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Related papers: Sparsity Enhanced Decision Feedback Equalization

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This paper investigates the design and analysis of minimum mean square error (MMSE) turbo decision feedback equalization (DFE), with expectation propagation (EP), for single carrier modulations. Classical non iterative DFE structures have…

Signal Processing · Electrical Eng. & Systems 2018-07-03 Serdar Şahin , Antonio M. Cipriano , Charly Poulliat , Marie-Laure Boucheret

In this article, a new category of soft-input soft-output (SISO) minimum-mean square error (MMSE) finite-impulse response (FIR) decision feedback equalizers (DFEs) with iteration-wise static filters (i.e. iteration variant) is investigated.…

Signal Processing · Electrical Eng. & Systems 2020-01-29 Serdar Şahin , Antonio Maria Cipriano , Charly Poulliat , Marie-Laure Boucheret

Fiber optics is one of the highest bandwidth communication channel types in the current communication industry. The paper is to analyze a typical optical channel and perform channel equalization using an adaptive modified DFE with Activity…

Other Computer Science · Computer Science 2010-03-30 Tarek Hasan-Al-Mahmud , M. Mahbubur Rahman , Sumon Kumar Debnath

Reverberation can severely degrade the quality of speech signals recorded using microphones in an enclosure. In acoustic sensor networks with spatially distributed microphones, a similar dereverberation performance may be achieved using…

Audio and Speech Processing · Electrical Eng. & Systems 2026-02-04 Anselm Lohmann , Toon van Waterschoot , Joerg Bitzer , Simon Doclo

Affine Frequency Division Multiplexing (AFDM), which is based on discrete affine Fourier transform (DAFT), has recently been proposed for reliable communication in high-mobility scenarios. Two low complexity detectors for AFDM are…

Information Theory · Computer Science 2022-03-08 Ali Bemani , Nassar Ksairi , Marios Kountouris

Federated Learning (FL) enables multiple resource-constrained edge devices with varying levels of heterogeneity to collaboratively train a global model. However, devices with limited capacity can create bottlenecks and slow down model…

Machine Learning · Computer Science 2025-04-08 Afsaneh Mahanipour , Hana Khamfroush

Compressed sensing deals with the recovery of sparse signals from linear measurements. Without any additional information, it is possible to recover an $s$-sparse signal using $m \gtrsim s \log(d/s)$ measurements in a robust and stable way.…

Functional Analysis · Mathematics 2016-05-25 Axel Flinth

Compressed sensing aims to undersample certain high-dimensional signals, yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be recovered is sufficiently sparse in a…

Information Theory · Computer Science 2015-05-13 David L. Donoho , Arian Maleki , Andrea Montanari

This paper deals with the implementation of Least Mean Square (LMS) algorithm in Decision Feedback Equalizer (DFE) for removal of Inter Symbol Interference (ISI) at the receiver. The channel disrupts the transmitted signal by spreading it…

Artificial Intelligence · Computer Science 2012-08-13 Mohammad Havaei , Nandivada Krishna Prasad , Velleshala Sudheer

We propose a probabilistic framework for interpreting and developing hard thresholding sparse signal reconstruction methods and present several new algorithms based on this framework. The measurements follow an underdetermined linear model,…

Information Theory · Computer Science 2010-11-08 Kun Qiu , Aleksandar Dogandzic

One main challenge in federated learning is the large communication cost of exchanging weight updates from clients to the server at each round. While prior work has made great progress in compressing the weight updates through gradient…

Machine Learning · Computer Science 2023-02-10 Berivan Isik , Francesco Pase , Deniz Gunduz , Tsachy Weissman , Michele Zorzi

We focus on the problem of estimating the change in the dependency structures of two $p$-dimensional Gaussian Graphical models (GGMs). Previous studies for sparse change estimation in GGMs involve expensive and difficult non-smooth…

Machine Learning · Computer Science 2018-05-24 Beilun Wang , Arshdeep Sekhon , Yanjun Qi

The communication bottleneck has been a critical problem in large-scale distributed deep learning. In this work, we study distributed SGD with random block-wise sparsification as the gradient compressor, which is ring-allreduce compatible…

Machine Learning · Computer Science 2022-06-14 An Xu , Heng Huang

This paper describes the limiting behavior of linear and decision feedback equalizers (DFEs) in single/multiple antenna systems employing real/complex-valued modulation alphabets. The wideband frequency selective channel is modeled using a…

Information Theory · Computer Science 2013-07-16 Kiran Kuchi

Decentralized Federated Learning (DFL) enables collaborative model training without a central server but faces challenges in efficiency, stability, and trustworthiness due to communication and computational limitations among distributed…

Machine Learning · Computer Science 2025-03-18 Shan Sha , Shenglong Zhou , Lingchen Kong , Geoffrey Ye Li

Identifying the start time of a sequence of symbols received at the receiver, commonly referred to as \emph{frame synchronization}, is a critical task for achieving good performance in digital communications systems employing…

Signal Processing · Electrical Eng. & Systems 2020-07-14 Oren Kolaman , Ron Dabora

Any communication channel will usually distort the transmitted signal. This is especially true in the case of mobile systems, where multipath propagation causes the received signal to be seriously degraded. Over the years, many techniques…

Information Theory · Computer Science 2014-01-29 Felip Riera-Palou

In this paper, we consider diffusive molecular communication (MC) systems affected by signal-dependent diffusive noise, inter-symbol interference, and external noise. We design linear and nonlinear fractionally-spaced equalization schemes…

Information Theory · Computer Science 2020-04-28 Trang Ngoc Cao , Vahid Jamali , Nikola Zlatanov , Phee Lep Yeoh , Jamie Evans , Robert Schober

In this work we propose novel decision feedback (DF) detection algorithms with error propagation mitigation capabilities for multi-input multi-output (MIMO) spatial multiplexing systems based on multiple processing branches. The novel…

Information Theory · Computer Science 2013-04-18 R. C. de Lamare , D. Le Ruyet

We design a soft-in soft-out (SISO) decision feedback equalizer (DFE) that performs better than its linear counterpart in turbo equalizer (TE) setting. Unlike previously developed SISO-DFEs, the present DFE scheme relies on extrinsic…

Information Theory · Computer Science 2015-03-19 Seongwook Jeong , Jaekyun Moon
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