Showing papers on "Beamforming published in 2005"

Robust minimum variance beamforming

Abstract: This paper introduces an extension of minimum variance beamforming that explicitly takes into account variation or uncertainty in the array response. Sources of this uncertainty include imprecise knowledge of the angle of arrival and uncertainty in the array manifold. In our method, uncertainty in the array manifold is explicitly modeled via an ellipsoid that gives the possible values of the array for a particular look direction. We choose weights that minimize the total weighted power output of the array, subject to the constraint that the gain should exceed unity for all array responses in this ellipsoid. The robust weight selection process can be cast as a second-order cone program that can be solved efficiently using Lagrange multiplier techniques. If the ellipsoid reduces to a single point, the method coincides with Capon's method. We describe in detail several methods that can be used to derive an appropriate uncertainty ellipsoid for the array response. We form separate uncertainty ellipsoids for each component in the signal path (e.g., antenna, electronics) and then determine an aggregate uncertainty ellipsoid from these. We give new results for modeling the element-wise products of ellipsoids. We demonstrate the robust beamforming and the ellipsoidal modeling methods with several numerical examples.

On downlink beamforming with greedy user selection: performance analysis and a simple new algorithm

Abstract: This paper considers the problem of simultaneous multiuser downlink beamforming. The idea is to employ a transmit antenna array to create multiple "beams" directed toward the individual users, and the aim is to increase throughput, measured by sum capacity. In particular, we are interested in the practically important case of more users than transmit antennas, which requires user selection. Optimal solutions to this problem can be prohibitively complex for online implementation at the base station and entail so-called Dirty Paper (DP) precoding for known interference. Suboptimal solutions capitalize on multiuser (selection) diversity to achieve a significant fraction of sum capacity at lower complexity cost. We analyze the throughput performance in Rayleigh fading of a suboptimal greedy DP-based scheme proposed by Tu and Blum. We also propose another user-selection method of the same computational complexity based on simple zero-forcing beamforming. Our results indicate that the proposed method attains a significant fraction of sum capacity and throughput of Tu and Blum's scheme and, thus, offers an attractive alternative to DP-based schemes.

Collaborative beamforming for distributed wireless ad hoc sensor networks

Abstract: The performance of collaborative beamforming is analyzed using the theory of random arrays. The statistical average and distribution of the beampattern of randomly generated phased arrays is derived in the framework of wireless ad hoc sensor networks. Each sensor node is assumed to have a single isotropic antenna and nodes in the cluster collaboratively transmit the signal such that the signal in the target direction is coherently added in the far-field region. It is shown that with N sensor nodes uniformly distributed over a disk, the directivity can approach N, provided that the nodes are located sparsely enough. The distribution of the maximum sidelobe peak is also studied. With the application to ad hoc networks in mind, two scenarios (closed-loop and open-loop) are considered. Associated with these scenarios, the effects of phase jitter and location estimation errors on the average beampattern are also analyzed.

Analysis and design of spherical microphone arrays

Abstract: Spherical microphone arrays have been recently studied for sound-field recordings, beamforming, and sound-field analysis which use spherical harmonics in the design. Although the microphone arrays and the associated algorithms were presented, no comprehensive theoretical analysis of performance was provided. This work presents a spherical-harmonics-based design and analysis framework for spherical microphone arrays. In particular, alternative spatial sampling schemes for the positioning of microphones on a sphere are presented, and the errors introduced by finite number of microphones, spatial aliasing, inaccuracies in microphone positioning, and measurement noise are investigated both theoretically and by using simulations. The analysis framework can also provide a useful guide for the design and analysis of more general spherical microphone arrays which do not use spherical harmonics explicitly.

Robust adaptive beamforming

Abstract: Contributors. Preface. 1. Robust Minimum Variance Beamforming (R. Lorenz & S. Boyd). 2. Robust Adaptive beamforming Based on Worst-Case Performance Optimization (A. Gershman, et al.). 3. Robust Capon Beamforming (J. Li, et al.). 4. Diagonal Loading for Finite Sample Size Beamforming: An Asymptotic Approach (X. Mestre & M. Lagunas). 5. Mean-Squared Error Beamforming for Signal Estimation: A Competitive Approach (Y. Eldar & A. Nehorai). 6. Constant Modulus Beamforming (A. van der Veen & A. Leshem). 7. Robust Wideband Beamforming (E. Di Claudio & R. Parisi). Index.

Synthetic aperture beamformer for imaging through a dielectric wall

Abstract: A coarray-based aperture synthesis scheme using subarrays and postdata acquisition beamforming is presented for through-the-wall wideband microwave imaging applications. The wall causes wave refraction and a change in the propagation speed, both effects alter the travel time between the transmitter, the target, and the receiver. Coherent combining of the pulse waveforms emitted by the different transmitters and incident at the receivers through reflections from targets and clutter requires incorporation of wall effects into the beamformer design. Simulation results verifying the proposed synthetic aperture technique for a through-the-wall imaging (TWI) system are presented. The impact of the wall ambiguities or incorrect estimates of the wall parameters, such as thickness and dielectric constant, on performance is considered.

Extensions of DAMAS and Benefits and Limitations of Deconvolution in Beamforming

Abstract: The DAMAS deconvolution algorithm represents a breakthrough in phased array imaging for aeroacoustics, potentially eliminating sidelobles and array resolution effects from beamform maps . DAMAS is an iterative non-negative least squares solver. The original algorithm is too slow and lacks an explicit regularization method to prevent noise amplification. Two extensions are proposed, DAMAS2 and DAMAS3. DAMAS2 provides a dramatic speedup of each iteration and adds regularization by a low pass filter. DAMAS3 also provides fast iterations, and additionally, reduces the required number of iterations. It uses a different regularization technique from DAMAS2, and is partially based on the Wiener filter. Both DAMAS2 and DAMAS3 restrict the point spread function to a translationally-invariant, convolutional, form. This is a common assumption in optics and radio astronomy, but may be a serious limitation in aeroacoustic beamforming. This limitation is addressed with a change of variables from (x,y,z) to a new set, (u,v,w). The concepts taken together, along with appropriate array design, may permit practical 3D beamforming in aeroacoustics.

Beamformer analysis of MEG data.

Abstract: Publisher Summary This chapter discusses a source reconstruction approach, beamforming, which was only recently introduced to electroencephalography (EEG) and magnetoencephalography (MEG). As with any other source reconstruction method, a set of a priori assumptions are made so that a solution to the inverse problemcan be obtained. The main assumption behind the beamformer approach is that no two distant cortical areas generate coherent local field potentials over long time scales; it has been shown empirically that this is a reasonable assumption set. The reason the beamformer assumption set although simplistic, may indeed be quite plausible is argued on the basis of anatomical and electrophysiological data. The time when the assumptions might fail is described and suggestions for improvements in the beamformer implementations are presented. Beamforming is an exciting new approach to MEGsource reconstruction that could provide another stepping stone on the route towards an appropriate assumption set with which to non-invasively image the brain.

Smart Antennas for Wireless Communications: With MATLAB

Abstract: 1. Introduction 1.1. What is a Smart Antenna? 1.2. Why Are Smart Antennas Emerging Now? 1.3. What are the Benefits of Smart Antennas? 1.4. Smart Antennas Involve Many Disciplines 1.5. Overview of the Book References 2. Fundamentals of Electromagnetic Fields 2.1. Maxwell's Equations 2.2. The Helmholtz Wave Equation 2.3. Propagation in Rectangular Coordinates 2.4. Propagation in Spherical Coordinates 2.5. Electric Field Boundary Conditions 2.6. Magnetic Field Boundary Conditions 2.7. Planewave Reflection and Transmission Coefficients 2.7.1. Normal Incidence 2.7.2. Oblique Incidence 2.8. Propagation Over Flat Earth 2.9. Knife-Edge Diffraction References Problems 3. Antenna Fundamentals 3.1. Antenna Field Regions 3.2. Power Density 3.3. Radiation Intensity 3.4. Basic Antenna Nomenclature 3.4.1. Antenna Pattern 3.4.2. Antenna Boresight 3.4.3. Principal Plane Patterns 3.4.4. Beamwidth 3.4.5. Directivity 3.4.6. Beam Solid Angle 3.4.7. Gain 3.4.8. Effective Aperture 3.5. Friis Transmission Formula 3.6. Magnetic Vector Potential and the Far Field 3.7. Linear Antennas 3.7.1. Infinitesimal Dipole 3.7.2. Finite Length Dipole 3.8. Loop Antennas 3.8.1. Loop of Constant Phasor Current References Problems 4. Array Fundamentals 4.1. Linear Arrays 4.1.2. Two Element Array 4.1.3. Uniform N-Element Linear Array 4.1.2.1 Broadside Linear Array 4.1.2.2 End-Fire Linear Array 4.1.2.3 Beamsteered Linear Array 4.1.4. Uniform N-Element Linear Array Directivity 4.1.4.1. Broadside Array Maximum Directivity 4.1.4.2. End-Fire Array Maximum Directivity 4.1.4.3. Beamsteered Array Maximum Directivity 4.2. Array Weighting 4.2.2. Beamsteered and Weighted Arrays 4.3. Circular Arrays 4.3.2. Beamsteered Circular Arrays 4.4. Rectangular Planar Arrays 4.5. Fixed Beam Arrays 4.5.2. Butler Matrices 4.6. Fixed Sidelobe Canceling 4.7. Retrodirective Arrays References Problems 5. Principles of Random Variables and Processes 5.1. Definition of Random variables 5.2. Probability Density Functions 5.3. Expectation and Moments 5.4. Common probability density functions 5.5. Stationarity and ergodicity 5.6. Autocorrelation and power spectral density 5.7. Correlation matrix References Problems 6. Propagation Channel Characteristics 6.1. Flat Earth Model 6.2. Multipath Propagation Mechanisms 6.3. Propagation Channel Basics 6.3.1. Fading 6.3.2. Fast Fading Modeling 6.3.3. Channel Impulse Response 6.3.4. Power Delay Profile 6.3.5. Prediction of Power Delay Profiles 6.3.6. Power Angular Profile 6.3.7. Prediction of Angular Spread 6.3.8. Power Delay-Angular Profile 6.3.9. Channel Dispersion 6.3.10. Slow Fading Modeling 6.4. Improving Signal Quality 6.4.2. Equalization 6.4.3. Diversity 6.4.3.1. RAKE Receiver 6.4.4. Channel Coding 6.4.5. MIMO References Problems 7. Angle-of-Arrival Estimation 7.1. Fundamentals of Matrix Algebra 7.1.2. Vector Basics 7.1.3. Matrix Basics 7.2. Array Correlation Matrix 7.3 AOA Estimation Methods 7.3.1. Bartlett AOA Estimate 7.3.2. Capon AOA Estimate 7.3.3. Linear Prediction AOA Estimate 7.3.4. Maximum Entropy AOA Estimate 7.3.5. Pisarenko Harmonic Decomposition AOA Estimate 7.3.6. Min-Norm AOA Estimate 7.3.7. MUSIC AOA Estimate 7.3.8 Root-MUSIC AOA Estimate 7.3.9 ESPRIT AOA Estimate References Problems 8. Smart Antennas 8.1. Introduction 8.2. The Historical Development of "Smart Antennas" 8.3. Fixed Weight Beamforming Basics 8.3.1. Maximum Signal-to-Interference Ratio 8.3.2. Minimum Mean-Square Error 8.3.3. Maximum Likelihood 8.3.4. Minimum Variance 8.4. Adaptive Beamforming 8.4.1. Least Mean Squares 8.4.2. Sample Matrix Inversion 8.4.3. Recursive Least Squares 8.4.4. Constant Modulus 8.4.5. Least Squares Constant Modulus 8.4.6. Conjugate Gradient Method 8.4.7. Spreading Sequence Array Weights 8.4.7.1. Description of the New SDMA Receiver 8.4.7.2. Example using bi-phase chipping References Problems

Iterative multiuser uplink and downlink beamforming under SINR constraints

Abstract: We study the problem of power efficient multiuser beamforming transmission for both uplink and downlink. The base station is equipped with multiple antennas, whereas the mobile units have single antennas. In the uplink, interference is canceled by successive decoding. In the downlink, ideal "dirty paper" precoding is assumed. The design goal is to minimize the total transmit power while maintaining individual SINR constraints. In the uplink, the optimization problem is solved by a recursive formula with low computational complexity. The downlink problem is solved by exploiting the duality between uplink and downlink; thus, the uplink solution carries over to the downlink. In the second part of the paper, we show how the solution can be applied to the problem of rate balancing in Gaussian multiuser channels. We propose a strategy for throughput-wise optimal transmission for broadcast and multiple access channels under a sum power constraint. Finally, we show that single-user transmission achieves the sum capacity in the low-SNR regime. We completely characterize the SNR-range where single-user transmission is optimal.

Quantifying the power loss when transmit beamforming relies on finite-rate feedback

Abstract: Transmit beamforming achieves optimal performance in systems with multiple transmit antennas and a single receive antenna from both the capacity and the received signal-to-noise ratio (SNR) perspectives but ideally requires perfect channel knowledge at the transmitter. In practical systems where the feedback link can only convey a finite number of bits, transmit beamformer designs have been extensively investigated using either the outage probability or the average SNR as the figure of merit. In this paper, we study the symbol error rate (SER) for transmit beamforming with finite-rate feedback in a multi-input single-output setting. We derive an SER lower bound that is tight for good beamformer designs. Comparing this bound with the SER corresponding to the ideal case, we quantify the power loss due to the finite-rate constraint across the entire SNR range.

Optimality of zero-forcing beamforming with multiuser diversity

Abstract: In MIMO downlink channels, the capacity is achieved by dirty paper coding (DPQ). However, DPC is difficult to implement in practical systems. This work investigates if, for a large number of users, simpler schemes can achieve the same performance. Specifically, we show that a zero-forcing beamforming (ZFBF) strategy, while generally suboptimal, can achieve the same asymptotic sum-rate capacity as that of DPC, as the number of users goes to infinity. In proving this asymptotic result, we propose an algorithm for determining which users should be active in ZFBF transmission. These users are semi-orthogonal to one another, and when fairness among users is required, can be grouped for simultaneous transmissions to enhance the throughput of fair schedulers. We provide numerical results to confirm the optimality of ZFBF and to compare its performance with that of various MIMO downlink strategies.

Interpolation based transmit beamforming for MIMO-OFDM with limited feedback

Abstract: Transmit beamforming and receive combining are simple methods for exploiting spatial diversity in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. Optimal beamforming requires channel state information in the form of the beamforming vectors for each OFDM subcarrier. This paper proposes a limited feedback architecture that combines beamforming vector quantization and smart vector interpolation. In the proposed system, the receiver sends a fraction of information about the optimal beamforming vectors to the transmitter and the transmitter computes the beamforming vectors for all subcarriers through interpolation. A new spherical interpolator is developed that exploits parameters for phase rotation to satisfy the phase invariance and unit norm properties of the transmitted beamforming vectors. The beamforming vectors and phase parameters are quantized at the receiver and the quantized information is provided to the transmitter. The proposed quantization system provides only a moderate increase in complexity versus over comparable approaches. Numerical simulations show that the proposed scheme performs better than existing diversity techniques with the same feedback data rate.

Realizing an electronically tunable reflectarray using varactor diode-tuned elements

Abstract: Electronically tunable reflectarrays hold significant promise as cost effective architectures for RF beamforming applications. The successful operation of these arrays depends on the phase agility of the cells used to realize the array. This letter describes the design of an electronically tunable reflectarray based on a novel cell architecture that provides a large degree of phase agility. Experimental results demonstrating the beamforming capabilities of the array at 5.8 GHz are presented.

A multi user beamforming scheme for downlink MIMO channels based on maximizing signal-to-leakage ratios

Abstract: Multi-user multiple-input multiple-output (MU-MIMO) wireless systems can provide a substantial gain in network downlink throughput by allowing multiple users to communicate in the same frequency and time slots. The challenge is to design transmit beamforming vectors for every user while limiting the co-channel interference (CCI) from other users. One approach is to perfectly cancel the CCI at every user, which requires a relatively large number of transmit antennas. In this paper, we consider an alternative approach based on maximizing the signal-to-leakage ratio (SLR) for designing transmit beamforming vectors in a multi-user system. One advantage of the proposed scheme is that it does not impose a restriction on the number of available transmit antennas; it also outperforms the conventional beamforming scheme.

Multimode precoding for MIMO wireless systems

Abstract: Multiple-input multiple-output (MIMO) wireless systems obtain large diversity and capacity gains by employing multielement antenna arrays at both the transmitter and receiver. The theoretical performance benefits of MIMO systems, however, are irrelevant unless low error rate, spectrally efficient signaling techniques are found. This paper proposes a new method for designing high data-rate spatial signals with low error rates. The basic idea is to use transmitter channel information to adaptively vary the transmission scheme for a fixed data rate. This adaptation is done by varying the number of substreams and the rate of each substream in a precoded spatial multiplexing system. We show that these substreams can be designed to obtain full diversity and full rate gain using feedback from the receiver to transmitter. We model the feedback using a limited feedback scenario where only finite sets, or codebooks, of possible precoding configurations are known to both the transmitter and receiver. Monte Carlo simulations show substantial performance gains over beamforming and spatial multiplexing.

Adaptive Array Systems: Fundamentals and Applications

Abstract: Preface. Acknowledgments. List of Figures. List of Tables. Introduction. I.1 Adaptive Filtering. I.2 Historical Aspects. I.3 Concept of Spatial Signal Processing. 1 Fundamentals of Array Signal Processing. 1.1 Introduction. 1.2 The Key to Transmission. 1.3 Hertzian Dipole. 1.4 Antenna Parameters & Terminology. 1.5 Basic Antenna Elements. 1.6 Antenna Arrays. 1.7 Spatial Filtering. 1.8 Adaptive Antenna Arrays. 1.9 Mutual Coupling & Correlation. 1.10 Chapter Summary. 1.11 Problems. 2 Narrowband Array Systems. 2.1 Introduction. 2.2 Adaptive Antenna Terminology. 2.3 Beam Steering. 2.4 Grating Lobes. 2.5 Amplitude Weights. 2.6 Chapter Summary. 2.7 Problems. 3 Wideband Array Processing. 3.1 Introduction. 3.2 Basic concepts. 3.3 A Simple Delay-line Wideband Array. 3.4 Rectangular Arrays as Wideband Beamformers. 3.5 Wideband Beamforming using FIR Filters. 3.6 Chapter Summary. 3.7 Problems. 4 Adaptive Arrays. 4.1 Introduction. 4.2 Spatial Covariance Matrix. 4.3 Multi-beam Arrays. 4.4 Scanning Arrays. 4.5 Switched Beam Beamformers. 4.6 Fully Adaptive Beamformers. 4.7 Adaptive Algorithms. 4.8 Source Location Techniques. 4.9 Fourier Method. 4.10 Capon's Minimum Variance. 4.11 The MUSIC Algorithm. 4.12 ESPRIT. 4.13 Maximum Likelihood Techniques. 4.14 Spatial Smoothing. 4.15 Determination of Number of Signal Sources. 4.16 Blind Beamforming. 4.17 Chapter Summary. 4.18 Problems. 5 Practical Considerations. 5.1 Introduction. 5.2 Signal Processing Constraints. 5.3 Implementation Issues. 5.4 Radiowave Propagation. 5.5 Transmit Beamforming. 5.6 Chapter Summary. 5.7 Problems. 6 Applications. 6.1 Introduction. 6.2 Antenna Arrays for Radar Applications. 6.3 Antenna Arrays for Sonar Applications. 6.4 Antenna Arrays for Biomedical Applications. 6.5 Antenna Arrays for Wireless Communications. 6.6 Chapter Summary. 6.7 Problems. References. Index.

Ultrasound research scanner for real-time synthetic aperture data acquisition

Abstract: Conventional ultrasound systems acquire ultrasound data sequentially one image line at a time. The architecture of these systems is therefore also sequential in nature and processes most of the data in a sequential pipeline. This often makes it difficult to implement radically different imaging strategies on the platforms and makes the scanners less accessible for research purposes. A system designed for imaging research flexibility is the prime concern. The possibility of sending out arbitrary signals and the storage of data from all transducer elements for 5 to 10 seconds allows clinical evaluation of synthetic aperture and 3D imaging. This paper describes a real-time system specifically designed for research purposes. The system can acquire multichannel data in real-time from multi-element ultrasound transducers, and can perform some real-time processing on the acquired data. The system is capable of performing real-time beamforming for conventional imaging methods using linear, phased, and convex arrays. Image acquisition modes can be intermixed, and this makes it possible to perform initial trials in a clinical environment with new imaging modalities for synthetic aperture imaging, 2D and 3D B-mode, and velocity imaging using advanced coded emissions. The system can be used with 128-element transducers and can excite 128 transducer elements and receive and sample data from 64 channels simultaneously at 40 MHz with 12-bit precision. Two-to-one multiplexing in receive can be used to cover 128 receive channels. Data can be beamformed in real time using the system's 80 signal processing units, or it can be stored directly in RAM. The system has 16 Gbytes RAM and can, thus, store more than 3.4 seconds of multichannel data. It is fully software programmable and its signal processing units can also be reconfigured under software control. The control of the system is done over a 100-Mbits/s Ethernet using C and Matlab. Programs for doing, e.g., B-mode imaging can be written directly in Matlab and executed on the system over the net from any workstation running Matlab. The overall system concept is presented along with its implementation and examples of B-mode and in vivo synthetic aperture flow imaging.

An overview of scheduling algorithms in MIMO-based fourth-generation wireless systems

Abstract: In this article an overview of the scheduling algorithms proposed for fourth-generation multiuser wireless networks based on multiple-input multiple-output technology is presented. In MIMO systems a multi-user diversity gain can be extracted by tracking the channel fluctuations between each user and the base station, and scheduling transmission for the "best" user. Based on this idea, several opportunistic scheduling schemes that attempt to improve global capacity or satisfy users with different QoS requirements have been proposed. Transmit beamforming procedures aimed at increasing the channel fluctuations have been proposed. The simultaneous exploitation of both spatial and multi-user diversity is not straightforward; however, it may be achieved by a refined selection of the "best" user. In addition, a multiple access gain can be obtained from a simple SDMA/TOMA system. Finally, several resource allocation schemes are discussed for this hybrid multiple access system.

Scalable feedback control for distributed beamforming in sensor networks

Abstract: Recent work has shown that large gains in communication capacity are achievable by distributed beamforming in sensor networks. The principal challenge in realizing these gains in practice, is in synchronizing the carrier signal of individual sensors in such a way that they combine coherently at the intended receiver. In this paper, we provide a scalable mechanism for achieving phase synchronization in completely distributed fashion, based only on feedback regarding the power of the net received signal. Insight into the workings of the protocol is obtained from a simple theoretical model that provides accurate performance estimates

A system and method for beamforming using a microphone array

Abstract: The ability to combine multiple audio signals captured from the microphones in a microphone array is frequently used in beamforming systems. Typically, beamforming involves processing the output audio signals of the microphone array in such a way as to make the microphone array act as a highly directional microphone. In other words, beamforming provides a "listening beam" which points to a particular sound source while often filtering out other sounds. A "generic beamformer," as described herein automatically designs a set of beams (i.e., beamforming) that cover a desired angular space range within a prescribed search area. Beam design is a function of microphone geometry and operational characteristics, and also of noise models of the environment around the microphone array. One advantage of the generic beamformer is that it is applicable to any microphone array geometry and microphone type.

Correlated MIMO wireless channels: capacity, optimal signaling, and asymptotics

Abstract: The capacity of the multiple-input multiple-output (MIMO) wireless channel with uniform linear arrays (ULAs) of antennas at the transmitter and receiver is investigated. It is assumed that the receiver knows the channel perfectly but that the transmitter knows only the channel statistics. The analysis is carried out using an equivalent virtual representation of the channel that is obtained via a spatial discrete Fourier transform. A key property of the virtual representation that is exploited is that the components of virtual channel matrix are approximately independent. With this approximation, the virtual representation allows for a general capacity analysis without the common simplifying assumptions of Gaussian statistics and product-form correlation (Kronecker model) for the channel matrix elements. A deterministic line-of-sight (LOS) component in the channel is also easily incorporated in much of the analysis. It is shown that in the virtual domain, the capacity-achieving input vector consists of independent zero-mean proper-complex Gaussian entries, whose variances can be computed numerically using standard convex programming algorithms based on the channel statistics. Furthermore, in the asymptotic regime of low signal-to-noise ratio (SNR), it is shown that beamforming along one virtual transmit angle is asymptotically optimal. Necessary and sufficient conditions for the optimality of beamforming, and the value of the corresponding optimal virtual angle, are also derived based on only the second moments of the virtual channel coefficients. Numerical results indicate that beamforming may be close to optimum even at moderate values of SNR for sparse scattering environments. Finally, the capacity is investigated in the asymptotic regime where the numbers of receive and transmit antennas go to infinity, with their ratio being kept constant. Using a result of Girko, an expression for the asymptotic capacity scaling with the number of antennas is obtained in terms

A novel interference suppression scheme for global navigation satellite systems using antenna array

Abstract: This paper considers interference suppression and multipath mitigation in Global Navigation Satellite Systems (GNSSs). In particular, a self-coherence anti-jamming scheme is introduced which relies on the unique structure of the coarse/acquisition (C/A) code of the satellite signals. Because of the repetition of the C/A-code within each navigation symbol, the satellite signals exhibit strong self-coherence between chip-rate samples separated by integer multiples of the spreading gain. The proposed scheme utilizes this inherent self-coherence property to excise interferers that have different temporal structures from that of the satellite signals. Using a multiantenna navigation receiver, the proposed approach obtains the optimal set of beamforming coefficients by maximizing the cross correlation between the output signal and a reference signal, which is generated from the received data. It is demonstrated that the proposed scheme can provide high gains toward all satellites in the field of view, while suppressing strong interferers. By imposing constraints on the beamformer, the proposed method is also capable of mitigating multipath that enters the receiver from or near the horizon. No knowledge of either the transmitted navigation symbols or the satellite positions is required.

ML estimator and hybrid beamformer for multipath and interference mitigation in GNSS receivers

Abstract: This paper addresses the estimation of the code-phase (pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. The signal is received by an antenna array in a scenario with interference and multipath propagation. These two effects are generally the limiting error sources in most high-precision positioning applications. A new estimator of the code- and carrier-phases is derived by using a simplified signal model and the maximum likelihood (ML) principle. The simplified model consists essentially of gathering all signals, except for the direct one, in a component with unknown spatial correlation. The estimator exploits the knowledge of the direction-of-arrival of the direct signal and is much simpler than other estimators derived under more detailed signal models. Moreover, we present an iterative algorithm, that is adequate for a practical implementation and explores an interesting link between the ML estimator and a hybrid beamformer. The mean squared error and bias of the new estimator are computed for a number of scenarios and compared with those of other methods. The presented estimator and the hybrid beamforming outperform the existing techniques of comparable complexity and attains, in many situations, the Crame/spl acute/r-Rao lower bound of the problem at hand.

Adaptive minimum bit-error rate beamforming

Abstract: An adaptive beamforming technique is proposed based on directly minimizing the bit-error rate (BER). It is demonstrated that this minimum BER (MBER) approach utilizes the antenna array elements more intelligently than the standard minimum mean square error (MMSE) approach. Consequently, MBER beamforming is capable of providing significant performance gains in terms of a reduced BER over MMSE beamforming. A block-data adaptive implementation of the MBER beamforming solution is developed based on the Parzen window estimate of probability density function. Furthermore, a sample-by-sample adaptive implementation is considered, and a stochastic gradient algorithm, referred to as the least bit error rate, is derived. The proposed adaptive MBER beamforming technique provides an extension to the existing work for adaptive MBER equalization and multiuser detection.

Medical ultrasound imaging using the fully adaptive beamformer

Abstract: Medical ultrasound beamforming is conventionally done using a classical delay-and-sum operation. This simplest beamforming suffers from drawbacks. Indeed, in phased array imaging, the beamformed radiofrequency signal is often polluted with off-axis energies. We investigate the use of an adaptive beamforming approach widely used in array processing, the fully adaptive beamformer, to reduce the bright off-axis energies contribution. We show that the fully adaptive beamformer cannot be applied to medical ultrasound as it was initially derived since the medical ultrasonic medium produces coherent or highly correlated signals and the algorithm fails to work within this context. Spatial smoothing preprocessing is introduced which allows the fully adaptive beamformer to operate. A complementary preprocessing that uses the received data obtained using consecutive transmission lines further improve the performances. Very promising results for the application of adaptive array processing techniques in medical ultrasound are obtained.

A study of opportunism for multiple-antenna systems

Abstract: Recently proposed opportunistic beamforming exploits the multiuser diversity to reduce the feedback by not requiring the precoding information used for closed-loop schemes to be known at the transmitter. Opportunism could also be beneficially employed for other multiple-antenna transmission techniques like cophasing and antenna selection. For opportunistic beamforming and antenna selection, we give closed-form expressions for throughput that closely approximate the performance of these schemes with a Proportionally Fair scheduler (PFS) at low signal-to-noise ratios (SNRs). For large number of transmit antennas, opportunistic cophasing has similar performance as opportunistic beamforming. Asymptotic dependence of the required number of users to achieve the gains of opportunism on the number of transmit antennas is exponential for opportunistic beamforming (and cophasing for large numbers of transmit antennas), and at best linear for opportunistic antenna selection. For multiple-antenna receivers, we additionally examine an opportunistic multiple-input multiple-output (MIMO) scheme that transmits multiple data streams simultaneously to the same user.

System and method for interpolation based transmit beamforming for MIMO-OFDM with partial feedback

Abstract: Transmit beamforming with receive combining uses the significant diversity provided by multiple-input multiple-output (MIMO) systems, and the use of orthogonal frequency division multiplexing (OFDM) enables low complexity implementation of this scheme over frequency selective MIMO channels. Optimal beamforming uses channel state information in the form of the beamforming vectors corresponding to all the OFDM subcarriers. In non-reciprocal channels, this information should be conveyed back to the transmitter. To reduce the amount of feedback information, transmit beamforming combines limited feedback and beamformer interpolation. In this architecture, the receiver sends back a fraction of information about the beamforming vectors to the transmitter, and the transmitter computes the beamforming vectors for all subcarriers through interpolation of the conveyed beamforming vectors. Since a beamforming vector is phase invariant and has unit norm, a linear spherical interpolator uses additional parameters for phase rotation. These parameters are determined at the receiver in the sense of maximizing the minimum channel gain or capacity. The interpolator maybe combined with beamformer quantization.

Satellite communications systems and methods using radiotelephone location-based beamforming

Abstract: A processor for use in a satellite communications system includes a selector that is configured to select a subset of a plurality of spatially diverse satellite signals based upon a location of a radioterminal. The processor further includes a signal processor that is configured to detect a return-link transmission from the radioterminal responsive to the selected subset of the spatially diverse satellite signals. The respective spatially diverse satellite signals may include respective signals corresponding to respective antenna elements of a satellite. The selector and the signal processor may be ground based.

A four-antenna receiver in 90-nm CMOS for beamforming and spatial diversity

Abstract: A fully integrated four-channel multi-antenna receiver intended for beamforming and spatial diversity applications is presented. It can also be used as a low-power area-efficient range extender for spatially multiplexed multi-antenna systems that are poised to become mainstream in the near future. Implemented in a 90-nm CMOS technology, each channel weights its input signal by a complex weight with full 360/spl deg/ phase shift programmability using vector combinations of variable-gain amplifiers, thus obviating the need for expensive phase shifters. The chip consumes 140 mW from a single 1.4-V supply and achieves 12 dB of array gain with all four channels activated and >20 dB direction-of-arrival-dependent interference rejection.