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This paper presents a novel deep reinforcement learning-based resource allocation technique for the multi-agent environment presented by a cognitive radio network where the interactions of the agents during learning may lead to a…

Machine Learning · Computer Science 2022-05-30 Ankita Tondwalkar , Andres Kwasinski

This paper proposes a new multi-carrier system, called orthogonal code-based block transmission (OCBT). OCBT applies a time-spreading method with an orthogonal code to have a block signal structure and a windowing procedure to reduce the…

Information Theory · Computer Science 2017-05-03 Hyejin Kim , Insik Jung , Wonsuk Chung , Sooyong Choi , Daesik Hong

We propose a concept system termed distributed base station (DBS), which enables distributed transmit beamforming at large carrier wavelengths to achieve significant range extension and/or increased downlink data rate, providing a low-cost…

Information Theory · Computer Science 2018-03-09 Muhammed Faruk Gencel , Maryam Eslami Rasekh , Upamanyu Madhow

In this article, we study a Radio Resource Allocation (RRA) that was formulated as a non-convex optimization problem whose main aim is to maximize the spectral efficiency subject to satisfaction guarantees in multiservice wireless systems.…

This paper studies joint uplink (UL) and downlink (DL) resource allocation in user-centric orthogonal frequency division multiple access (OFDMA) cloud radio access network (CRAN), where the users select the distributed remote radio heads…

Information Theory · Computer Science 2019-06-21 Zehong Lin , Yuan Liu

In this paper, the distributed resource allocation optimization problem is investigated. The allocation decisions are made to minimize the sum of all the agents' local objective functions while satisfying both the global network resource…

Optimization and Control · Mathematics 2017-04-11 Peng Yi , Yiguang Hong , Feng Liu

In this work, the delay limited capacity (DLC) of orthogonal frequency division multiplexing (OFDM) systems is investigated. The analysis is organized into two parts. In the first part, the impact of system parameters on the OFDM DLC is…

Information Theory · Computer Science 2007-07-13 Gerhard Wunder , Thomas Michel

This paper presents a decentralized algorithm for solving distributed convex optimization problems in dynamic networks with time-varying objectives. The unique feature of the algorithm lies in its ability to accommodate a wide range of…

Optimization and Control · Mathematics 2023-07-12 Navneet Agrawal , Renato L. G. Cavalcante , Masahiro Yukawa , Slawomir Stanczak

In this paper, we study resource allocation algorithm design for multi-user orthogonal frequency division multiple access (OFDMA) ultra-reliable low latency communication (URLLC) in mobile edge computing (MEC) systems. To meet the stringent…

Information Theory · Computer Science 2022-11-10 Walid R. Ghanem , Vahid Jamali , Robert Schober

Offline Reinforcement Learning (RL) methods leverage previous experiences to learn better policies than the behavior policy used for data collection. However, they face challenges handling distribution shifts due to the lack of online…

Machine Learning · Computer Science 2025-06-09 Suzan Ece Ada , Erhan Oztop , Emre Ugur

We propose orthogonal frequency division multiplexing (OFDM), as a spectrally efficient multiplexing technique, for quantum key distribution (QKD) at the core of trustednode quantum networks. Two main schemes are proposed and analyzed in…

Quantum Physics · Physics 2015-11-24 Sima Bahrani , Mohsen Razavi , Jawad A. Salehi

In this research paper, an efficient routing protocol for all optical network (AOL) is proposed. The technique uses wavelength division multiplexing (WDM). The proposed one is different from the conventional AOL protocol in transmission of…

Networking and Internet Architecture · Computer Science 2014-07-25 Kazi Sakib , Mosaddek Hossain Kamal , Upama Kabir

The explosive growth of dynamic and heterogeneous data traffic brings great challenges for 5G and beyond mobile networks. To enhance the network capacity and reliability, we propose a learning-based dynamic time-frequency division duplexing…

Machine Learning · Computer Science 2023-03-22 Ziyan Yin , Zhe Wang , Jun Li , Ming Ding , Wen Chen , Shi Jin

Recently introduced distributed zeroth-order optimization (ZOO) algorithms have shown their utility in distributed reinforcement learning (RL). Unfortunately, in the gradient estimation process, almost all of them require random samples…

Systems and Control · Electrical Eng. & Systems 2024-05-06 Gangshan Jing , He Bai , Jemin George , Aranya Chakrabortty , Piyush K. Sharma

This report investigates the application of deep reinforcement learning (DRL) algorithms for dynamic resource allocation in wireless communication systems. An environment that includes a base station, multiple antennas, and user equipment…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-14 Shubham Malhotra , Fnu Yashu , Muhammad Saqib , Dipkumar Mehta , Jagdish Jangid , Sachin Dixit

Resource allocation is investigated to enhance the performance of device-to-device (D2D) cooperation in a fog radio access network (F-RAN) architecture. Our envisioned framework enables two D2D links to share certain orthogonal radio…

Information Theory · Computer Science 2021-04-16 Md. Zoheb Hassan , Md. Jahangir Hossain , Julian Cheng , Victor C. M. Leung

We address the problem of distributed resource allocation for multicast communication in device-to-device (D2D) enabled underlay cellular networks. The optimal resource allocation is crucial for maximizing the performance of such networks,…

Networking and Internet Architecture · Computer Science 2023-09-27 Mohd Saif Ali Khan , Ajay Bhardwaj , Samar Agnihotri

In this paper a unified approach for power allocation (PA) problem in multi-hop orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) relaying systems has been developed. In the proposed approach, we consider short and…

Information Theory · Computer Science 2015-08-07 Amin Azari , Jalil S. Harsini , Farshad Lahouti

This work proposes an integrated approach for optimising Federated Learning (FL) communication in dynamic and heterogeneous network environments. Leveraging the modular flexibility of the Open Radio Access Network (ORAN) architecture and…

Systems and Control · Electrical Eng. & Systems 2025-05-27 Abdelaziz Salama , Mohammed M. H. Qazzaz , Syed Danial Ali Shah , Maryam Hafeez , Syed Ali Zaidi

The optimal power flow (OPF) problem is fundamental in power system operations and planning. Large-scale renewable penetration in distribution networks calls for real-time feedback control, and hence the need for fast and distributed…

Optimization and Control · Mathematics 2016-05-19 Qiuyu Peng , Steven H. Low
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