and Implementation. —New York: Wiley.
  • Paulraj A. and Papadias C. (1997): Space-time processing for wireless communications. — IEEE Signal Process. Mag., Vol. 14, No. 5, pp. 49–83.
  • Perry R., Bull D. and Nix A. (1999): Efficient adaptive complex filtering algorithm with application to channel equalization. — IEE Proc.-Vis. Image Signal Process., Vol. 146, No. 2, pp. 57–64.
  • Pillai S. (1989): Array Signal Processing. — New York: Springer.
  • Rappaport T. (1998): Smart Antennas: Adaptive Arrays, Algorithms, and Wireless Position Location. —IEEE Press.
  • Scott I. and Mulgrew B. (1995): Sparse LCMV beamforming design for suppression of ground clutter in airborn radar. —IEEE Trans. Signal Process., Vol. 43, No. 12, pp. 2843– 2852.
  • Shanbhag N. (1998): Algorithmic transformation techniques for low-power wireless VLSI systems design. — Int. J. Wireless Inf. Netw., Vol. 5, No. 2, pp. 147–171.
  • Shynk J. (1992): Frequency-domain and multirate adaptive filtering. — IEEE Signal Process. Mag., Vol. 9, No. 1, pp. 14–39.
  • Taveniku M. and Ahlander A. (1997): Instruction statistics in array signal processing. — Res. Rep., Halmstad Univ.
  • Tian Z., Bell K. and van Trees H. (2001): A recursive least squares implementation of the LCMP beamformer under quadratic constraint. — IEEE Trans. Signal Process., Vol. 49, No. 6, pp. 1510–1522.
  • Timmoneri L., Proudler I., Farina A. and McWhirter J. (1994): QRD-based MVDR algorithm for adaptive multipulse array signal processing.—IEE Proc.-Radar, Sonar Navigat., Vol. 141, No. 2, pp. 93–102.
  • van Veen B. and Buckley K. (1988): Beamforming: A versatile approach to spatial filtering. — IEEE ASSP Mag., Vol. 5, No. 4, pp. 4–24.
  • Weiss S., Stewart R., Schaber M., Proudler I. and Hoffman M. (1999): An efficient scheme for broadband adaptive beamforming. — Proc. 33rd Asilomar Conf. Signals, Sysems, Computers, Monterey, CA, USA, Vol. I, pp. 495–500.
  • Wenzler A. and Luder E. (1995): New structures for compex multipliers and their noise analysis. — Proc. IEEE ISCAS, Seattle, USA, pp. 1431–1435.
  • Widrow B. and Stearns S. (1985): Adaptive Signal Processing. — Englewood Cliffs, NJ: Prentice Hall.
  • Winograd S. (1980): Arithmetic Complexity of Computations.— Philadelphia: SIAM.
  • Winters J. (1998): Smart antennas for wireless systems.—IEEE Person. Comm., Vol. 5, No. 1, pp. 23–27.
  • Xu Z. and Tsatsanis M. (1999): Adaptive minimum variance methods for direct blind multichannel equalization. — Signal Process., Vol. 73, pp. 125–138.
  • Ye W., Bar-Nes W. and Haimovich A. (1997): A self-correcting loop for joint estimation-calibration in adaptive radar. — IEEE Nat. Radar Conf., Syracuse, NY, pp. 320–324.
  • Yu J. and Leou M. (2000): Transformation-based adaptive array beamforming. — Sign. Process., Vol. 80, No. 2, pp. 231– 241.
  • Yu S. and Ueng F. (2000): Blind adaptive beamforming based on generalized sidelobe canceller. — Signal Process., Vol. 80, No. 12, pp. 2497–2506.
  • Yuen S. (1991): Exact Least-Squares adaptive beamforming using orthogonalization network.—IEEE Trans. Aerospace Electr. Sys., Vol. 27, No. 2, pp. 311–330.

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