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Gaussian process (GP) emulator has been used as a surrogate model for predicting force field and molecular potential, to overcome the computational bottleneck of molecular dynamics simulation. Integrating both atomic force and energy in…

Chemical Physics · Physics 2022-05-13 Hao Li , Musen Zhou , Jessalyn Sebastian , Jianzhong Wu , Mengyang Gu

While the channel capacity reflects a theoretical upper bound on the achievable information transmission rate in the limit of infinitely many bits, it does not characterise the information transfer of a given encoding routine with finitely…

Neurons and Cognition · Quantitative Biology 2017-04-05 Sebastian Weichwald , Tatiana Fomina , Bernhard Schölkopf , Moritz Grosse-Wentrup

Motivated by the growing application of wireless multi-access networks with stringent delay constraints, we investigate the Gaussian multiple access channel (MAC) in the finite blocklength regime. Building upon information spectrum…

Information Theory · Computer Science 2013-09-11 Ebrahim MolavianJazi , J. Nicholas Laneman

The high computational cost of approaching the performance of Maximum-likelihood (ML) decoding has limited its practical use for decades. Because the complexity grows exponentially with the message length, researchers have spent years…

Signal Processing · Electrical Eng. & Systems 2026-04-21 Marwan Jalaleddine , Jiajie Li , Syed Mohsin Abbas , Warren J. Gross

Millimeter wave (mmWave) spectrum has drawn attention due to its tremendous available bandwidth. The high propagation losses in the mmWave bands necessitate beamforming with a large number of antennas. Traditionally each antenna is paired…

Information Theory · Computer Science 2018-05-31 Junmo Sung , Jinseok Choi , Brian L. Evans

Approximate dynamic programming is a popular method for solving large Markov decision processes. This paper describes a new class of approximate dynamic programming (ADP) methods- distributionally robust ADP-that address the curse of…

Machine Learning · Statistics 2012-05-22 Marek Petrik

Recent advances in deep learning for wireless communications have renewed interest in channel output feedback codes. In the additive white Gaussian broadcast channel with feedback (AWGN-BC-F), feedback can expand the channel capacity region…

Signal Processing · Electrical Eng. & Systems 2025-12-02 Jacqueline Malayter , Yingyao Zhou , Natasha Devroye , Chih-Chun Wang , Christopher Brinton , David J. Love

For 5G it will be important to leverage the available millimeter wave spectrum. To achieve an approximately omni- directional coverage with a similar effective antenna aperture compared to state of the art cellular systems, an antenna array…

Information Theory · Computer Science 2017-04-27 Kilian Roth , Josef A. Nossek

The Distributed Adaptive Signal Fusion (DASF) framework is a meta-algorithm for computing data-driven spatial filters in a distributed sensing platform with limited bandwidth and computational resources, such as a wireless sensor network.…

Signal Processing · Electrical Eng. & Systems 2024-05-07 Charles Hovine , Alexander Bertrand

Identification capacity has been established as a relevant performance metric for various goal-/task-oriented applications, where the receiver may be interested in only a particular message that represents an event or a task. For example,…

Information Theory · Computer Science 2025-08-27 Mohammad Javad Salariseddigh , Heinz Koeppl , Holger Boche , Vahid Jamali

$M$-ary signal transmission over AWGN channel with additive $Q$-ary interference where the sequence of i.i.d. interference symbols is known causally at the transmitter is considered. Shannon's theorem for channels with side information at…

Information Theory · Computer Science 2007-07-13 Hamid Farmanbar , Amir K. Khandani

We recently proved threshold saturation for spatially coupled sparse superposition codes on the additive white Gaussian noise channel. Here we generalize our analysis to a much broader setting. We show for any memoryless channel that…

Information Theory · Computer Science 2016-03-16 Jean Barbier , Mohamad Dia , Nicolas Macris

Sparse superposition codes, also called sparse regression codes (SPARCs), are a class of codes for efficient communication over the AWGN channel at rates approaching the channel capacity. In a standard SPARC, codewords are sparse linear…

Information Theory · Computer Science 2021-06-25 Cynthia Rush , Kuan Hsieh , Ramji Venkataramanan

We consider communication over the block noncoherent AWGN channel with low-precision Analog-to-Digital Converters (ADCs) at the receiver. For standard uniform Phase Shift Keying (PSK) modulation, we investigate the performance of a receiver…

Information Theory · Computer Science 2009-05-28 Jaspreet Singh , Upamanyu Madhow

Sparse superposition codes, or sparse regression codes (SPARCs), are a recent class of codes for reliable communication over the AWGN channel at rates approaching the channel capacity. Approximate message passing (AMP) decoding, a…

Information Theory · Computer Science 2019-04-24 Cynthia Rush , Ramji Venkataramanan

Within the family of guessing-based decoding algorithms, ordered reliability bits GRAND (ORBGRAND) has attracted considerable attention due to its efficient use of soft information and suitability for hardware implementation. It has also…

Information Theory · Computer Science 2026-05-05 Zhuang Li , Wenyi Zhang

In this letter, we investigate the performance of non-orthogonal multiple access (NOMA), under the assumption of generalized Gaussian noise (GGN), over Rayleigh fading channels. Specifically, we consider a NOMA system with $L$ users, each…

Signal Processing · Electrical Eng. & Systems 2020-05-12 Lina Bariah , Sami Muhaidat , Paschalis C. Sofotasios , Sanjeev Gurugopinath , Walaa Hamouda , Halim Yanikomeroglu

The use of 1-bit analog-to-digital converters (ADCs) is seen as a promising approach to significantly reduce the power consumption and hardware cost of multiple-input multiple-output (MIMO) receivers. However, the nonlinear distortion due…

Information Theory · Computer Science 2022-10-12 Neil Irwin Bernardo , Jingge Zhu , Yonina C. Eldar , Jamie Evans

This paper investigates the information-theoretic limits of energy-harvesting (EH) channels in the finite blocklength regime. The EH process is characterized by a sequence of i.i.d. random variables with finite variances. We use the…

Information Theory · Computer Science 2016-10-19 Silas L. Fong , Vincent Y. F. Tan , Jing Yang

This paper seeks an efficient algorithm for stochastic precoding to maximize the long-term average weighted sum rates throughout a multiple-input multiple-output (MIMO) network. Unlike many existing works that assume a particular…

Information Theory · Computer Science 2026-03-10 Wenyu Wang , Kaiming Shen