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Integrated Sensing and Communications (ISAC) is emerging as a key paradigm for future Sixth-Generation (6G) networks, with communication-centric designs favored for their compatibility with existing standards. Communication signals contain…

Signal Processing · Electrical Eng. & Systems 2026-05-14 Mathieu Reniers , Martin Willame , Jérôme Louveaux , Luc Vandendorpe

This paper presents a time-frequency phase-coded sub-Nyquist sampling orthogonal frequency division multiplexing (PC-SNS-OFDM) radar system to reduce the analog-to-digital converter (ADC) sampling rate without any additional hardware or…

Signal Processing · Electrical Eng. & Systems 2024-03-22 Seonghyeon Kang , Kawon Han , Songcheol Hong

Chirp waveform plays a significant role in radar and communication systems for its ability of pulse compression and spread spectrum. This paper presents a principle of orthogonally multiplexing a bank of linear chirp waveforms within the…

Information Theory · Computer Science 2016-01-26 Xing Ouyang , Jian Zhao

Non-orthogonal multiple access (NOMA) is envisioned as an efficient candidate for future communication systems. This letter proposes a novel orthogonal frequency division multiplexing (OFDM) with index modulation (IM)-based NOMA scheme,…

Signal Processing · Electrical Eng. & Systems 2020-04-20 Emre Arslan , Ali Tugberk Dogukan , Ertugrul Basar

Dual-function radar-communication (DFRC) systems, which can efficiently utilize the congested spectrum and costly hardware resources by employing one common waveform for both sensing and communication (S&C), have attracted increasing…

Information Theory · Computer Science 2022-08-08 Zichao Xiao , Rang Liu , Ming Li , Yang Liu , Qian Liu

Wireless communication is the most effective communication to convey audio or video information among the population. It enables the masses to connect throughout the world. Wireless technologies improve the lifestyle of individuals in rural…

Signal Processing · Electrical Eng. & Systems 2020-02-13 Usha S. M , Mahesh H. B

In general, reliable communication via multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) requires accurate channel estimation at the receiver. The existing literature largely focuses on denoising…

Signal Processing · Electrical Eng. & Systems 2025-08-12 Myeung Suk Oh , Seyyedali Hosseinalipour , Taejoon Kim , Christopher G. Brinton , David J. Love

In this work, we discuss techniques for coherently detecting turbo coded orthogonal frequency division multiplexed (OFDM) signals, transmitted through frequency selective Rayleigh (the magnitude of each channel tap is Rayleigh distributed)…

Information Theory · Computer Science 2015-11-04 K. Vasudevan

This paper presents a principled approach for detecting out-of-distribution (OOD) samples in deep neural networks (DNN). Modeling probability distributions on deep features has recently emerged as an effective, yet computationally cheap…

Machine Learning · Computer Science 2020-12-09 Ibrahima Ndiour , Nilesh Ahuja , Omesh Tickoo

This paper addresses channel estimation and data equalization on frequency-selective 1-bit quantized Multiple Input-Multiple Output (MIMO) systems. No joint processing or Channel State Information is assumed at the transmitter, and…

Information Theory · Computer Science 2021-03-09 Javier García , Jawad Munir , Kilian Roth , Josef A. Nossek

The use of up to hundreds of antennas in massive multi-user (MU) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) poses a complexity challenge for digital predistortion (DPD) aiming to linearize the…

Signal Processing · Electrical Eng. & Systems 2024-10-25 Yibo Wu , Ulf Gustavsson , Mikko Valkama , Alexandre Graell i Amat , Henk Wymeersch

Recently, deep neural network (DNN) has been widely adopted in the design of intelligent communication systems thanks to its strong learning ability and low testing complexity. However, most current offline DNN-based methods still suffer…

Information Theory · Computer Science 2022-02-08 Jiabao Gao , Caijun Zhong , Geoffrey Ye Li , Zhaoyang Zhang

Orthogonal time frequency space (OTFS) modulation is a recently proposed waveform for reliable communication in high-speed vehicular communication scenarios. It has better resilience to inter-carrier interference (ICI) than orthogonal…

Information Theory · Computer Science 2020-01-29 Vivek Rangamgari , Shashank Tiwari , Suvra Sekhar Das , Subhas Chandra Mondal

Orthogonal frequency division multiplexing (OFDM) based non-orthogonal multiple access (NOMA) has increased complexity and reduced spectral efficiency in visible light communications (VLC) NOMA compared to radiofrequency NOMA due to…

Signal Processing · Electrical Eng. & Systems 2020-11-24 T. Uday , Abhinav Kumar , L. Natarajan

Sensing emerges as a critical challenge in 6G networks, which require simultaneous communication and target sensing capabilities. State-of-the-art super-resolution techniques for the direction of arrival (DoA) estimation encounter…

Signal Processing · Electrical Eng. & Systems 2025-06-17 Murat Babek Salman , Emil Björnson

Multi-input multi-output orthogonal frequency division multiplexing (MIMO OFDM) is a key technology for mobile communication systems. However, due to the issue of high peak-to-average power ratio (PAPR), the OFDM symbols may suffer from…

Signal Processing · Electrical Eng. & Systems 2021-06-01 Liangyuan Xu , Feifei Gao , Wei Zhang , Shaodan Ma

Distribution network reconfiguration (DNR) is a tool used by operators to balance line load flows and mitigate losses. As distributed generation and flexible load adoption increases, the impact of DNR on the security, efficiency, and…

In this letter, we propose a power allocation scheme for relayed orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. The proposed power allocation scheme replies on artificial neural network (ANN) and deep…

Information Theory · Computer Science 2020-10-27 Jiusi Zhou , Shuping Dang , Basem Shihada , Mohamed-Slim Alouini

Optimal margin Distribution Machine (ODM) is a newly proposed statistical learning framework rooting in the novel margin theory, which demonstrates better generalization performance than the traditional large margin based counterparts.…

Machine Learning · Computer Science 2023-06-13 Yilin Wang , Nan Cao , Teng Zhang , Xuanhua Shi , Hai Jin

In this paper, a new modulation method defined as Ramanujan Periodic Subspace Division Multiplexing (RPSDM) is proposed using Ramanujan subspaces. Each subspace contains an integer valued Ramanujan Sum (RS) and its circular downshifts as a…

Signal Processing · Electrical Eng. & Systems 2019-04-30 Goli Srikanth , Vijay Kumar Chakka , Shaik Basheeruddin Shah