Related papers: A Belief Propagation Based Framework for Soft Mult…

The belief propagation (BP) algorithm is an efficient way to solve "inference" problems in graphical models, such as Bayesian networks and Markov random fields. The system-state probability distribution of CSMA wireless networks is a Markov…

In this thesis, we study differential modulation schemes which do not need channel knowledge at the transmitter nor at the receiver. First, we consider single-antenna systems and investigate the use of Differential Amplitude Phase Shift…

Recently, filter bank multi-carrier spread spectrum (FBMC-SS) technology has been proposed for use in ultra-wideband (UWB) communication systems. It has been noted that, due to the spectral partitioning properties of the filter banks, a UWB…

We developed machine learning approaches for data-driven trellis-based soft symbol detection in coded transmission over intersymbol interference (ISI) channels in presence of bursty impulsive noise (IN), for example encountered in wireless…

We consider the CDMA (code-division multiple-access) multi-user detection problem for binary signals and additive white gaussian noise. We propose a spreading sequences scheme based on random sparse signatures, and a detection algorithm…

Generalized Spatial Modulation (GSM) is being considered for high capacity and energy-efficient networks of the future. However, signal detection due to inter-channel interference among the active antennas is a challenge in GSM systems and…

We investigate the application of the factor graph framework for blind joint channel estimation and symbol detection on time-variant linear inter-symbol interference channels. In particular, we consider the expectation maximization (EM)…

In recent years, there has been a growing interest in multiple access communication systems that spread their transmitted energy over very large bandwidths. These systems, which are referred to as ultra wide-band (UWB) systems, have various…

Error correction at short blocklengths remains a challenge for low-density parity-check (LDPC) codes, as belief propagation (BP) decoding is suboptimal compared to maximum-likelihood decoding (MLD). While BP rarely makes errors, it often…

Orthogonal time frequency space (OTFS) modulation has emerged as a robust solution for high-mobility wireless communications. However, conventional detection algorithms, such as linear equalizers and message passing (MP) methods, either…

The sum-product or belief propagation (BP) algorithm is a widely used message-passing technique for computing approximate marginals in graphical models. We introduce a new technique, called stochastic orthogonal series message-passing…

Precise localization and tracking of moving non-collaborative persons and objects using a network of ultra-wideband (UWB) radar nodes has been shown to represent a practical and effective approach. In UWB radar sensor networks (RSNs),…

Cell-free massive MIMO is a promising technology for beyond-5G networks. Through the deployment of many cooperating access points (AP), the technology can significantly enhance user coverage and spectral efficiency compared to traditional…

The rapid development of the mobile communications requires ever higher spectral efficiency. The non-orthogonal multiple access (NOMA) has emerged as a promising technology to further increase the access efficiency of wireless networks.…

This paper proposes a novel modulation and coding scheme (MCS) selection framework that integrates mutual information (MI) prediction based on vector similarity search (VSS) for massive multi-user multiple-input multiple-output orthogonal…

Communications in dispersive direct-sequence code-division multiple-access (DS-CDMA) channels suffer from intersymbol and multiple-access interference, which can significantly impair performance. Joint maximum \textit{a posteriori}…

This paper proposes a low-computational Bayesian algorithm for noisy sparse recovery (NSR), called BHT-BP. In this framework, we consider an LDPC-like measurement matrices which has a tree-structured property, and additive white Gaussian…

Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (iBDD) based on hard-decision channel outputs which entails a performance loss compared to a soft-decision decoder. Recently, several hybrid…

We describe a novel approach to statistical learning from particles tracked while moving in a random environment. The problem consists in inferring properties of the environment from recorded snapshots. We consider here the case of a fluid…

We present an exact method of greatly speeding up belief propagation (BP) for a wide variety of potential functions in pairwise MRFs and other graphical models. Specifically, our technique applies whenever the pairwise potentials have been…