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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

Complex ADMM-Net, a complex-valued neural network architecture inspired by the alternating direction method of multipliers (ADMM), is designed for interference removal in super-resolution stepped frequency radar angle-range-doppler imaging.…

Signal Processing · Electrical Eng. & Systems 2021-07-07 Jeremy Johnston , Yinchuan Li , Marco Lops , Xiaodong Wang

Large pre-trained language models contain societal biases and carry along these biases to downstream tasks. Current in-processing bias mitigation approaches (like adversarial training) impose debiasing by updating a model's parameters,…

Computation and Language · Computer Science 2023-06-21 Deepak Kumar , Oleg Lesota , George Zerveas , Daniel Cohen , Carsten Eickhoff , Markus Schedl , Navid Rekabsaz

Reconfigurable intelligent surface (RIS) based communications have emerged as a new paradigm. This letter proposes a differential reflecting modulation (DRM) scheme for RIS based communication systems. In DRM, information bits are jointly…

Signal Processing · Electrical Eng. & Systems 2020-11-04 Shuaishuai Guo , Jia Ye , Peng Zhang , Haixia Zhang , Mohamed-Slim Alouini

Adaptive gradient-based optimization methods such as \textsc{Adagrad}, \textsc{Rmsprop}, and \textsc{Adam} are widely used in solving large-scale machine learning problems including deep learning. A number of schemes have been proposed in…

Machine Learning · Computer Science 2019-05-30 Parvin Nazari , Davoud Ataee Tarzanagh , George Michailidis

Delay alignment modulation (DAM) has been recently proposed to enable manipulable channel delay spread for efficient single- or multi-carrier communications. In particular, with perfect delay alignment, inter-symbol interference (ISI) can…

Signal Processing · Electrical Eng. & Systems 2022-07-11 Zhiqiang Xiao , Yong Zeng

High resolution analog to digital converters (ADCs) are conventionally used at the receiver terminals to store an accurate digital representation of the received signal, thereby allowing for reliable decoding of transmitted messages.…

Information Theory · Computer Science 2021-12-07 Abbas Khalili , Farhad Shirani , Elza Erkip , Yonina C. Eldar

Hybrid analog-digital precoding architectures and low-resolution analog-to-digital converter (ADC) receivers are two solutions to reduce hardware cost and power consumption for millimeter wave (mmWave) multiple-input multiple-output (MIMO)…

Information Theory · Computer Science 2018-07-04 Hengtao He , Chao-Kai Wen , Shi Jin

For integrated sensing and communication (ISAC) systems, the channel information essential for communication and sensing tasks fluctuates across different timescales. Specifically, wireless sensing primarily focuses on acquiring path state…

Information Theory · Computer Science 2023-10-18 Zhiqiang Xiao , Yong Zeng , Fuxi Wen , Zaichen Zhang , Derrick Wing Kwan Ng

The Orthogonal Frequency Division Multiplexing based M-ary Frequency Shift Keying (OFDM-MFSK) is a noncoherent modulation scheme which merges MFSK with the OFDM waveform. It is designed to improve the receiver sensitivity in the hard…

Signal Processing · Electrical Eng. & Systems 2017-10-31 Ghaith Al-Juboori , Angela Doufexi , Andrew R. Nix

Analog-to-digital conversion (ADC) is a key bottleneck in scaling DSP-centric receiver architectures to multiGigabit/s speeds. Recent information-theoretic results, obtained under ideal channel conditions (perfect synchronization, no…

Information Theory · Computer Science 2011-12-21 Jaspreet Singh , Upamanyu Madhow

In this work we examine blind adaptive and iterative decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems in frequency selective channels. Code-constrained minimum variance (CMV) and constant…

Information Theory · Computer Science 2013-01-23 Rodrigo C. de Lamare , Raimundo Sampaio-Neto

We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the majority of existing methods, our approach is based on a variational formulation consisting of…

Numerical Analysis · Mathematics 2019-05-24 Omri Azencot , Wotao Yin , Andrea Bertozzi

Many modern computer vision and machine learning applications rely on solving difficult optimization problems that involve non-differentiable objective functions and constraints. The alternating direction method of multipliers (ADMM) is a…

Computer Vision and Pattern Recognition · Computer Science 2017-04-11 Zheng Xu , Mario A. T. Figueiredo , Xiaoming Yuan , Christoph Studer , Tom Goldstein

For distributed sensor/relay networks, high reliability and power efficiency are often required. However, several implementation issues arise in practice. One such problem is that all the distributed transmitters have limited power supply…

Information Theory · Computer Science 2015-08-05 Po-Chun Fu , Pei-Rong Li , Li-Ming Wei , Chang-Lin Chen , Che Lin

The advancement to 6G calls for waveforms that transcend static robustness to achieve intelligent adaptability. Affine Frequency Division Multiplexing (AFDM), despite its strength in doubly-dispersive channels, has been confined by chirp…

Information Theory · Computer Science 2025-12-17 Yewen Cao , Yulin Shao

This paper investigates the performance of the adaptive matched filtering (AMF) in cluttered environments, particularly when operating with superimposed signals. Since the instantaneous signal-to-clutter-plus-noise ratio (SCNR) is a random…

Information Theory · Computer Science 2025-12-10 Lei Xie , Hengtao He , Yifeng Xiong , Fan Liu , Shi Jin

Deep learning models for channel estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems often suffer from performance degradation under fast-fading channels and low-SNR scenarios. To address these limitations, we introduce…

Machine Learning · Computer Science 2025-05-15 Berkay Guler , Hamid Jafarkhani

The alternating direction method of multipliers (ADMM) is a versatile tool for solving a wide range of constrained optimization problems, with differentiable or non-differentiable objective functions. Unfortunately, its performance is…

Machine Learning · Computer Science 2017-07-20 Zheng Xu , Mario A. T. Figueiredo , Tom Goldstein

Automatic Modulation Classification (AMC) plays a significant role in modern cognitive and intelligent radio systems, where accurate identification of modulation is crucial for adaptive communication. The presence of heterogeneous wireless…

Signal Processing · Electrical Eng. & Systems 2025-08-12 K. A. Shahriar