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This paper investigates the symbol error probability~(SEP) of point-to-point massive multiple-input multiple-output (MIMO) systems using equally likely PAM, PSK, and square QAM signallings in the presence of transmitter correlation. The…

Information Theory · Computer Science 2019-01-03 Zheng Dong , Jian-Kang Zhang , He Chen

Asymptotic expressions of the mutual information between any discrete input and the corresponding output of the scalar additive white Gaussian noise channel are presented in the limit as the signal-to-noise ratio (SNR) tends to infinity.…

Information Theory · Computer Science 2014-04-23 Alex Alvarado , Fredrik Brannstrom , Erik Agrell , Tobias Koch

In this paper, we address the classical problem of maximum-likelihood (ML) detection of data in the presence of random phase noise. We consider a system, where the random phase noise affecting the received signal is first compensated by a…

Information Theory · Computer Science 2016-11-15 Rajet Krishnan , M. Reza Khanzadi , Thomas Eriksson , Tommy Svensson

This paper investigates beamforming schemes designed to minimize the symbol error probability (SEP) for an authorized user while guaranteeing that the likelihood of an eavesdropper correctly recovering symbols remains below a predefined…

Signal Processing · Electrical Eng. & Systems 2025-04-08 Nam Nguyen , An Vuong , Thuan Nguyen , Thinh Nguyen

We study non-coherent detection schemes for molecular communication (MC) systems that do not require knowledge of the channel state information (CSI). In particular, we first derive the optimal maximum likelihood (ML) multiple-symbol (MS)…

Information Theory · Computer Science 2017-07-28 Vahid Jamali , Nariman Farsad , Robert Schober , Andrea Goldsmith

This paper considers the problem of symbol detection in massive multiple-input multiple-output (MIMO) wireless communication systems. We consider hard-thresholding preceeded by two variants of the regularized least squares (RLS) decoder;…

Information Theory · Computer Science 2023-08-11 Ayed M. Alrashdi , Abla Kammoun , Ali H. Muqaibel , Tareq Y. Al-Naffouri

The maximum likelihood (ML) and maximum a posteriori (MAP) estimation techniques are widely used to address the direction-of-arrival (DOA) estimation problems, an important topic in sensor array processing. Conventionally the ML estimators…

Applications · Statistics 2016-03-31 Xin Zhang , Mohammed Nabil El Korso , Marius Pesavento

Inter-symbol interference (ISI) with heteroscedastic, or state-dependent, noise is a defining feature of molecular communication via diffusion (MCvD). However, such noise variance dependency across ISI states has not been systematically…

Information Theory · Computer Science 2026-03-09 Erencem Ozbey , H. Birkan Yilmaz , Chan-Byoung Chae

This paper focuses on the analysis and optimization of a class of linear one-bit precoding schemes for a downlink massive MIMO system under Rayleigh fading channels. The considered class of linear one-bit precoding is fairly general,…

Information Theory · Computer Science 2023-06-28 Zheyu Wu , Junjie Ma , Ya-Feng Liu , A. Lee Swindlehurst

Motivated by a recent surge of interest in convex optimization techniques, convexity/concavity properties of error rates of the maximum likelihood detector operating in the AWGN channel are studied and extended to frequency-flat slow-fading…

Information Theory · Computer Science 2016-11-17 Sergey Loyka , Victoria Kostina , Francois Gagnon

The performance of Maximum a posteriori (MAP) estimation is studied analytically for binary symmetric multi-channel Hidden Markov processes. We reduce the estimation problem to a 1D Ising spin model and define order parameters that…

Statistical Mechanics · Physics 2015-06-11 Avik Halder , Ansuman Adhikary

This paper addresses the adaptive radar target detection problem in the presence of Gaussian interference with unknown statistical properties. To this end, the problem is first formulated as a binary hypothesis test, and then we derive a…

Signal Processing · Electrical Eng. & Systems 2025-03-05 Chaoran Yin , Tianqi Wang , Linjie Yan , Chengpeng Hao , Alfonso Farina , Danilo Orlando

Inter-symbol interference (ISI) channels with data dependent Gauss Markov noise have been used to model read channels in magnetic recording and other data storage systems. The Viterbi algorithm can be adapted for performing maximum…

Information Theory · Computer Science 2010-06-28 Naveen Kumar , Aditya Ramamoorthy , Murti Salapaka

This paper considers maximum-a-posteriori (MAP) and linear discriminant based MAP detectors to detect changes in the mean and covariance of a stochastic input, driving specific network nodes, using noisy measurements from sensors…

Optimization and Control · Mathematics 2020-11-10 Rajasekhar Anguluri , Vaibhav Katewa , Sandip Roy , Fabio Pasqualetti

Channel and frequency offset estimation is a classic topic with a large body of prior work using mainly maximum likelihood (ML) approach together with Cram\'er-Rao Lower bounds (CRLB) analysis. We provide the maximum a posteriori (MAP)…

Signal Processing · Electrical Eng. & Systems 2019-05-13 Mingda Zhou , Zhe Feng , Xinming Huang , Youjian , Liu

We consider the problem of upper bounding the expected log-likelihood sub-optimality of the maximum likelihood estimate (MLE), or a conjugate maximum a posteriori (MAP) for an exponential family, in a non-asymptotic way. Surprisingly, we…

Machine Learning · Statistics 2021-11-15 Rémi Le Priol , Frederik Kunstner , Damien Scieur , Simon Lacoste-Julien

This paper introduces a random modulation technique that is decoupled from the channel matrix, allowing it to be applied to arbitrary norm-bounded and spectrally convergent channel matrices. The proposed random modulation constructs an…

Information Theory · Computer Science 2026-01-01 Lei Liu , Yuhao Chi , Shunqi Huang

In this work, we derive the maximum a posteriori (MAP) symbol detector for a multiple-input multiple-output system in the presence of Wiener phase noise due to noisy local oscillators. As in single-antenna systems, the computation of the…

Information Theory · Computer Science 2013-12-10 Rajet Krishnan , Giulio Colavolpe , Alexandre Graell i Amat , Thomas Eriksson

In this paper we are interested in empirical likelihood (EL) as a method of estimation, and we address the following two problems: (1) selecting among various empirical discrepancies in an EL framework and (2) demonstrating that EL has a…

Statistics Theory · Mathematics 2009-08-25 Marian Grendár , George Judge

When recovering an unknown signal from noisy measurements, the computational difficulty of performing optimal Bayesian MMSE (minimum mean squared error) inference often necessitates the use of maximum a posteriori (MAP) inference, a special…

Machine Learning · Statistics 2016-09-23 Madhu Advani , Surya Ganguli
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