Wideband beamforming with heavily imbalanced channels

This paper studies fixed wideband beamforming with consideration of realistic channels. There has been a perception that nice beam patterns can always be formed with advanced optimization techniques. This is mostly true if the channels are ideal. But in reality it is not always true. Indeed, achieving a desirable beam pattern with an actual beamforming system can be very difficult, and this might be responsible by the fact that the channel transfer functions are neither spectrally flat nor identical across channels. Therefore, unique issues and countermeasures have to be considered in design phase. In this paper we identify the problems and find solutions via comparison study. Performance and computational load are two major issues. New architectures with parallel processing and off-board computing engines are proposed to reduce the computational pressure as well as run time and improve the performance. Both least-square minimization and convex optimization are used to synthesize the beamformer coefficients. Performance requirements like side-lobe suppression, notch/nulling and frequency invariance have to be jointly considered. Different optimization formulations are proposed to achieve a balance among these requirements. It is found that, with the measured channel data (500-MHz bandwidth, centered at 5.25 GHz), the convex-optimization beamformer can achieve 19 dB side-lobe suppression and a 59-dB notch, but this beamformer does not always turn out a feasible and/or acceptable solution. In contrast, the least-square beamformer is more robust to different parameters. It also observed that frequency invariance beamforming is not a feasible requirement for a realistic wideband beamformer. Overall speaking, the convex-optimization beamformer combined with frequency-interleave (parallel processing) offers the best beamforming performance at a reduced computational cost.

[1]  P.G. Vouras,et al.  Wideband Adaptive Beamforming Using Linear Phase Filterbanks , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[2]  O. L. Frost,et al.  An algorithm for linearly constrained adaptive array processing , 1972 .

[3]  R. Langley,et al.  Application of the least squares approach to fixed beamformer design with frequency-invariant constraints , 2011 .

[4]  Sergio L. Netto,et al.  Numerically efficient optimal design of cosine-modulated filter banks with peak-constrained least-squares behavior , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.

[5]  Truong Q. Nguyen,et al.  The theory and design of arbitrary-length cosine-modulated filter banks and wavelets, satisfying perfect reconstruction , 1996, IEEE Trans. Signal Process..

[6]  F. Hlawatsch,et al.  Oversampled cosine modulated filter banks with perfect reconstruction , 1998 .

[7]  Stephan Weiss,et al.  Design of near perfect reconstruction oversampled filter banks for subband adaptive filters , 1999 .

[8]  Tapio Saramäki,et al.  Design of practically perfect-reconstruction cosine-modulated filter banks: a second-order cone programming approach , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[9]  Harry L. Van Trees,et al.  Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory , 2002 .

[10]  P. P. Vaidyanathan,et al.  Cosine-modulated FIR filter banks satisfying perfect reconstruction , 1992, IEEE Trans. Signal Process..

[11]  Jörg Kliewer,et al.  Oversampled cosine-modulated filter banks with arbitrary system delay , 1998, IEEE Trans. Signal Process..

[12]  Wei Liu,et al.  Subband design of fixed wideband beamformers based on the least squares approach , 2011, Signal Process..

[13]  Wei Liu,et al.  Design and Analysis of Broadband Beamspace Adaptive Arrays , 2007, IEEE Transactions on Antennas and Propagation.

[14]  Wei Liu,et al.  Wideband Beamforming: Concepts and Techniques , 2010 .

[15]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[16]  Martin Vetterli,et al.  Oversampled filter banks , 1998, IEEE Trans. Signal Process..

[17]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[18]  Wei Liu,et al.  A least squares approach to the design of frequency invariant beamformers , 2009, 2009 17th European Signal Processing Conference.

[19]  J. Capon High-resolution frequency-wavenumber spectrum analysis , 1969 .

[20]  Truong Q. Nguyen,et al.  Efficient Design of Cosine-Modulated Filter Banks via Convex Optimization , 2009, IEEE Transactions on Signal Processing.

[21]  Helmut Bölcskei,et al.  Frame-theoretic analysis of oversampled filter banks , 1998, IEEE Trans. Signal Process..

[22]  Wei Liu,et al.  An Adaptive Wideband Beamforming Structure With Combined Subband Decomposition , 2009, IEEE Transactions on Antennas and Propagation.