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In this paper, we propose a novel algorithm to optimize the energy-efficiency (EE) of orthogonal frequency division multiplexing-based cognitive radio systems under channel uncertainties. We formulate an optimization problem that guarantees…

Signal Processing · Electrical Eng. & Systems 2019-02-11 Ebrahim Bedeer , Osama Amin , Octavia A. Dobre , Mohamed H. Ahmed , Kareem E. Baddour

In this paper we propose an independent channel precoder for orthogonal frequency division multiplexing (OFDM) systems over fading channels. The design of the precoder is based on the information redistribution of the input modulated…

Information Theory · Computer Science 2025-01-27 Jorge Ortin , Paloma Garcia , Fernando Gutierrez , Antonio Valdovinos

In this paper, two new companders are designed to reduce the ratio of peak to average power (PAPR) experienced by filter bank multicarrier (FBMC) signals. Specifically, the compander basic model is generalized, which alter the distributed…

Signal Processing · Electrical Eng. & Systems 2021-08-10 Srinivas Ramavath , Umesh Chandra Samal

Orthogonal frequency division multiplexing (OFDM) is one of the most widely adopted waveforms for integrated sensing and communication (ISAC) systems, owing to its high spectral efficiency and compatibility with modern communication…

Signal Processing · Electrical Eng. & Systems 2025-10-16 Kawon Han , Kaitao Meng , Alexandra Chatzicharistou , Christos Masouros

The Single Carrier-Frequency Division Multiple Access (SC-FDMA) is a transmission technique used in the uplink of Long Term Evolution (LTE) and 5G systems, as it is characterized by reduced transmitted signal envelope fluctuations in…

Networking and Internet Architecture · Computer Science 2025-01-22 Pawel Kryszkiewicz

Nonlinear distortion in power amplifiers (PA) can significantly degrade performance of orthogonal frequency division multiplexed (OFDM) communication systems. This paper presents a joint maximum-likelihood channel frequency response and…

Information Theory · Computer Science 2016-12-30 Sergey V. Zhidkov

In end-to-end optimized learned image compression, it is standard practice to use a convolutional variational autoencoder with generalized divisive normalization (GDN) to transform images into a latent space. Recently, Operational Neural…

Image and Video Processing · Electrical Eng. & Systems 2021-05-31 M. Akın Yılmaz , Onur Keleş , Hilal Güven , A. Murat Tekalp , Junaid Malik , Serkan Kıranyaz

Classical methods for model order selection often fail in scenarios with low SNR or few snapshots. Deep learning-based methods are promising alternatives for such challenging situations as they compensate lack of information in the…

Signal Processing · Electrical Eng. & Systems 2023-12-07 Michael Baur , Franz Weißer , Benedikt Böck , Wolfgang Utschick

Recently, deep joint source channel coding (DJSCC) techniques have been extensively studied and have shown significant performance with limited bandwidth and low signal to noise ratio. Most DJSCC work considers discrete-time analog…

Signal Processing · Electrical Eng. & Systems 2023-09-22 Maolin Liu , Wei Chen , Jialong Xu , Bo Ai

Wireless communication systems that rely on orthogonal frequency-division multiplexing (OFDM) suffer from a high peak-to-average (power) ratio (PAR), which necessitates power-inefficient radio-frequency (RF) chains to avoid an increase in…

Information Theory · Computer Science 2021-07-16 Sueda Taner , Christoph Studer

Learning from an imbalanced distribution presents a major challenge in predictive modeling, as it generally leads to a reduction in the performance of standard algorithms. Various approaches exist to address this issue, but many of them…

Machine Learning · Computer Science 2024-12-11 Samuel Stocksieker , Denys Pommeret , Arthur Charpentier

In this article we research about underwater acoustics transceivers. As Underwater acoustic transceivers consume more power than Radio frequency transceivers. The techniques which are being utilized in radio frequency cannot be implemented…

Signal Processing · Electrical Eng. & Systems 2020-07-03 Waleed Raza , Xuefei Ma , Amir Ali , Zubair Ali Shah , Ghazanfar Mehdi

Orthogonal frequency division multiplexing (OFDM) is a modulation technique susceptible to source, channel and amplifier nonlinearities because of its high peak-to-average ratio (PAPR). The distortion gets worse by increasing the average…

Information Theory · Computer Science 2014-04-07 Mohammad Noshad , Maite Brandt-Pearce

We propose an enhanced spatial modulation (SM)-based scheme for indoor visible light communication systems. This scheme enhances the achievable throughput of conventional SM schemes by transmitting higher order complex modulation symbol,…

Signal Processing · Electrical Eng. & Systems 2022-01-21 Shimaa Naser , Lina Bariah , Sami Muhaidat , Mahmoud Al-Qutayri , Paschalis C. Sofotasios

Vector orthogonal frequency division multiplexing (V-OFDM) is a general system that builds a bridge between OFDM and single-carrier frequency domain equalization in terms of intersymbol interference and receiver complexity. In this paper,…

Information Theory · Computer Science 2015-12-22 Qi Feng , Xiang-Gen Xia , Zhihui Ye , Naitong Zhang

This paper proposes a novel parallel coding transmission strategy and an iterative detection and decoding receiver signal processing technique for orthogonal delay-Doppler division multiplexing (ODDM) modulation. Specifically, the proposed…

Information Theory · Computer Science 2025-02-04 Qi Li , Jinhong Yuan , Min Qiu

In dual-functional communication-radar systems, common radio frequency (RF) signals are used for both communication and detection. For better compatibility with existing communication systems, we adopt multiple-input multiple-output (MIMO)…

Information Theory · Computer Science 2022-10-14 Chen Zhong , Chunrong Gu , Lan Tang , Yechao Bai , Mengting Lou

Under a low Signal-to-Noise Ratio (SNR), the Orthogonal Frequency-Division Multiplexing (OFDM) signal symbol rate is limited. Existing carrier number estimation algorithms lack adequate methods to deal with low SNR. This paper proposes an…

Information Theory · Computer Science 2022-07-28 Zetian Qin , Yubai Li , Benye Niu , Qingyao Li , Renhao Xue

The data bottleneck has emerged as a fundamental challenge in learning based image restoration methods. Researchers have attempted to generate synthesized training data using paired or unpaired samples to address this challenge. This study…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Dihan Zheng , Yihang Zou , Xiaowen Zhang , Chenglong Bao

Recent studies have explored the use of deep generative models of speech spectra based of variational autoencoders (VAEs), combined with unsupervised noise models, to perform speech enhancement. These studies developed iterative algorithms…

Sound · Computer Science 2019-05-15 Manuel Pariente , Antoine Deleforge , Emmanuel Vincent