The performance of the MUSIC and ML methods is studied, and their statistical efficiency is analyzed. The Cramer-Rao bound (CRB) for the estimation problems is derived, and some useful properties of the CRB covariance matrix are established. The relationship between the MUSIC and ML estimators is investigated as well. A numerical study is reported of the statistical efficiency of the MUSIC estimator for the problem of finding the directions of two plane waves using a uniform linear array. An exact description of the results is included. >

MUSIC, maximum likelihood, and Cramer-Rao bound

A study of a matrix pencil method for estimating frequencies and damping factors of exponentially damped and/or undamped sinusoids in noise is presented. Comparison of this method to a polynomial method (SVD-Prony method) shows that the matrix pencil method and the polynomial method are two special cases of a matrix prediction approach and that the pencil method is more efficient in computation and less restrictive about signal probes. It is found through perturbation analysis and simulation that, for signals with unknown damping factors, the pencil method is less sensitive to noise than the polynomial method. An expression of the Cramer-Rao bound for the exponential signals is presented. >

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Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise

A numerical and analytical study of conditional and unconditional direction-of-arrival (DOA) estimation is presented. Explicit expressions for the unconditional Cramer-Rao bounds on the DOA estimation accuracy and the covariance matrix of the conditional maximum likelihood method are given. It is shown that many DOA estimation methods have the same asymptotic statistical properties under conditional and unconditional models. The situation of two narrowband plane signals impinging on a uniformly spaced linear array is discussed. >

Performance study of conditional and unconditional direction-of-arrival estimation

Cognitive radio (CR) is the enabling technology for supporting dynamic spectrum access: the policy that addresses the spectrum scarcity problem that is encountered in many countries. Thus, CR is widely regarded as one of the most promising technologies for future wireless communications. To make radios and wireless networks truly cognitive, however, is by no means a simple task, and it requires collaborative effort from various research communities, including communications theory, networking engineering, signal processing, game theory, software-hardware joint design, and reconfigurable antenna and radio-frequency design. In this paper, we provide a systematic overview on CR networking and communications by looking at the key functions of the physical (PHY), medium access control (MAC), and network layers involved in a CR design and how these layers are crossly related. In particular, for the PHY layer, we will address signal processing techniques for spectrum sensing, cooperative spectrum sensing, and transceiver design for cognitive spectrum access. For the MAC layer, we review sensing scheduling schemes, sensing-access tradeoff design, spectrum-aware access MAC, and CR MAC protocols. In the network layer, cognitive radio network (CRN) tomography, spectrum-aware routing, and quality-of-service (QoS) control will be addressed. Emerging CRNs that are actively developed by various standardization committees and spectrum-sharing economics will also be reviewed. Finally, we point out several open questions and challenges that are related to the CRN design.

Cognitive radio networking and communications: an overview

Orthogonal frequency-division multiplexing (OFDM) effectively mitigates intersymbol interference (ISI) caused by the delay spread of wireless channels. Therefore, it has been used in many wireless systems and adopted by various standards. In this paper, we present a comprehensive survey on OFDM for wireless communications. We address basic OFDM and related modulations, as well as techniques to improve the performance of OFDM for wireless communications, including channel estimation and signal detection, time- and frequency-offset estimation and correction, peak-to-average power ratio reduction, and multiple-input-multiple-output (MIMO) techniques. We also describe the applications of OFDM in current systems and standards.

OFDM and Its Wireless Applications: A Survey

An explicit connection between fitting exponential models and pole-zero models to observed data is made. The fitting problem is formulated as a constrained nonlinear minimization problem. This problem is then solved using a simplified iterative algorithm. The algorithm is applied to simulated data, and the performance of the algorithm is compared to previous results.

An algorithm for pole-zero modeling and spectral analysis

This article gives a brief tutorial on transform-domain communication system (TDCS), OFDM, and MC-CDMA. The primary goal of this article is to give a detailed description of the TDCS transmitter and receiver systems and to highlight the fundamental differences relative to OFDM and MC-CDMA. The fundamental idea in TDCS is to synthesize a smart adaptive waveform to avoid interference at the transmitter instead of the more traditional mitigating of interference at the receiver. Unlike OFDM and MC-CDMA, TDCS has very little exposure in the current literature.

TDCS, OFDM, and MC-CDMA: a brief tutorial

The growth of wireless applications and spectral limitations are serious concerns for both the military and civilian communities. Cognitive radio (CR) technologies expand spectrum efficiency using elements of space, time and frequency diversity that up to now have not been exploited. An adaptive waveform (AW) generation technique is presented which adapts to the changing electromagnetic environment and synthesizes waveform features in the frequency domain. Spectral coexistence with other applications is also addressed and can be accomplished in both static and dynamic environments. Bit error rate (BER) serves as the primary performance metric for evaluating and comparing AW processing with other waveforms and systems.

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Cognitive radio - an adaptive waveform with spectral sharing capability

Several studies have revealed that spectrum congestion is primarily due to the inefficient use of spectrum versus unavailability. Cognitive radio (CR) and ultra wide band (UWB) technologies have been proposed as candidates to address this problem. Currently, a CR determines unused frequency bands and transmits overlay waveforms in these bands, while UWB transmits underlay waveforms that span the entire frequency band while coexisting with primary users. This suggests that most of the spectrum occupied by primary users is underused. This work proposes a general soft decision cognitive radio (SDCR) framework, based on a previous developed spectrally modulated, spectrally modulated (SMSE) framework, to combine benefits of overlay/underlay techniques while maximizing channel capacity. We also show that current CR and UWB implementations represent two extreme SDCR cases and that current overlay/underlay waveforms are two special cases of the general waveform platform.

A general overlay/underlay analytic expression representing cognitive radio waveform

The bearing estimation problem is formulated as a matrix-approximation problem. The columns of a matrix X are formed by the snapshot vectors from an N-element array. The matrix X is then approximated by a matrix in the least-square sense. The rank as well as the partial structure of the space spanned by the columns of the approximated X matrix are prespecified. After the approximated X matrix is computed, the bearings of the sources and, consequently, the spatial correlation of the source signals are estimated. The performance of the proposed technique is compared with two existing methods using simulation. The comparison is made in terms of bias, mean-squared error, failure rates, and confidence intervals for the mean and the variance estimates for all three methods at different signal-to-noise ratios. When the sources are moving slowly and the number of snapshot vectors available for processing is large, a simple online adaptive algorithm is suggested. >

Arnab K. Shaw

Papers

An algorithm for pole-zero modeling and spectral analysis

TDCS, OFDM, and MC-CDMA: a brief tutorial

Cognitive radio - an adaptive waveform with spectral sharing capability

A general overlay/underlay analytic expression representing cognitive radio waveform

Superresolution by structured matrix approximation