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ADAPTIVE ANTENNAS FOR WIRELESS NETWORKS
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Here Q(X) is the standard Q-function de ned in 1, x, G is the processing gain of the CDMA system, b 0:05513, and D is the directivity of the beam of the multibeam antenna system. A comparison of the BER performance of the systems using other than LMS algorithms [149,190,192] has shown that the maximum entropy method [190] and the spatial discrete Fourier transform method [192] provide better BER performance than the LMS algorithm. Finally, we note that there are some other performance improvements that can be obtained by using an antenna array, such as an increase in transmission ef ciency, reduction in handoff rate and in cross talks, improvement of dynamic channel assignment, cost-effective implementation, complexity reduction, and network implication. All these are aspects beyond the subject of this book and are well described in existing literature [161 163,178,180,193 196].
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SUMMARY Smart antenna systems are usually categorized as either switched beam or adaptive array systems. Although both systems attempt to increase gain in the direction of the user, only the adaptive array system offers optimal gain while simultaneously identifying, tracking, and minimizing interfering signals. The traditional switched beam method is considered as an extension of the current cellular sectorization scheme in which a typical sectorized cell site is composed of three 120 macrosectors. The switched beam approach further subdivides the macrosectors into several microsectors. The adaptive antennas take a very different approach. By adjusting to an RF environment as it changes, adaptive antenna technology can dynamically alter the signal patterns to optimize the performance of the wireless system. Usually, in the transmit mode, the adaptive array focuses energy in the required direction, which helps to reduce multipath re ections and the delay spread. In the receive mode, however, the array provides compensation in multipath fading by adding the signals emanating from other clusters after compensating for delays, as well as by canceling delayed signals emanating from directions other than that of the desired signal.
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[1] Glaser, E. M., Signal detection by adaptive lters, IEEE Trans. Inform. Theory, vol. IT-7, no. 1, 1961, pp. 87 98. [2] Davisson, L. D., A theory of adaptive lters, IEEE Trans. Inform. Theory, vol. IT-12, no. 1, 1966, pp. 97 102. [3] Grif ts, L. J., A comparison of multidimensional Weiner and maximum-likelihood lters for antenna arrays , Proc. IEEE, vol. 55, 1967, pp. 2045 2057. [4] Goode, B. B., Synthesis of a nonlinear Bayer detector for Gaussian signal and noise elds using Wiener lters, IEEE Trans. Information Theory, vol. IT-13, 1967, pp. 116 118.
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[5] Burg, J. P., Three-dimensional ltering with an array of sesmometers, Geophysics, vol. 29, 1964, pp. 693 713. [6] Haykin, S., ed., Array Signal Processing, Prentice-Hall, Englewood Cliffs, New Jersey, 1985. [7] Stuber, G. L., Principles of Mobile Communication, Kluwer Academic Publishers, 1996. [8] Proakis, J. G., Digital Communication, McGraw Hill, New York, NY, 2001. [9] Steele, R., Mobile Radio Communications, IEEE Press, New York, 1992. [10] Rappaport, T, S., Wireless Communications Principles and Practice, Prentice Hall, New York, NY, 1996. [11] Farina, A., Antenna-Based Signal Processing Techniques for Radar Systems, Artech House, Norwood, Massachusetts, 1992. [12] Krim, H., and M. Viberg, Two decades of array signal processing research, IEEE Signal Processing Magazine, no. 1, 1996, pp. 67 94. [13] Paulraj, A. J., and C. B. Papadias, Space-time processing for wireless communications, IEEE Personal Communications, vol. 14, no. 5, 1997, pp. 49 83. [14] Widrow, B., P. E. Mantey, L. J. Grif ts, et al., Adaptive antenna systems, Proc. IEEE, vol. 55, no. 12, 1967, pp. 2143 2159. [15] Special Issue on Active and Adaptive Antennas, IEEE Trans. Antennas Propagat., March 1964; vol. AP-24, no. 3, September 1976. [16] Gabriel, W. F., Adaptive arrays-an introduction, Proc. IEEE, vol. 64, no. 2, 1976, pp. 239 272. [17] Gabriel, W. F., Spectral analysis and adaptive array super resolution techniques, Proc. IEEE, vol. 68, no. 6, 1980, pp. 654 666. [18] Monzingo, R. A., and T. W. Miller, Introduction to Adaptive Arrays, Wiley and Sons, New York, 1980. [19] Hudson, J. E., Adaptive Array Principles, Peter Peregrinus, New York, 1981. [20] Special Issue on Adaptive Processing Antenna Systems, IEEE Trans. Antennas Propagat., vol. AP-34, March 1986. [21] Compton, R. T., Jr., Adaptive Antennas: Concepts and Performance, Prentice-Hall, Englewood Cliffs, New Jersey, 1988. [22] Gabriel, W. F., Adaptive processing array systems, Proc. IEEE, vol. 80, no. 1, 1992, pp. 152 162. [23] Barret, M., and R. Arnott, Adaptive antennas for mobile communications, Electron. Communic. Eng. J., vol. 6, no. 2, 1994, pp. 203 214. [24] Litva, J., and T. Lo, Digital Beamforming in Wireless Communications, Artech House, 1996. [25] Pridham, R. G., and R. A. Mucci, A novel approach to digital beamforming, J. Acoust. Soc. Amer., vol. 63, 1978, pp. 425 434. [26] Pridham, R. G., and R. A. Mucci, Digital interpolation beamforming for low-pass and bandpass signals, Proc. IEEE, vol. 67, no. 5, 1979, pp. 904 919. [27] Curtis, T. E., Digital beamforming for sonar system, IEE Proc. Pt. F, vol. 127, no. 2, 1980, pp. 257 265. [28] Mucci, R. A., A comparison of ef cient beamforming algorithms, IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-32, no. 3, 1984, pp. 548 558.
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