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The spectral efficiency of a representative uplink of a given length, in interference-limited, spatially-distributed wireless networks with hexagonal cells, simple power control, and multiantenna linear Minimum-Mean-Square-Error receivers is found to approach an asymptote as the numbers of base-station antennas N and wireless nodes go to infinity. An approximation for the area-averaged spectral efficiency of a representative link (averaged over the spatial base-station and mobile distributions), for Poisson distributed base stations, is also provided. For large N, in the interference-limited regime, the area-averaged spectral efficiency is primarily a function of the ratio of the product of N and the ratio of base-station to wireless-node densities, indicating that it is possible to scale such networks by linearly increasing the product of the number of base-station antennas and the relative density of base stations to wireless nodes, with wireless-node density. The results are useful for designers of wireless systems with high inter-cell interference because it provides simple expressions for spectral efficiency as a function of tangible system parameters like base-station and wireless-node densities, and number of antennas. These results were derived combining infinite random matrix theory and stochastic geometry., Accepted to IEEE Transactions on Communications

In this paper, the optimal spectral efficiency (data rate divided by the message bandwidth) that minimizes the probability of causing disruptive interference for ad hoc wireless networks or cognitive radios is investigated. Two basic problem constraints are considered: a given message size, or fixed data rate. Implicitly, the trade being optimized is between longer transmit duration and wider bandwidth versus higher transmit power. Both single-input single-output (SISO) and multiple-input multiple-output (MIMO) links are considered. Here, a link optimizes its spectral efficiency to be a "good neighbor." The probability of interference is characterized by the probability that the signal power received by a hidden node in a wireless network exceeds some threshold. The optimized spectral efficiency is a function of the transmitter-to-hidden-node channel exponent, exclusively. It is shown that for typical channel exponents a spectral efficiency of slightly greater than 1~b/s/Hz per antenna is optimal. It is also shown that the optimal spectral efficiency is valid in the environment with multiple hidden nodes. Also explicit evaluations of the probability of collisions is presented as a function of spectral efficiency., 12 pages, 6 figures, contributed to the 2010 IEEE Asilomar Conference on Signals, Systems and Computers

For the Superconducting Super Collider (SSC) to meet its physics requirements, the magnetic center of each collider dipole magnet (CDM) must be accurately aligned. A technique has been developed to determine the magnetic center of the SSC dipole magnet under ambient test conditions. This technique involves flowing current in the upper half of the coils in the direction opposite to the current in the lower half. This is done using a temporary lead connected to the splice joining the two coil halves and two matched power supplies. The resulting field is primarily skew quadrupole and has high field gradients which allow the center to be accurately located. The viability of this method has been verified by analysis using a Taylor series expansion of the resulting magnetic field. The analysis has also verified that off-the-shelf power supplies have low enough mismatch to be used in this technique. The analytical results have been verified through the test of a short dipole magnet at the Brookhaven National Laboratory. >

The authors report on the status of the magnetic design of the Superconducting Super Collider (SSC) dipole magnets. A two- and three-dimensional design optimization was performed that included the effects of permeable collar, yoke, cryostat, beam tube, crescent yoke end pieces, cool-down, and Lorentz loads. A field quality plan was developed that represents the approach to tuning the design for satisfying the systematic and RMS multipole specifications. The VSA tool is being used to simulate the effects of random parts, tool and process variations on the expected multipole distributions, both between many magnets, and within a single magnet. >

The end regions of the Superconducting Super Collider (SSC) collider dipole magnets. (CDMs) were designed to meet both magnetic and mechanical requirements. The authors present an optimized end design for CDM magnets that is mechanically producible and possesses desirable magnetic field quality, peak field, and magnetic length properties. A three-dimensional magnetic field distribution was calculated for this end-turn design using the finite element program TOSCA. The effective magnetic length, integrated multipole content, and peak fields are extracted from the results of the finite element model. These results compare favorably with those from a second analysis program, ENDTURN, that is based on an analytic solution to the defining field equations. >

We examine the clutter covariance matrices for ground moving-target indicator (GMTI) multiple-input, multiple-output (MIMO) radar systems, and, in particular, discuss a potential suboptimal increase in their rank. This increase in rank will generically degrade the ability of a MIMO GMTI system to detect slowly moving targets. We first give a general theoretical analysis and then focus on simulated and experimental data for MIMO systems employing fast-time random, time-division multiple-access (TDMA), and Doppler-division multiple-access (DDMA) waveforms. We will show that for the TDMA/DDMA waveforms the clutter covariance matrix in a given Doppler bin is effectively rank 1 for both the simulated and experimental data.

Multiple-input multiple-output (MIMO) extensions to radar systems enable a number of advantages compared to traditional approaches. These advantages include improved angle estimation and target detection. In this tutorial, an overview of MIMO radar is provided, and the concept of coherent MIMO radar is defined. In addition, two topics are addressed more thoroughly: MIMO waveform/array geometry optimization for target tracking, and MIMO ground moving target indication (GMTI).

Multiple-input multiple-output (MIMO) extensions to radar systems enable a number of advantages compared to traditional approaches. These advantages include improved angle estimation and target detection. In this paper, MIMO ground moving target indication (GMTI) radar is addressed. The concept of coherent MIMO radar is introduced. Comparisons are presented comparing MIMO GMTI and traditional radar performance. Simulations and theoretical bounds for MIMO GMTI angle estimation and minimum detectable velocity are presented. The simulations are evaluated in the time domain, enabling waveform design studies. For some applications, these results indicate significant potential improvements in clutter-mitigation SINR loss and reduction in angle-estimation error for slow-moving targets.

The combined use of orthogonal frequency-division multiplexing (OFDM) and wireless multiple-input multiple-output (MIMO) links is becoming common. For many applications, such as ad hoc wireless networks, interference is a significant issue. MIMO links allow for the spatial mitigation of interference; however, spatial interference mitigation when using OFDM modulation performs somewhat poorly because of the relatively limited interference spectral confinement of the Discrete Fourier Transform. Traditional windowing approaches that minimize leakage of the interference into neighboring carriers induce intercarrier interference. In this paper, a technique is developed for determining optimal windows that trade off interference suppression with intercarrier and interframe interference. This technique assumes channel statistics are known. Optimized windows for various levels of interference, delay spreads, frame length, and cyclic prefix lengths can be produced.

An asymptotic expression is derived for the mean spectral efficiency of multi-antenna links randomly distributed on a plane in a uniform manner where transmitters (Tx) have Channel-State-Information (CSI) of the channels between themselves and their target receivers while receivers (Rx) have CSI between themselves and all transmitters. The mean per-link spectral efficiency in the network is found to increase if nodes transmit using a subset of their strongest channel modes instead of the link-optimal strategy of water-filling on all channel modes (Farrokhi et al.). For reasonable parameters, this system which requires limited Tx CSI, has approximately double the mean spectral efficiency of systems without Tx CSI.

This chapter contains sections titled: Introduction Notation MIMO Radar Virtual Aperture MIMO Radar in Clutter-Free Environments Optimality of MIMO Radar for Detection MIMO Radar with Moving Targets in Clutter: GMTI Radars Summary Appendix 2A A Localization Principle Appendix 2B Bounds on R(N) Appendix 2C An Operator Norm Inequality Appendix 2D Negligible Terms Appendix 2E Bound on Eigenvalues Appendix 2F Some Inner Products Appendix 2G An Invariant Inner Product Appendix 2H Kr��necker and Tensor Products Acknowledgments References

We derive several new outer bounds on the capacity of the MIMO Gaussian interference channel. Many of the bounds presented herein are extensions of the work by Etkin et al. (2007) on the single antenna interference channel. These bounds are compared with a Han and Kobayashi achievable rate region and we show the conditions when the achievable rate approaches the outer bound. We also describe the conditions when the outer bounds are concave, thus guaranteeing a computable outer bound.

We analyze networks with wireless nodes distributed randomly in space, transmitting simultaneously in the same channel to their nearest base-stations using a simple power control algorithm. Base-stations are on a hexagonal grid and have N optimally-phased antennas. We derive the asymptotic mean upstream spectral efficiency (validated by simulation) as a function of N, wireless-node density, base-station separation, and path-loss-exponent which controls signal attenuation with distance. These results indicate that mean per-link spectral efficiency is constant if the number of receive antennas or density of base-stations is increased linearly with wireless node density. They also improve our understanding of systems like city-wide wireless Internet deployments and mobile telephony with small cells for which the spatial distribution of nodes causing out-of-cell interference is important. The results are also readily extendable to random code-division-multiple-access systems with spreading factor N.

The high signal-to-noise ratio capacity of the symmetric MIMO interference channel is characterized as a function of the interference-to-noise ratio. This work is a multiple antenna extension of the degrees of freedom expressions derived by Etkin et al. for the single antenna case. This characterization considers the case where the number of receive antennas is greater than or equal to the number of transmit antennas and shows the number of degrees of freedom available for communication as a function of log(INR)/log(SNR).

We consider a collaborative communication system consisting of several nodes jointly communicating to a common destination node. Once each node determines the message to send, a space-time code across the sources is used to transmit the signal to the destination. As there may be frequency offsets and unknown frequency selective channels, we assume a training sequence is sent in the preamble to estimate these parameters. In this paper, we derive an algorithm that designs training sequences that minimize the Cramer-Rao Bound for frequency estimation in a frequency-selective environment for a multiple node collaborative communication system.

In this paper, techniques for the optimization of multiple-input multiple-output (MIMO) radar waveform correlations and array geometries are investigated. The primary focus of this study is improved angle-estimation performance. This performance can be characterized by the Cramer-Rao angle- estimation bound and by the threshold point. The threshold point indicates the signal-to-noise ratio (SNR) at which the angle- estimation performance of an estimation statistic deviates from the Cramer-Rao bound performance. Approximation techniques for estimating the threshold are introduced. Examples of joint waveform and array geometry optimization are presented.

One of the limiting factors in ad hoc wireless mesh networks using traditional physical layer techniques is the inability to transmit and receive at the same frequency simultaneously. As a consequence, careful time-slot or frequency-reuse planning is required. This has adverse network data-rate and latency implications. The focus of this paper is a demonstration of signal processing techniques that enable simultaneous transmission and reception. These techniques employ informed-transmittermultiple-input multiple-output (MIMO) links. A combination of adaptive transmit and receive antenna array approaches is exploited. A number of important types of networking limitations can be resolved given simultaneous transmit and receive technology. The first example is the simultaneous link problem. By employing transmit and receive spatial adaptivity, two links can operate in close proximity using the same frequency at the same time. Another example is the full duplex relay node. Using the same frequency for both links, a given node can simultaneously receive packets from one node while forwarding them to another. For practical systems, two issues dominate performance: channel estimation error, often caused by stale estimates of the channel at the transmitter, and dynamic range limitations of the transmitter and receiver. These issues are investigated. Theoretical, simulated, and experimental results are presented.

Cooperative diversity systems are wireless communication systems designed to exploit cooperation among users to mitigate the effects of multipath fading. In fairly general conditions, it has been shown that these systems can achieve the diversity order of an equivalent MISO channel and, if the node geometry permits, virtually the same outage probability can be achieved as that of the equivalent MISO channel for a wide range of applicable SNR. However, much of the prior analysis has been performed under the assumption of perfect timing and frequency offset synchronization. In this paper, we derive the estimation bounds and associated maximum likelihood estimators for frequency offset estimation in a cooperative communication system. We show the benefit of adaptively tuning the frequency of the relay node in order to reduce estimation error at the destination. We also derive an efficient estimation algorithm, based on the correlation sequence of the data, which has mean squared error close to the Cramer-Rao Bound., Submitted to IEEE Transaction on Signal Processing

A MIMO (multi-input multi-output) radar system, unlike standard phased-array radar, can transmit via its antennas multiple probing signals. This waveform diversity offered by MIMO radar enables superior capabilities compared with a standard phased-array radar. We consider MIMO radar waveform optimization for parameter estimation for the general case of multiple targets in the presence of spatially colored interference and noise. Numerical examples are provided to demonstrate the effectiveness of the approaches we consider herein.

Cooperative diversity systems are wireless communication systems designed to exploit cooperation among users to mitigate the effects of multipath fading. In fairly general conditions, it has been shown that these systems can achieve the diversity order of an equivalent MISO channel and, if the node geometry permits, virtually the same outage probability is achieved as that of the equivalent MISO channel for a wide range of applicable SNR. However, much of the prior analysis has been performed under the assumption of perfect timing and frequency offset synchronization. In this paper, we derive the estimation bounds and associated maximum likelihood estimators for frequency offset estimation in a cooperative communication system. The cooperative nature of the system is utilized to reduce the estimation error with respect to standard (non-cooperative) frequency estimation algorithms. For a worst case frequency offset distribution among the nodes, we show that this estimator is optimal in the sense of estimation error variance.

In this paper, waveform optimization for multiple- input multiple-output (MIMO) radar systems is considered. Two types of waveform optimization are studied for static radar envi- ronments. Firstly, image-energy optimization using environmen- tally adaptive waveform design is considered. Secondly, waveform optimization for angle estimation in clutter-free environments is treated using Cramer-Rao bounds.

In this paper, an application of multiple-input multiple-output (MIMO) radar techniques to medical imaging is investigated. MIMO radar, which can be viewed as a form of microwave tomography for medical imaging geometries, offers an alternative to current X-ray technology. Of particular interest is the detection of cancerous tumors in breast tissue. Previously, ultrawideband radar techniques have been considered. Here, an intermediate bandwidth is assumed, which enables the digitization of the entire baseband signal. However, this comes with the cost of self-interference because of transmitting and receiving simultaneously. Because the scattering response of tumors is weak compared to self-interference, mitigation of the direct transmitter-to-receiver signal is important to detection. In this application, three interference suppression techniques are considered: temporal mitigation, receive-array mitigation, and transmit-waveform optimization. Mitigation residuals, caused by calibration errors and signal nonlinearities, are included in the analysis. A system concept is introduced, and results from simulations using a simplified physical model are presented.

Wireless communication using multiple-input multiple-output (MIMO) systems improves throughput and enhances reliability for a given total transmit power. In this paper, potential performance gains are investigated via a direct Galois field [GF(q)] low-density parity-check (LDPC) space-time coding and modulation scheme. The field order q is chosen such that the number of bits per GF(q) LDPC symbol matches the number of bits per space-time symbol. The result is an elegant coding and decoding scheme that leverages the powerful LDPC iterative decoding technique. Results for 2, 3, and 4 transmitter systems with relatively short block lengths of around 2000 bits are provided, demonstrating frame-error- rate performances as close as 0.5 dB to the probability of outage upper bound.

We find an asymptotic expression for the average signal to interference ratio (SIR) between a transmitter with a single isotropic antenna and a multi-antenna linear receiver in the presence of interferers with single isotropic transmit antennas distributed uniformly on an infinite plane. The channels are modeled as complex Gaussian random variables with average received power dependent on the distance separating nodes. We find that in large networks, the average SIR for a representative link depends primarily on the ratio of the number of receive antenna elements to the area density of interferers. Furthermore for our network model, the SIR grows super-linearly with the number of antenna elements. We also derive an approximate expression for the average capacity of the link when residual interference is treated as noise under certain conditions. We show via Monte-Carlo simulations that the asymptotic results are useful approximations to systems with finite parameters.

Multiple-input multiple-output (MIMO) wireless communication provides a number of potential advantages over traditional single-input single-output (SISO) approaches, including increased data rates for a given total transmit power and improved robustness to interference. In this paper, the details of a variety of receivers are incorporated into the effects of the channel so that information-theoretic performance bounds can be exploited to evaluate receiver approaches. Two classes of environments are considered: first, channel complexity, characterized by the distribution of the narrowband channel-matrix singular values and second, external interference. Receiver approaches discussed in this paper include minimum-mean-squared error, minimum-interference, as well as an iterative receiver that incorporates estimation subtraction, denoted here as multichannel multiuser detection (MCMUD). Various assumptions are made about the limitations on channel and interference estimation. Receiver performance implications are also demonstrated using experimental data.

The application of multiple-input multiple-output (MIMO) techniques to multistage radar offers a number of advantages, including improved resolution and sensitivity. Depending upon the radar's mode of operation, the array design and the environment, these advantages may or may not be significant. In this paper, a simple analytic model for ground moving target indicator (GMTI) radar detection is presented and its predictions are compared with simulation. Conventional single-input multiple output (SIMO) and MIMO GMTI radars are compared in terms of minimum detectable velocity, area-search rates and array sidelobes. Optimal waveform cross-correlation matrices are identified for MIMO radars, given different performance criteria. Finally, bounds are developed for MIMO arrays with uniformly sampled virtual apertures.

Wireless communication using multiple-input multiple-output (MIMO) systems enables increased data rates and link reliability for a given total transmit power and system bandwidth. Increased capacity is achieved by introducing additional spatial channels which are exploited using space-time coding. The spatial diversity improves the link reliability by reducing the adverse effects of link fading and shadowing. Because antenna arrays are used at both the transmitter and receiver, interference can be mitigated naturally. In this paper, MIMO communication is investigated using outdoor experimental data collected near the PCS frequency allocation (1790 MHz) in the presence of multiple jammers. Coherence issues associated with implementing antenna arrays using ad hoc groups of users are addressed. Presented here is an experimental example of demodulation of a space-time turbo code using a multichannel multiuser detector (MCMUD) that compensates for delay and Doppler spread, as well as local oscillator mismatch. In the experimental data the MIMO signal is transmitted from a moving vehicle.

Ultra-wideband (UWB) signals lend themselves to localization measurements using time difference of arrival (TDOA), or time delay estimation (TDE), techniques. However, TDOA estimation is complicated by pulse distortion due to the antenna elements, other system components, and the multipath propagation environment. This paper explores the use of cross correlation based TDOA methods in conjunction with a novel technique for combining the TDOA estimates from multiple antenna pairs to build an estimate of the transmitter position. Experiments that simulate foliage and industrial environments were performed in an anechoic chamber. Results from these measurements are presented.

In this paper, radar is discussed in the context of a multiple-input multiple-output (MIMO) system model. A comparison is made between MIMO wireless communication and MIMO radar. Examples are given showing that many traditional radar approaches can be interpreted within a MIMO context. Furthermore, exploiting this MIMO perspective, useful extensions to traditional radar can be constructed. Performance advantages in terms of degrees of freedom and resolution are discussed. Finally, a MlMO extension to space-time adaptive processing (STAP) is introduced as applied to ground moving-target indication (GMTI).

In this paper, experimental investigation of multiple-input multiple-output (MIMO) channel-probing estimation are reported for outdoor environments near the PCS frequency allocation (1.79 GHz). A simple channel parameterization and channel distance metrics are introduced. Channel complexity and channel stationarity are also investigated. Complexity is associated with channel-matrix singular value distributions. Stationarity is associated with the stability of channel singular value and singular vector structure over time.

Wireless communication using multiple-input multiple-output (MIMO) systems enables increased spectral efficiency and improved reliability for a given total transmit power. We discuss channel phenomenology and space-time turbo coding. Space-time turbo codes combine the advantages of turbo codes with MIMO systems. The performance of receiver options is investigated, including multichannel multiuser detectors (MCMUD) that iteratively employ space-time-frequency adaptive processing, multiuser detection, and joint channel-data estimation. MIMO capacity is a strong function of channel phenomenology, motivating experimental performance evaluation. Results from outdoor experimental data using a 2 bits/s/Hz, 4/spl times/4 space-time turbo code are presented.

In CDMA systems, multiple users produce cochannel interference that is only partially mitigated by user-dependent spreading codes. Limitations in any closed-loop transmitter power control can create received power variations at the base station that are potentially large. Multichannel multiuser detectors are data-adaptive receivers that provide interference mitigation as well as spatial and temporal diversity. These receivers are discussed in the context of CDMA applications. A maximum likelihood formulation of multiuser detection with antenna arrays is introduced to provide motivation and intuition. The proposed multiuser receiver incorporates space-time beamforming and time-domain interference cancellation. Performance examples using simulated and experimental data are given along with comparisons with a variety of receiver types.

Wireless communications using multiple input multiple output (MIMO) systems enable increased spectral efficiency for a given total transmit power. The increased capacity is achieved through the introduction of additional spatial channels (space-time coding). In this paper, MIMO capacity is calculated as a function of environmental factors, including channel complexity, external interference and channel estimation error. The capacity of MIMO systems, where both the transmitter and receiver know the channel (channel estimate feedback), is compared with single input multiple output (SIMO) and MIMO systems, where only the receiver knows the channel. The channel complexity is studied using a simple statistical physical scattering model. Finally, an expression for capacity loss particular to channel estimation error at the transmitter is introduced.

Multipath propagation has a significant impact on the performance of cellular and personal communication services (PCS) systems in urban environments. This paper contains analyses to better understand urban multipath and examines the use of base-station antenna arrays to obtain spatial diversity. The results are based on data collected on large sparse aperture arrays and finely sampled arrays at a location below surrounding roof top heights for both PCS and cellular frequencies. A statistical model is formulated to explain the relationship between multipath scatterers and signal cross-correlations as a function of antenna spacing.

Wireless communication using multiple-input multiple-output (MIMO) systems enables increased spectral efficiency for a given total transmit power. MIMO capacity is a strong function of the singular value distribution of the channel matrix, the receive antenna to transmit antenna transfer matrix. In this paper the capacity is calculated using an asymptotic large random matrix approach. Bounds on the maximum spectral efficiency of MIMO systems in which both transmitter and receiver know the channel (channel estimate feedback), are compared with MIMO systems in which only the receiver knows the channel. In addition, MIMO performance in the presence of cooperative and uncooperative interfering MIMO systems is presented.

The branching fractions for τ→eνντ, μνντ, and hντ are measured using data collected with the CLEO detector at the CESR e+e- collider: Be=0.1776±0.0006±0.0017, Bμ=0.1737±0.0008±0.0018, and Bh=0.1152±0.0005±0.0012, where the first error is statistical, the second systematic, and h refers to either a charged π or K. Also measured is the τ mass, mτ=(1778.2±1.4) MeV. Lepton universality is affirmed by the relative branching fractions (Bμ/Be=0.9777±0.0063±0.0087, Bh/Be=0.6484±0.0041±0.0060) and the charged-current gauge coupling-constant ratios (gμ/ge=1.0026±0.0055, gτ/gμ=0.9990±0.0098). The τ mass result may be recast as a τ neutrino mass limit, mντ

The measurement of magnetic field harmonics for the Super Collider magnets is currently performed using a rotating one meter long coil referred to as the “mole”. The fact that the mole is 1 meter long hides the fine structure of the harmonics as a function of axial position. Along the length of the magnet, particularly in the ends, there are axial variations in harmonics that are much shorter in wavelength than the mole search coil. This is not important to accelerator operation since only the integrated harmonics have a significant effect on the beam physics. However, in trying to understand manufacturing effects and end design, the fine axial harmonic structure is important. In addition, the mole length places significant limitations on the usefulness of discrete Fourier transforms in studying production effects on magnetic field harmonics. This paper details a method of determining the fine axial harmonic structure using the present mole design.

In this paper, we consider the problem of full-duplex bidirectional communication between a pair of modems, each with multiple transmit and receive antennas. The principal difficulty in implementing such a system is that, due to the close proximity of each modem's transmit antennas to its receive antennas, each modem's outgoing signal can exceed the dynamic range of its input circuitry, making it difficult-if not impossible-to recover the desired incoming signal. To address these challenges, we consider systems that use pilot-aided channel estimates to perform transmit beamforming, receive beamforming, and interference cancellation. Modeling transmitter/receiver dynamic-range limitations explicitly, we derive tight upper and lower bounds on the achievable sum-rate, and propose a transmission scheme based on maximization of the lower bound, which requires us to (numerically) solve a nonconvex optimization problem. In addition, we derive an analytic approximation to the achievable sum-rate, and show, numerically, that it is quite accurate. We then study the behavior of the sum-rate as a function of signal-to-noise ratio, interference-to-noise ratio, transmitter/receiver dynamic range, number of antennas, and training length, using optimized half-duplex signaling as a baseline.