Research Interests: Computer Science, Distributed Computing, Channel Estimation, Fading, Space Time, and 15 moreRate Adaptation, Throughput, Aloha, Forward Error Correction, Multiple-access Interference, Multipath Channels, Code Division Multiple Access, Electrical And Electronic Engineering, TWC, Interference Suppression, Adaptive arrays, Multipath Propagation, Direct sequence, Multipath channel, and Slotted Aloha
Research Interests:
In this paper, we consider the extension of the capabilities of autonomous underwater vehicles (AUV's) to operate in pairs, thus representing each pair of sonars as a bistatic sonar. We utilize principles from the emerging MIMO radar... more
In this paper, we consider the extension of the capabilities of autonomous underwater vehicles (AUV's) to operate in pairs, thus representing each pair of sonars as a bistatic sonar. We utilize principles from the emerging MIMO radar theory, considering both the sonar transmitter and the sonar receiver as systems of closely spaced antennas that transmit/receive multiple linearly independent waveforms. Our objective is to formulate a covariance matrix that allows independent direction of arrival (DOA), direction of departure (DOD), and target strength estimation with reduced complexity. Simulation results demonstrate the effectiveness of the proposed method.
Research Interests:
Research Interests:
Research Interests:
Derived from statistical conditional optimization criteria, the auxiliary-vector (AV) detection algorithm starts from the target vector and adding non-orthogonal auxiliary vector components generates an infinite sequence of tests that... more
Derived from statistical conditional optimization criteria, the auxiliary-vector (AV) detection algorithm starts from the target vector and adding non-orthogonal auxiliary vector components generates an infinite sequence of tests that converges to the ideal matched filter (MF) processor for any positive definite input autocorrelation matrix. When the input autocorrelation matrix is replaced by a conventional sample-average estimate, the algorithm effectively generates
Research Interests:
AbstractWe derive new bounds on the aperiodic total squared correlation (ATSC) of binary antipodal signature sets for any number of signatures K and any signature length L. We then present optimal designs that achieve the new bounds for... more
AbstractWe derive new bounds on the aperiodic total squared correlation (ATSC) of binary antipodal signature sets for any number of signatures K and any signature length L. We then present optimal designs that achieve the new bounds for several (K, L) cases. As an ...
Research Interests:
The classical problem of detecting a complex signal of unknown amplitude in colored Gaussian noise is revisited in the context of adaptive detection with limited training data via the auxiliary-vector (AV) filter estimation algorithm.... more
The classical problem of detecting a complex signal of unknown amplitude in colored Gaussian noise is revisited in the context of adaptive detection with limited training data via the auxiliary-vector (AV) filter estimation algorithm. Based on statistical conditional optimization criteria, the iterative AV algorithm starts from the target vector and adding non-orthogonal auxiliary vector components generates an infinite sequence of
Research Interests:
Research Interests:
Research Interests: Mathematics, Computer Science, Artificial Intelligence, Medicine, Multidisciplinary, and 15 moreGeneralization, Approximation, Cross Validation, Multilayer Perceptron, Overfitting, Cross Entropy, Backpropagation, Gaussian Mixture, Gaussian Process, Input Output, Stochastic, Probability Density Function, Perceptron, K means Clustering, and Synthetic Data Generation
Research Interests:
Sequence detection offers improved error-rate performance over conventional symbol-by-symbol detection when channel knowledge is not available at the receiver end. However, maximum-likelihood (ML) noncoherent sequence detection is proven... more
Sequence detection offers improved error-rate performance over conventional symbol-by-symbol detection when channel knowledge is not available at the receiver end. However, maximum-likelihood (ML) noncoherent sequence detection is proven to be notoriously intractable in many communication settings. In this work, we develop a new ML sequence detector for pulse-amplitude modulation (PAM) or quadrature-amplitude modulation (QAM) transmissions in unknown Rayleigh fading. Our detector identifies the ML sequence with overall polynomial complexity. This is possible via an auxiliary-angle approach that unlocks a low-rank property of the ML detection problem, reduces the exponential-size set of solution sequences to a polynomial-size set of candidates, and guarantees that the ML sequence is always contained in this substantially smaller set.
Research Interests:
Research Interests:
ABSTRACT The recent increased interest in massive multiple-input multiple-output systems, combined with the cost of the analog RF chains, necessitates the use of efficient antenna selection (AS) schemes. Capacity or SNR optimal AS has... more
ABSTRACT The recent increased interest in massive multiple-input multiple-output systems, combined with the cost of the analog RF chains, necessitates the use of efficient antenna selection (AS) schemes. Capacity or SNR optimal AS has been considered to require an exhaustive search among all possible antenna subsets. In this work, we identify in polynomial time a polynomial-size collection of antenna subsets that contains the one that maximizes the post-processing receiver SNR when two receive and an arbitrary number of selected transmit antennas are employed.