123 citations · 294 across the 27 of their papers we have counts for
20 papers · 1 filter
On the Entropy of a Random Geometric Graph
Praneeth Kumar Vippathalla, Justin P. Coon, Mihai-Alin Badiu
In this paper, we study the entropy of a hard random geometric graph (RGG), a commonly used model for spatial networks, where the connectivity is governed by the distances between…
Rate-Distortion-Perception Function of Bernoulli Vector Sources
Praneeth Kumar Vippathalla, Mihai-Alin Badiu, Justin P. Coon
In this paper, we consider the rate-distortion-perception (RDP) trade-off for the lossy compression of a Bernoulli vector source, which is a finite collection of independent binary…
Graph Compression with Side Information at the Decoder
Praneeth Kumar Vippathalla, Mihai-Alin Badiu, Justin P. Coon
In this paper, we study the problem of graph compression with side information at the decoder. The focus is on the situation when an unlabelled graph (which is also referred to as…
Rate-Distortion Function of the Stochastic Block Model
Martin Wachiye Wafula, Praneeth Kumar Vippathalla, Justin Coon +1
The stochastic block model (SBM) is extensively used to model networks in which users belong to certain communities. In recent years, the study of information-theoretic compression…
On Random Tree Structures, Their Entropy, and Compression
Amirmohammad Farzaneh, Mihai-Alin Badiu, Justin P. Coon
Measuring the complexity of tree structures can be beneficial in areas that use tree data structures for storage, communication, and processing purposes. This complexity can then b…
Performance Analysis of IOS-Assisted NOMA System with Channel Correlation and Phase Errors
Tianxiong Wang, Mihai-Alin Badiu, Gaojie Chen +1
In this paper, we investigate the performance of an intelligent omni-surface (IOS) assisted downlink non-orthogonal multiple access (NOMA) network with phase quantization errors an…
Structural Complexity of One-Dimensional Random Geometric Graphs
Mihai-Alin Badiu, Justin P. Coon
We study the richness of the ensemble of graphical structures (i.e., unlabeled graphs) of the one-dimensional random geometric graph model defined by nodes randomly scattered i…
BernoulliZip: a Compression Algorithm for Bernoulli Processes and Erdos-Renyi Graphs
Amirmohammad Farzaneh, Mihai-Alin Badiu, Justin P. Coon
A novel compression scheme for compressing the outcome of independent Bernoulli trials is introduced and analysed. The resulting algorithm, BernoulliZip, is a fast and near-opt…
A Framework for Characterising the Value of Information in Hidden Markov Models
Zijing Wang, Mihai-Alin Badiu, Justin P. Coon
In this paper, a general framework is formalised to characterise the value of information (VoI) in hidden Markov models. Specifically, the VoI is defined as the mutual information…
A Value of Information Framework for Latent Variable Models
Zijing Wang, Mihai-Alin Badiu, Justin P. Coon
In this paper, a general value of information (VoI) framework is formalised for latent variable models. In particular, the mutual information between the current status at the sour…
Model-Based Detector for SSDs in the Presence of Inter-cell Interference
Hachem Yassine, Mihai-Alin Badiu, Justin Coon
In this paper, we consider the problem of reducing the bit error rate of flash-based solid state drives (SSDs) when cells are subject to inter-cell interference (ICI). By observing…
Binary-Tree Encoding for Uniform Binary Sources in Index Modulation Systems
Justin P. Coon, Mihai-Alin Badiu, Ye Liu +2
The problem of designing bit-to-pattern mappings and power allocation schemes for orthogonal frequency-division multiplexing (OFDM) systems that employ subcarrier index modulation…
Entropy Rate of Time-Varying Wireless Networks
Arta Cika, Mihai-Alin Badiu, Justin P. Coon +1
In this paper, we present a detailed framework to analyze the evolution of the random topology of a time-varying wireless network via the information theoretic notion of entropy ra…
Variational Bayesian Line Spectral Estimation with Multiple Measurement Vectors
Jiang Zhu, Qi Zhang, Peter Gerstoft +2
In this paper, the line spectral estimation (LSE) problem with multiple measurement vectors (MMVs) is studied utilizing the Bayesian methods. Motivated by the recently proposed var…
On the Distribution of Random Geometric Graphs
Mihai-Alin Badiu, Justin P. Coon
Random geometric graphs (RGGs) are commonly used to model networked systems that depend on the underlying spatial embedding. We concern ourselves with the probability distribution…
Variational Bayesian Inference of Line Spectra
Mihai-Alin Badiu, Thomas Lundgaard Hansen, Bernard Henri Fleury
In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a…
An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation
Thomas L. Hansen, Peter B. Jørgensen, Mihai-Alin Badiu +1
In this work we design a receiver that iteratively passes soft information between the channel estimation and data decoding stages. The receiver incorporates sparsity-based paramet…
Distributed Iterative Processing for Interference Channels with Receiver Cooperation
Mihai-Alin Badiu, Carles Navarro Manchón, Vasile Bota +1
We propose a framework for the derivation and evaluation of distributed iterative algorithms for receiver cooperation in interference-limited wireless systems. Our approach views t…
Message-Passing Algorithms for Channel Estimation and Decoding Using Approximate Inference
Mihai-Alin Badiu, Gunvor Elisabeth Kirkelund, Carles Navarro Manchón +2
We design iterative receiver schemes for a generic wireless communication system by treating channel estimation and information decoding as an inference problem in graphical models…
Merging Belief Propagation and the Mean Field Approximation: A Free Energy Approach
Erwin Riegler, Gunvor Elisabeth Kirkelund, Carles Navarro Manchón +2
We present a joint message passing approach that combines belief propagation and the mean field approximation. Our analysis is based on the region-based free energy approximation m…