121 research outputs found
Asymptotic optimal SINR performance bound for space-time beamforming
International audienceIn many detection applications, the main performance criterion is the signal to interference plus noise ratio (SINR). After linear filtering, the optimal SINR corresponds to the maximum value of a Rayleigh quotient, which can be interpreted as the largest generalized eigenvalue of two covariance matrices. Using an extension of Szegö's theorem for the generalized eigenvalues of Hermitian block Toeplitz matrices, an expression of the theoretical asymptotic optimal SINR w.r.t. the number of taps is derived for arbitrary arrays with a limited but arbitrary number of sensors and arbitrary spectra. This bound is interpreted as an optimal zero-bandwidth spatial SINR in some sense. Finally, the speed of convergence of the optimal wideband SINR for a limited number of taps is analyzed for several interference scenario
Unit Circle Roots Based Sensor Array Signal Processing
As technology continues to rapidly evolve, the presence of sensor arrays and the algorithms processing the data they generate take an ever-increasing role in modern human life. From remote sensing to wireless communications, the importance of sensor signal processing cannot be understated. Capon\u27s pioneering work on minimum variance distortionless response (MVDR) beamforming forms the basis of many modern sensor array signal processing (SASP) algorithms. In 2004, Steinhardt and Guerci proved that the roots of the polynomial corresponding to the optimal MVDR beamformer must lie on the unit circle, but this result was limited to only the MVDR. This dissertation contains a new proof of the unit circle roots property which generalizes to other SASP algorithms. Motivated by this result, a unit circle roots constrained (UCRC) framework for SASP is established and includes MVDR as well as single-input single-output (SISO) and distributed multiple-input multiple-output (MIMO) radar moving target detection. Through extensive simulation examples, it will be shown that the UCRC-based SASP algorithms achieve higher output gains and detection probabilities than their non-UCRC counterparts. Additional robustness to signal contamination and limited secondary data will be shown for the UCRC-based beamforming and target detection applications, respectively
Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach
This paper proposes a spatial filtering technique for
the reception of pilot-aided multirate multicode direct-sequence
code division multiple access (DS/CDMA) systems such as wideband
CDMA (WCDMA). These systems introduce a code-multiplexed
pilot sequence that can be used for the estimation of the
filter weights, but the presence of the traffic signal (transmitted
at the same time as the pilot sequence) corrupts that estimation
and degrades the performance of the filter significantly. This is
caused by the fact that although the traffic and pilot signals are
usually designed to be orthogonal, the frequency selectivity of the
channel degrades this orthogonality at hte receiving end. Here,
we propose a semi-blind technique that eliminates the self-noise
caused by the code-multiplexing of the pilot. We derive analytically
the asymptotic performance of both the training-only and
the semi-blind techniques and compare them with the actual simulated
performance. It is shown, both analytically and via simulation,
that high gains can be achieved with respect to training-onlybased
techniques.Peer Reviewe
3-D Beamspace ML Based Bearing Estimator Incorporating Frequency Diversity and Interference Cancellation
The problem of low-angle radar tracking utilizing an array of antennas is considered. In the low-angle environment, echoes return from a low flying target via a specular path as well as a direct path. The problem is compounded by the fact that the two signals arrive within a beamwidth of each other and are usually fully correlated, or coherent. In addition, the SNR at each antenna element is typically low and only a small number of data samples, or snapshots, is available for processing due to the rapid movement of the target. Theoretical studies indicates that the Maximum Likelihood (ML) method is the only reliable estimation procedure in this type of scenario. However, the classical ML estimator involves a multi-dimensional search over a multi-modal surface and is consequently computationally burdensome. In order to facilitate real time processing, we here propose the idea of beamspace domain processing in which the element space snapshot vectors are first operated on by a reduced Butler matrix composed of three orthogonal beamforming weight vectors facilitating a simple, closed-form Beamspace Domain ML (BDML) estimator for the direct and specular path angles. The computational simplicity of the method arises from the fact that the respective beams associated with the three columns of the reduced Butler matrix have all but three nulls in common. The performance of the BDML estimator is enhanced by incorporating the estimation of the complex reflection coefficient and the bisector angle, respectively, for the symmetric and nonsymmetric multipath cases. To minimize the probability of track breaking, the use of frequency diversity is incorporated. The concept of coherent signal subspace processing is invoked as a means for retaining the computational simplicity of single frequency operation. With proper selection of the auxiliary frequencies, it is shown that perfect focusing may be achieved without iterating. In order to combat the effects of strong interfering sources, a novel scheme is presented for adaptively forming the three beams which retains the feature of common nulls
Signal Processing in Large Systems: a New Paradigm
For a long time, detection and parameter estimation methods for signal
processing have relied on asymptotic statistics as the number of
observations of a population grows large comparatively to the population size
, i.e. . Modern technological and societal advances now
demand the study of sometimes extremely large populations and simultaneously
require fast signal processing due to accelerated system dynamics. This results
in not-so-large practical ratios , sometimes even smaller than one. A
disruptive change in classical signal processing methods has therefore been
initiated in the past ten years, mostly spurred by the field of large
dimensional random matrix theory. The early works in random matrix theory for
signal processing applications are however scarce and highly technical. This
tutorial provides an accessible methodological introduction to the modern tools
of random matrix theory and to the signal processing methods derived from them,
with an emphasis on simple illustrative examples
Minimum redundancy array structure for interference cancellation
Adaptive antenna arrays are widely used in many advanced radar, sonar, and communication systems because of their effectiveness in cancelling intentional or unintentional interferers. A uniformly spaced linear array, referred to as a Uniform Regular Array (URA), is the usual structure used for interference cancellation. The Minimum Redundancy Array (MRA) structure proposed in this work is a special kind of thinned array whose application was limited in the past to direction finding. MRAs with the same number of array elements can resolve directions of much more closely spaced signals than URAs.
The URA structure is customarily utilized for interference cancellation, and the Minimum Noise Variance (MNV) criterion is a common performance measure for deriving optimum weights, provided that the desired signal is absent during adaptation. The MNV criterion is to minimize the combined sum of the interference and background noise power.
Another approach to interference cancellation using the URA structure is the eigencanceling method. This method, which is based on the eigenstructure of the spatial autocorrelation matrix, when compared to the conventional beamforming method, has the following advantages: 1) deeper interference cancellation 2) independence of the interfers\u27 power, and 3) faster optimum weight convergence. In this work, both the conventional beamforming and eigencanceling methods were applied to the MRA structure and investigated analytically. Performance of the MRAs were studied and compared to that of the URAs.
For uncorrelated interferers, the cancellation depth of the MRA in the main beam region was almost the same as that of the URA with the same aperture and many more elements. When the eigencanceling technique was applied, it was found that the convergence rate of the MRA was about four times faster than that of the URA.
This work also contains other topics, such as the relation between the eigenspaces of the MRA structure and its corresponding URA. Preliminary results on planar MRA structures are also included. For an array application with a large aperture requirement in terms of the number of array elements, the MRA proved to be a much better choice than the URA in achieving interference cancellation
Joint transceiver design for MIMO channel shortening.
Channel shortening equalizers can be employed
to shorten the effective impulse response of a long intersymbol
interference (ISI) channel in order, for example, to decrease the
computational complexity of a maximum-likelihood sequence
estimator (MLSE) or to increase the throughput efficiency of an
orthogonal frequency-division multiplexing (OFDM) transmission
scheme. In this paper, the issue of joint transmitterâreceiver filter
design is addressed for shortening multiple-input multiple-output
(MIMO) ISI channels. A frequency-domain approach is adopted
for the transceiver design which is effectively equivalent to an
infinite-length time-domain design. A practical spaceâfrequency
waterfilling algorithm is also provided. It is demonstrated that the
channel shortening equalizer designed according to the time-domain
approach suffers from an error-floor effect. However, the
proposed techniques are shown to overcome this problem and
outperform the time-domain channel shortening filter design. We
also demonstrate that the proposed transceiver design can be considered
as a MIMO broadband beamformer with constraints on
the time-domain multipath length. Hence, a significant diversity
gain could also be achieved by choosing strong eigenmodes of the
MIMO channel. It is also found that the proposed frequency-domain
methods have considerably low computational complexity as
compared with their time-domain counterparts
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