Array processing involves manipulation of signals induced on various antenna elements. Its capabilities of steering nulls to reduce cochannel interferences and pointing independent beams toward various mobiles, as well as its ability to provide estimates of directions of radiating sources, make it attractive to a mobile communications system designer. Array processing is expected to play an important role in fulfilling the increased demands of various mobile communications services. Part I of this paper showed how an array could be utilized in different configurations to improve the performance of mobile communications systems, with references to various studies where feasibility of apt array system for mobile communications is considered. This paper provides a comprehensive and detailed treatment of different beam-forming schemes, adaptive algorithms to adjust the required weighting on antennas, direction-of-arrival estimation methods-including their performance comparison-and effects of errors on the performance of an array system, as well as schemes to alleviate them. This paper brings together almost all aspects of array signal processing.

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Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations

A technique is proposed for the extraction of spectral signals for which the components within a signal set are characterized by complex envelopes which exhibit correlation The technique is based on an orthogonal decomposition of the cross (discrete) frequency correlation matrix describing the set in the presence of additive uncorrelated noise Certain advantages of the technique relative to those based on Fourier analysis with either estimated power spectrum or minimum variance processing are presented Specifically, it is illustrated how the detection performance of the technique is established by the total energy in the spectral set rather than by the levels of individual spectral elements in the set Furthermore, it is shown how minimum variance spectrum analysis actually can suppress components in such a set

Spectral Signal Set Extraction

The status of optimum-adaptive space-time processing development is assessed. Reasons are considered as to why these techniques have encountered only moderate acceptance in sonar applications. The issues of applicability, complexity and cost are examined. New research topics in high resolution processing and joint source-sensor position estimation are outlined.

Overview of Adaptive Array Processing

Relaxed zero-forcing beamformer under temporally-correlated interference

The relaxed zero-forcing (RZF) beamformer is a quadratically-and-linearly constrained minimum variance beamformer. The central question addressed in this paper is whether RZF performs better than the widely-used minimum variance distortionless response and zero-forcing beamformers under temporally-correlated interference. First, RZF is rederived by imposing an ellipsoidal constraint that bounds the amount of interference leakage for mitigating the intrinsic gap between the output variance and the mean squared error (MSE) which stems from the temporal correlations. Second, an analysis of RZF is presented for the single-interference case, showing how the MSE is affected by the spatio-temporal correlations between the desired and interfering sources as well as by the signal and noise powers. Third, numerical studies are presented for the multiple-interference case, showing the remarkable advantages of RZF in its basic performance as well as in its application to brain activity reconstruction from EEG data. The analytical and experimental results clarify that the RZF beamformer gives near-optimal performance in some situations.

Relaxed Zero-Forcing Beamformer under Temporally-Correlated Interference

: A model for a multichannel array signal processor that performs a noise-cancellation function is specified. The performance of the processor is examined in terms of the output signal-to-total-background-noise ratio. The parameters of interest are the correlation between signal and noise, the number of noise sampling channels, the relative gain of the noise in the signal-plus- noise versus the noise-only channels, and the array input signal-to-noise and interference-to-noise ratios. An important practical implication of the results presented is that, in systems such as adaptive beamformers for arrays, system performance can be seriously degraded if the signal and noise waveforms are correlated over finite time intervals.

Norman L Owsley

Papers

Noise Cancellation in the Presence of Correlated Signal and Noise