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Fundamentals Of Statistical Signal Processing
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The article was published on 2001-03-16 and is currently open access. It has received 7058 citations till now. The article focuses on the topics: Statistical signal processing.read more
Citations
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Journal ArticleDOI
Supermodular Game for Power Control in TOA-Based Positioning
TL;DR: This paper addresses the problem of minimizing the energy cost of positioning nodes in a wireless sensor network, using time of arrival measurements and derives a solution based on modeling the positioning problem as a non-cooperative game that is supermodular and possesses a unique Nash equilibrium.
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OTFS Signaling for Uplink NOMA of Heterogeneous Mobility Users
TL;DR: This work develops an efficient iterative turbo receiver based on the principle of successive interference cancellation (SIC) to overcome the co-channel interference (CCI) and proposes two turbo detector algorithms: orthogonal approximate message passing with linear minimum mean squared error (OAMP-LMMSE) and Gaussian approximate message passed with expectation propagation (GAMP-EP).
Journal ArticleDOI
Unconditional Maximum Likelihood Performance at Finite Number of Samples and High Signal-to-Noise Ratio
TL;DR: This correspondence establishes the equivalence between the unconditional and the conditional maximum-likelihood criterions at high signal-to-noise ratio and proves the non-Gaussianity and thenon-efficiency of the unconditional maximum- likelihood estimator.
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SWIPT Massive MIMO Systems With Active Eavesdropping
TL;DR: Asymptotic expressions for a lower bound on ergodic secrecy rate (ESR) and AHE in large system limit are derived and used to optimize the power allocation for downlink SWIPT transmissions which include information signals, artificial noise and energy signal towards the IUs, and legitimate and illegitimate antennas of the EH, respectively.
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Methods of goodness of fit for GNSS interference detection
TL;DR: Two versions of a signal quality monitoring algorithm are proposed: one working exclusively precorrelation, the other providing postcorrelation information as well.
References
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Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Journal ArticleDOI
Fundamentals of statistical signal processing: estimation theory
TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Book
Probability, random variables and stochastic processes
TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
Book
Probability, random variables, and stochastic processes
TL;DR: In this paper, the meaning of probability and random variables are discussed, as well as the axioms of probability, and the concept of a random variable and repeated trials are discussed.
Book
Discrete-Time Signal Processing
TL;DR: In this paper, the authors provide a thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete time Fourier analysis.