A new subspace identification algorithm for high-resolution DOA estimation

In this paper, we propose a new direction of arrival (DOA) estimator for sensor-array processing. The estimator is based on a linear algebraic connection between the standard subspace model of the array correlation matrix and a special signal-plus-interference model, which we develop in this paper. The estimator we propose is a signal subspace scaled MUSIC algorithm, which we call SSMUSIC. It is not a subspace weighted MUSIC, because the scaling depends on the eigenstructure of the estimated signal subspace. SSMUSIC has the advantage of simultaneously estimating the DOA and the power of each source. We employ a second-order perturbation analysis of the estimator and derive stochastic representations for its bias and squared-error. We compare the new DOA estimator with the MUSIC estimator, based on these representations. Numerical results demonstrate the superior performance of SSMUSIC relative to MUSIC and the validity of the perturbation results.     

Interference estimation with applications to blind multiple-accesscommunication over fading channels

We consider the detection of nonorthogonal multipulse signals on multiple-access fading channels. The generalized maximum-likelihood rule is employed to decode users whose complex fading gains are unknown. We develop geometrical interpretations for the resulting detectors and their corresponding asymptotic efficiencies. The generalized maximum-likelihood detection rule is then applied to find a matched subspace detector for the frequency-selective fading channel, under the assumption of a short coherence time (or long coherence time without the computational power to track the fading parameters). We propose blind implementations of these detectors for nonorthogonal multipulse signaling on both frequency-nonselective and frequency-selective multiple-access fading channels. These blind detectors extend the results of Wang and Poor (see ibid., vol.44, p.677-89, 1998) to multipulse modulation and fast frequency selective fading. For comparison, the minimum mean-squared error decision rules for these channels are derived and blind implementations of their corresponding detectors are developed     

Beamforming, diversity, and interference rejection for multiuser communication over fading channels with a receive antenna array

We consider M-ary communication with K users over a space diversity channel, consisting of a single transmit antenna for each user and multiple receive antennas. We examine two different flat fading models, namely, phase coherent wavefront fading and noncoherent element-to-element fading. In the case of wavefront fading, the fade is constant across the face of the receive antenna and we can associate an angle of arrival to the signal. We present a variation of the MUSIC algorithm for estimating this parameter and use it to form a spatial beam. In the case of noncoherent element-to-element fading, the fading path to each sensor is different (although possibly correlated) and no angle of arrival can be exploited for conventional beamforming. For each channel model, we develop several detection strategies which assume various amounts of prior information about the fading. We then consider blind extensions of these detectors based on subspace tracking, which do not require a prior model for the interfering users' signals.     

Goniothalenol: a novel,bioactive, tetrahydrofurano-2-pyrone from goniothalamus giganteus (annonaceae)

Fractionation of the stem bark of the title plant, monitoring for bioactivity with brine lethality, led to the isolation of goniothalenol (I). Mass, ¹HNMR, and ¹³CNMR spectral data helped to characterized I as a phenyltetrahydrofurano-2-pyrone, as a novel heterocyclic ring system for natural compounds. X-Ray crystallographic analysis confirmed the structure and established the configuration for I.     

Modulation and Coding for Noncoherent Communications

Until recently, the theory of noncoherent communications was premised on the use of orthogonal multi-pulse modulation such as frequency shift keying. The main drawback of this modulation scheme has been its poor spectral efficiency (rate/bandwidth). This paper considers instead the more general non-orthogonal multi-pulse modulation (NMM) technique. Optimal and suboptimal noncoherent detection strategies for NMM are reviewed and their asymptotic (high SNR) performances are characterized for the additive Gaussian as well as the Rayleigh fading channels. The resulting non-Euclidean distance measures are then used to design NMM signal sets that yield significantly higher bandwidth efficiencies than their orthogonal counterparts. NMM in conjunction with convolutional coding is also studied as a way to improve energy efficiency. Several optimal convolutional codes are examined together with our signal designs. An introduction to equalization on the noncoherent channel is also presented and illustrated by example. This paper thus contains several new results and attempts at the same time to give a tutorial exposition of the subject of noncoherent communications.     

Analysis and design of short block OFDM spreading matrices for use on multipath fading channels

We consider the use of block spreading in a multicarrier system to gain diversity advantage when employed over multipath fading channels. The main idea is to split the full set of subcarriers into smaller blocks and spread the data symbols across these blocks via unitary spreading matrices in order to gain multipath diversity across each block at the receiver. We pose the problem of designing the spreading matrix as a finite dimensional optimization problem in which the asymptotic error is minimized. This formulation allows us to find explicit solutions for the optimal spreading matrices. The performance is validated for the uncoded channel as well as for the coded channel employing turbo-iterative decoding. We further demonstrate that suboptimal linear complexity equalization strategies for spread orthogonal frequency division multiplexing (OFDM) do not gain any diversity advantage over traditional diagonal OFDM.     

Lag-windowing and multiple-data-windowing are roughly equivalent for smooth spectrum estimation

There is no fundamental difference between lag-windowing a correlation sequence and multiple-windowing a data sequence when the objective is to reduce the mean-squared error of a spectrum estimator. By analyzing the approximate low-rank factorization of a bandlimiting Toeplitz operator, we find that lag-windowed (or spectrally smoothed) spectrum estimators have multiple-data-windowed implementations. This makes the Blackman-Tukey-Grenander-Rosenblatt spectrogram equivalent to the Thomson spectrum estimator (and vice-versa), meaning BTGR spectrograms may be implemented in a multichannel filterbank version of the Thomson estimator.     

Signal design and convolutional coding for noncoherent space-timecommunication on the block-Rayleigh-fading channel

We consider the problem of designing signal constellations for the multiple transmit-multiple receive antenna Rayleigh-fading communication channel, when neither the transmitter nor the receiver know the fading. In particular, by employing the asymptotic union bound (AUB) on the probability of error, we give a new formulation of the problem of signal design for the noncoherent fading channel. Since unitary signals are optimal for this channel (in the limit of large signal-to-noise ratios SNRs), the problem can be posed in terms of packings on the Grassmanian manifold. A key difference in our approach from that of other authors is that we use a notion of distance on this manifold that is suggested by the union bound. As a consequence of our use of this distance measure, we obtain signal designs that are guaranteed to achieve the full diversity order of the channel, a result that does not hold when the chordal distance is used. We introduce a new method of recursively designing signals, termed successive updates, to approximately optimize this performance measure. We then examine the use of our signals with several convolutional codes over the fading channel. An upper bound on the bit error probability of the maximum-likelihood decoder is presented together with an asymptotic analysis of that bound     

Blind adaptation of zero forcing projections and oblique pseudo-inverses for subspace detection and estimation when interference dominates noise

In much of modern radar, sonar, and wireless communication, it seems more reasonable to model "measurement noise" as subspace interference-plus-broadband noise than as colored noise. This observation leads naturally to a variety of detection and estimation problems in the linear statistical model. To solve these problems, one requires oblique pseudo-inverses, oblique projections, and zero-forcing orthogonal projections. The problem is that these operators depend on knowledge of signal and interference subspaces, and this information is often not at hand. More typically, the signal subspace is known, but the interference subspace is unknown. We prove a theorem that allows these operators to be estimated directly from experimental data, without knowledge of the interference subspace. As a byproduct, the theorem shows how signal subspace covariance may be estimated. When the strict identities of the theorem are approximated, then the detectors, estimators, and beamformers of this paper take on the form of adaptive subspace estimators, detectors, and Capon beamformers, all of which are reduced in rank. The fundamental operator turns out to be a certain reduced-rank Wiener filter, which we clarify in the course of our derivations. The results of this paper form a foundation for the rapid adaptation of receivers that are then used for detection and estimation. They may be applied to detection and estimation in radar, sonar, and hyperspectral imaging and to data decoding in multiuser communication receivers.