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We study the regulation of a monopolistic firm using a robust-design approach. We solve for the policy that minimizes the regulator's worst-case regret, where the regret is the difference between his complete-information payoff minus his…

Theoretical Economics · Economics 2019-10-11 Yingni Guo , Eran Shmaya

This paper proposes two low-complexity iterative algorithms to compute the capacity of a single-user multiple-input multiple-output channel with per-antenna power constraint. The first method results from manipulating the optimality…

Information Theory · Computer Science 2017-05-18 Thuy M. Pham , Ronan Farrell , Le-Nam Tran

This paper describes an optimisation methodology that has been specifically developed for engineering design problems. The methodology is based on a Tabu search (TS) algorithm that has been shown to find high quality solutions with a…

Optimization and Control · Mathematics 2016-06-21 Andy M. Connor , P. John Clarkson , Shahrokh Shahpar , Paul Leonard

The spectral efficiency of wireless networks can be made nearly infinitely large by deploying many antennas, but the deployment of very many antennas requires new topologies beyond the compact and discrete antenna arrays used by…

Information Theory · Computer Science 2022-03-29 Emil Björnson , Luca Sanguinetti

One of the most common control decisions faced by power system operators is the question of how to dispatch generation to meet demand for power. This is a complex optimization problem that includes many nonlinear, non convex constraints as…

Optimization and Control · Mathematics 2013-06-14 Russell Bent , Daniel Bienstock , Michael Chertkov

Topological design of terrestrial networks for communication via satellites is studied in the paper. Quantitative model of the network cost-analysis minimizing the total transmission and switching cost is described. Several algorithms…

Networking and Internet Architecture · Computer Science 2010-02-19 Boris S. Verkhovsky

Historically, the design of antenna arrays has evolved separately from Shannon theory. Shannon theory adopts a probabilistic approach in the design of communication systems, while antenna design approaches have relied on deterministic…

The aim of this letter is to explore the capability of pinching-antenna systems to construct line-of-sight (LoS) links in the presence of LoS blockages. Specifically, pinching antennas are pre-installed at preconfigured positions along…

Signal Processing · Electrical Eng. & Systems 2025-07-15 Kaidi Wang , Chongjun Ouyang , Yuanwei Liu , Zhiguo Ding

Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula…

Methodology · Statistics 2014-06-12 Elisa Perrone , Werner G. Müller

We propose a model-based, automated, bottom-up approach for design, which is applicable to various physical domains, but in this work we focus on the electrical domain. This bottom-up approach is based on a meta-topology in which each link…

Optimization and Control · Mathematics 2023-02-17 Ion Matei , Maksym Zhenirovskyy , John Maxwell , Johan de Kleer

Filterless optical transport networks relies on passive optical interconnections between nodes, i.e., on splitters/couplers and amplifiers. While different studies have investigated their design, none of them offer a solution for an optimal…

Networking and Internet Architecture · Computer Science 2021-01-05 Brigitte Jaumard , Yan Wang

Densifying the network and deploying more antennas at each access point are two principal ways to boost the capacity of wireless networks. However, due to the complicated distributions of random signal and interference channel gains,…

Information Theory · Computer Science 2017-05-03 Xianghao Yu , Chang Li , Jun Zhang , Khaled B. Letaief

Multiple-antenna systems is a key technique to serve multiple users in future wireless systems. For low energy consumption and hardware complexity we first consider transmit symbols with constant magnitude and then 1-bit digital-to-analog…

Information Theory · Computer Science 2018-01-18 Lukas T. N. Landau , Rodrigo C. de Lamare

Efficient resource allocation with hybrid precoder design is essential for massive MIMO systems operating in millimeter wave (mmW) domain. Owing to a higher energy efficiency and a lower complexity of a partially connected hybrid…

Information Theory · Computer Science 2021-02-03 Salman Khalid , Waqas bin Abbas , Farhan Khalid

We consider rather a general class of multi-level optimization problems, where a convex objective function is to be minimized subject to constraints of optimality of nested convex optimization problems. As a special case, we consider a…

Optimization and Control · Mathematics 2024-04-30 Allahkaram Shafiei , Vyacheslav Kungurtsev , Jakub Marecek

A general class of nonconvex optimization problems is considered, where the penalty is the composition of a linear operator with a nonsmooth nonconvex mapping, which is concave on the positive real line. The necessary optimality condition…

Optimization and Control · Mathematics 2018-04-23 Daria Ghilli , Karl Kunisch

Stochastic optimization of continuous objectives is at the heart of modern machine learning. However, many important problems are of discrete nature and often involve submodular objectives. We seek to unleash the power of stochastic…

Machine Learning · Computer Science 2017-11-07 Mohammad Reza Karimi , Mario Lucic , Hamed Hassani , Andreas Krause

This article investigates the integration of movable antennas (MAs) into multicast communication systems. By discretizing the motion of the MAs, a novel MA-assisted multicast transmission architecture is formulated. An alternating…

Signal Processing · Electrical Eng. & Systems 2025-05-16 Zhenqiao Cheng , Nanxi Li , Jianchi Zhu , Chongjun Ouyang , Xingqi Zhang

This paper considers the design of optimal resource allocation policies in wireless communication systems which are generically modeled as a functional optimization problem with stochastic constraints. These optimization problems have the…

Machine Learning · Computer Science 2022-02-08 Mark Eisen , Clark Zhang , Luiz F. O. Chamon , Daniel D. Lee , Alejandro Ribeiro

The optimal solution to an optimization problem depends on the problem's objective function, constraints, and size. While deep neural networks (DNNs) have proven effective in solving optimization problems, changes in the problem's size,…

Machine Learning · Computer Science 2025-02-17 Nikos A. Mitsiou , Pavlos S. Bouzinis , Panagiotis G. Sarigiannidis , George K. Karagiannidis