IEEE Military Communications Conference, 2003. MILCOM 2003.
DATA VERSUS DECISlON FUSION FOR DISTRIBUTED CLASSIFICATION IN SENSOR NETWORKS Ashwin D'Costa... more DATA VERSUS DECISlON FUSION FOR DISTRIBUTED CLASSIFICATION IN SENSOR NETWORKS Ashwin D'Costa Akbar M. Sayeed ... These statistical properties of the SCRs can be made pre-cise via the sampling theorem for the spatially bandlimited signal field. I c DX Fig. ...
Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)
Joint signal representations of arbitrary variables extend the scope of joint time-frequency repr... more Joint signal representations of arbitrary variables extend the scope of joint time-frequency representations, and provide a useful description for a wide variety of nonstationary signal characteristics. Cohen's (see Prentice Hall, 1995) marginal-based theory for bilinear representations is canonical from a distributional viewpoint, whereas, from other perspectives, such as characterization of the effect of unitary signal transformations of interest, a covariance-based formulation is needed and more attractive. We present a simple covariance-based characterization of bilinear joint signal representations of arbitrary variables. The formulation is highlighted by its simple structure and interpretation, and naturally extends the concept of the corresponding linear representations.
Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)
Even though broadband signaling and reception is often employed in practice for communication ove... more Even though broadband signaling and reception is often employed in practice for communication over time- and frequency-dispersive channels, existing receiver designs do not fully exploit the advantage of broadband signaling. We introduce a framework for time-frequency processing that is dictated by a canonical characterization of linear dispersive channels and fully utilizes the advantage of broadband signaling. The framework is based on processing in a natural time-frequency subspace defined by orthogonal time-frequency shifted copies of the transmitted broadband waveform. It generalizes existing receivers and suggests new designs that promise substantially improved performance compared to existing systems.
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).
Sensor networks provide virtual snapshots of the physical world via distributed wireless nodes th... more Sensor networks provide virtual snapshots of the physical world via distributed wireless nodes that can sense in different modalities, such as acoustic and seismic. Classification of objects moving through the sensor field is an important application that requires collaborative signal processing (CSP) between nodes. Given the limited resources of nodes, a key constraint is to exchange the least amount of information between them to achieve the desired performance. Two main forms of CSP are possible. Data fusion - exchange of low dimensional feature vectors - is needed between correlated nodes, in general, for optimal performance. Decision fusion $exchange of likelihood values - is sufficient between independent nodes. Decision fusion is generally preferable due to its lower communication burden. We study the CSP of multiple node measurements, each modeled as a Gaussian signal vector (corresponding to the target class) corrupted by additive white Gaussian noise. The measurements are partitioned into groups. The signal components within each group are perfectly correlated whereas they vary independently between groups. Three classifiers are compared: the optimal maximum likelihood classifier; a data averaging classifier that treats all measurements as correlated; a decision fusion classifier that treats them all as independent. The performances of the three CSP classifiers are compared using analytical and numerical results based on real data. These indicate that the sub-optimal decision fusion classifier, that is most attractive in the context of sensor networks, is also a robust choice from a decision theoretic viewpoint.
1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999
... Eko N. Onggosanusi, Akbar M. Sayeed, and Barry D. Van Veen ... p=l,***,P<M; l=O,***,L. (11... more ... Eko N. Onggosanusi, Akbar M. Sayeed, and Barry D. Van Veen ... p=l,***,P<M; l=O,***,L. (11) The angles {e,} corresponding to the canonical spatial sam-pling in (4) and (5) are chosen so that {a(ep)} form a com-plete basis for M-dimensional space spanned by the array ...
Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)
Optimal multi-antenna wideband signaling schemes are derived for multipath channels assuming perf... more Optimal multi-antenna wideband signaling schemes are derived for multipath channels assuming perfect channel state information at the transmitter. The scheme that minimizes the bit-error-probability in the single-user case is a rank-one space-time beamformer which focuses the signal transmission in the direction of the most dominant channel mode. Several sub-optimal variations are discussed for multiuser applications. Simulation results are given to
Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002, 2002
ABSTRACT A low-complexity decoupled detection MIMO receiver structure is proposed for wireless sy... more ABSTRACT A low-complexity decoupled detection MIMO receiver structure is proposed for wireless systems with frequency-selective channels. This receiver structure is termed the decoupled Viterbi algorithm (DVA). In this structure, all the transmitted data streams are completely decoupled at the receiver and are detected independently. This structure can also be viewed as a variation of a MIMO minimum mean square error decision feedback sequence estimator (MMSE-DFSE) structure. Moreover, a certain MMSE optimization constraint, namely L-tap forward interference control (L-tap FIC), is needed to achieve complete decoupling of the transmitted data streams at the receiver. It is shown that the complexity of the DVA is &quot;linear&quot;, meaning it increases only linearly with the number of transmitted data streams. Compared with other receivers that have &quot;linear&quot; complexity, such as partitioned Viterbi algorithm (PVA) (Miller, C. et al., IEEE Trans. on Commun., vol.49, no.11, 2001), DVA provides an attractive alternative since it does not require interchange of tentative decisions between different detection branches.
Time-frequency representations (TFRs) provide a powerful and exible structure for designing optim... more Time-frequency representations (TFRs) provide a powerful and exible structure for designing optimal detectors in a variety of nonstationary scenarios. In this paper, we describe a TFR-based framework for optimal detection of arbitrary second-order stochastic signals, with certain unknown or random nuisance parameters, in the presence of Gaussian noise. The framework provides a useful model for many important applications including machine fault diag-nostics and radar/sonar. We emphasize a subspace-based formulation of such TFR detectors which can be exploited in a variety of ways to design new techniques. In particular , we explore an extension based on multi-channel/sensor measurements that are often available in practice to facilitate improved signal processing. In addition to potentially improved performance, the subspace-based interpretation of such multi-channel detectors provides useful information about the physical mechanisms underlying the signals of interest.
Code division multiple access (CDMA) has emerged as a dominant technology for meeting the physica... more Code division multiple access (CDMA) has emerged as a dominant technology for meeting the physical layer challenges of future wireless communication systems. Signal processing requirements in the physical layer are dictated by three major factors: multiaccess interference, multipath dispersion and fading, and transceiver complexity. Existing CDMA system designs reeect a piecemeal approach due to the lack of an eeective framework for jointly addressing these issues. We propose signal processing in canonical multipath-Doppler coordinates for attacking physical layer impairments in an integrated fashion. The canonical coordinates are derived from a fundamental characterization of channel propagation dynamics in terms of discrete multipath-delayed and Doppler-shifted copies of the spread-spectrum signaling waveforms. The multipath-Doppler shifted waveforms constitute an approximately orthogonal basis and the corresponding signal representation naturally connects the various channel eeects. First, all processing relating to multipath propagation can be directly performed in the canonical coordinates. Second, the same coordinates provide a canonical subspace-based representation of the desired signal and interference which fully incorporates channel dispersion eeects. Finally, the maximally parsimonious nature of the coordinates and their simple computation aaord a direct handle on transceiver complexity. Various facets of the integrated framework are illustrated in the context of interference suppression, channel estimation, and diversity processing.
Existing subspace-based multiuser timing acquisition algorithmsfor code-division multiple access ... more Existing subspace-based multiuser timing acquisition algorithmsfor code-division multiple access systems do notaccount for the multipath channel effects satisfactorily. Wepresent a new timing acquisition framework that leveragesa canonical representation of the mobile wireless channelto fully exploit the underlying signal structure. The proposedapproach promises improved performance based onthree key advantages. First, it fully accounts for channeleffects in a parsimonious fashion....
Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)
Optimal detectors based on time-frequency/time-scale representations (TFRs/TSRs) admit a represen... more Optimal detectors based on time-frequency/time-scale representations (TFRs/TSRs) admit a representation in terms of a bank of spectrograms/scalograms that yields a large class of detectors. These range from the conventional matched filter to the more complex higher-rank detectors offering a superior performance in a wider variety of detection situations. In this paper, we optimize this complexity versus performance tradeoff by characterizing TFR/TSR detectors that optimize performance (based on the deflection criterion) for any given fixed rank. We also characterize the gain in performance as a function of increasing complexity thereby facilitating a judicious tradeoff. Our experience with real data shows that, in many cases, relatively low-rank optimal detectors can provide most of the gain in performance relative to matched-filter processors
A framework is proposed for distributing entanglement over multiple-input-multiple-output (MIMO) ... more A framework is proposed for distributing entanglement over multiple-input-multiple-output (MIMO) spatial multipath channels by sharing maximally-entangled photon pairs. An architecture based on lens arrays is outlined and initial results on the quality of entanglement presented.
Handbook on Array Processing and Sensor Networks, 2010
This chapter contains sections titled: Introduction and Overview Multipath Wireless Channel Model... more This chapter contains sections titled: Introduction and Overview Multipath Wireless Channel Modeling in Time, Frequency, and Space Point-to-Point MIMO Wireless Communication Systems Active Wireless Sensing with Wideband MIMO Transceivers Concluding Remarks References
IEEE Military Communications Conference, 2003. MILCOM 2003.
DATA VERSUS DECISlON FUSION FOR DISTRIBUTED CLASSIFICATION IN SENSOR NETWORKS Ashwin D'Costa... more DATA VERSUS DECISlON FUSION FOR DISTRIBUTED CLASSIFICATION IN SENSOR NETWORKS Ashwin D'Costa Akbar M. Sayeed ... These statistical properties of the SCRs can be made pre-cise via the sampling theorem for the spatially bandlimited signal field. I c DX Fig. ...
Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)
Joint signal representations of arbitrary variables extend the scope of joint time-frequency repr... more Joint signal representations of arbitrary variables extend the scope of joint time-frequency representations, and provide a useful description for a wide variety of nonstationary signal characteristics. Cohen's (see Prentice Hall, 1995) marginal-based theory for bilinear representations is canonical from a distributional viewpoint, whereas, from other perspectives, such as characterization of the effect of unitary signal transformations of interest, a covariance-based formulation is needed and more attractive. We present a simple covariance-based characterization of bilinear joint signal representations of arbitrary variables. The formulation is highlighted by its simple structure and interpretation, and naturally extends the concept of the corresponding linear representations.
Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380)
Even though broadband signaling and reception is often employed in practice for communication ove... more Even though broadband signaling and reception is often employed in practice for communication over time- and frequency-dispersive channels, existing receiver designs do not fully exploit the advantage of broadband signaling. We introduce a framework for time-frequency processing that is dictated by a canonical characterization of linear dispersive channels and fully utilizes the advantage of broadband signaling. The framework is based on processing in a natural time-frequency subspace defined by orthogonal time-frequency shifted copies of the transmitted broadband waveform. It generalizes existing receivers and suggests new designs that promise substantially improved performance compared to existing systems.
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).
Sensor networks provide virtual snapshots of the physical world via distributed wireless nodes th... more Sensor networks provide virtual snapshots of the physical world via distributed wireless nodes that can sense in different modalities, such as acoustic and seismic. Classification of objects moving through the sensor field is an important application that requires collaborative signal processing (CSP) between nodes. Given the limited resources of nodes, a key constraint is to exchange the least amount of information between them to achieve the desired performance. Two main forms of CSP are possible. Data fusion - exchange of low dimensional feature vectors - is needed between correlated nodes, in general, for optimal performance. Decision fusion $exchange of likelihood values - is sufficient between independent nodes. Decision fusion is generally preferable due to its lower communication burden. We study the CSP of multiple node measurements, each modeled as a Gaussian signal vector (corresponding to the target class) corrupted by additive white Gaussian noise. The measurements are partitioned into groups. The signal components within each group are perfectly correlated whereas they vary independently between groups. Three classifiers are compared: the optimal maximum likelihood classifier; a data averaging classifier that treats all measurements as correlated; a decision fusion classifier that treats them all as independent. The performances of the three CSP classifiers are compared using analytical and numerical results based on real data. These indicate that the sub-optimal decision fusion classifier, that is most attractive in the context of sensor networks, is also a robust choice from a decision theoretic viewpoint.
1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999
... Eko N. Onggosanusi, Akbar M. Sayeed, and Barry D. Van Veen ... p=l,***,P<M; l=O,***,L. (11... more ... Eko N. Onggosanusi, Akbar M. Sayeed, and Barry D. Van Veen ... p=l,***,P<M; l=O,***,L. (11) The angles {e,} corresponding to the canonical spatial sam-pling in (4) and (5) are chosen so that {a(ep)} form a com-plete basis for M-dimensional space spanned by the array ...
Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)
Optimal multi-antenna wideband signaling schemes are derived for multipath channels assuming perf... more Optimal multi-antenna wideband signaling schemes are derived for multipath channels assuming perfect channel state information at the transmitter. The scheme that minimizes the bit-error-probability in the single-user case is a rank-one space-time beamformer which focuses the signal transmission in the direction of the most dominant channel mode. Several sub-optimal variations are discussed for multiuser applications. Simulation results are given to
Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002, 2002
ABSTRACT A low-complexity decoupled detection MIMO receiver structure is proposed for wireless sy... more ABSTRACT A low-complexity decoupled detection MIMO receiver structure is proposed for wireless systems with frequency-selective channels. This receiver structure is termed the decoupled Viterbi algorithm (DVA). In this structure, all the transmitted data streams are completely decoupled at the receiver and are detected independently. This structure can also be viewed as a variation of a MIMO minimum mean square error decision feedback sequence estimator (MMSE-DFSE) structure. Moreover, a certain MMSE optimization constraint, namely L-tap forward interference control (L-tap FIC), is needed to achieve complete decoupling of the transmitted data streams at the receiver. It is shown that the complexity of the DVA is &quot;linear&quot;, meaning it increases only linearly with the number of transmitted data streams. Compared with other receivers that have &quot;linear&quot; complexity, such as partitioned Viterbi algorithm (PVA) (Miller, C. et al., IEEE Trans. on Commun., vol.49, no.11, 2001), DVA provides an attractive alternative since it does not require interchange of tentative decisions between different detection branches.
Time-frequency representations (TFRs) provide a powerful and exible structure for designing optim... more Time-frequency representations (TFRs) provide a powerful and exible structure for designing optimal detectors in a variety of nonstationary scenarios. In this paper, we describe a TFR-based framework for optimal detection of arbitrary second-order stochastic signals, with certain unknown or random nuisance parameters, in the presence of Gaussian noise. The framework provides a useful model for many important applications including machine fault diag-nostics and radar/sonar. We emphasize a subspace-based formulation of such TFR detectors which can be exploited in a variety of ways to design new techniques. In particular , we explore an extension based on multi-channel/sensor measurements that are often available in practice to facilitate improved signal processing. In addition to potentially improved performance, the subspace-based interpretation of such multi-channel detectors provides useful information about the physical mechanisms underlying the signals of interest.
Code division multiple access (CDMA) has emerged as a dominant technology for meeting the physica... more Code division multiple access (CDMA) has emerged as a dominant technology for meeting the physical layer challenges of future wireless communication systems. Signal processing requirements in the physical layer are dictated by three major factors: multiaccess interference, multipath dispersion and fading, and transceiver complexity. Existing CDMA system designs reeect a piecemeal approach due to the lack of an eeective framework for jointly addressing these issues. We propose signal processing in canonical multipath-Doppler coordinates for attacking physical layer impairments in an integrated fashion. The canonical coordinates are derived from a fundamental characterization of channel propagation dynamics in terms of discrete multipath-delayed and Doppler-shifted copies of the spread-spectrum signaling waveforms. The multipath-Doppler shifted waveforms constitute an approximately orthogonal basis and the corresponding signal representation naturally connects the various channel eeects. First, all processing relating to multipath propagation can be directly performed in the canonical coordinates. Second, the same coordinates provide a canonical subspace-based representation of the desired signal and interference which fully incorporates channel dispersion eeects. Finally, the maximally parsimonious nature of the coordinates and their simple computation aaord a direct handle on transceiver complexity. Various facets of the integrated framework are illustrated in the context of interference suppression, channel estimation, and diversity processing.
Existing subspace-based multiuser timing acquisition algorithmsfor code-division multiple access ... more Existing subspace-based multiuser timing acquisition algorithmsfor code-division multiple access systems do notaccount for the multipath channel effects satisfactorily. Wepresent a new timing acquisition framework that leveragesa canonical representation of the mobile wireless channelto fully exploit the underlying signal structure. The proposedapproach promises improved performance based onthree key advantages. First, it fully accounts for channeleffects in a parsimonious fashion....
Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96)
Optimal detectors based on time-frequency/time-scale representations (TFRs/TSRs) admit a represen... more Optimal detectors based on time-frequency/time-scale representations (TFRs/TSRs) admit a representation in terms of a bank of spectrograms/scalograms that yields a large class of detectors. These range from the conventional matched filter to the more complex higher-rank detectors offering a superior performance in a wider variety of detection situations. In this paper, we optimize this complexity versus performance tradeoff by characterizing TFR/TSR detectors that optimize performance (based on the deflection criterion) for any given fixed rank. We also characterize the gain in performance as a function of increasing complexity thereby facilitating a judicious tradeoff. Our experience with real data shows that, in many cases, relatively low-rank optimal detectors can provide most of the gain in performance relative to matched-filter processors
A framework is proposed for distributing entanglement over multiple-input-multiple-output (MIMO) ... more A framework is proposed for distributing entanglement over multiple-input-multiple-output (MIMO) spatial multipath channels by sharing maximally-entangled photon pairs. An architecture based on lens arrays is outlined and initial results on the quality of entanglement presented.
Handbook on Array Processing and Sensor Networks, 2010
This chapter contains sections titled: Introduction and Overview Multipath Wireless Channel Model... more This chapter contains sections titled: Introduction and Overview Multipath Wireless Channel Modeling in Time, Frequency, and Space Point-to-Point MIMO Wireless Communication Systems Active Wireless Sensing with Wideband MIMO Transceivers Concluding Remarks References
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