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Hayssam Dahrouj

Researcher at King Abdullah University of Science and Technology

Publications -  111
Citations -  2674

Hayssam Dahrouj is an academic researcher from King Abdullah University of Science and Technology. The author has contributed to research in topics: Backhaul (telecommunications) & Radio access network. The author has an hindex of 19, co-authored 100 publications receiving 1971 citations. Previous affiliations of Hayssam Dahrouj include Ruhr University Bochum & Effat University.

Papers
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Journal ArticleDOI

Coordinated beamforming for the multicell multi-antenna wireless system

TL;DR: Simulation results suggest that coordinating the beamforming vectors alone already provide appreciable performance improvements as compared to the conventional per-cell optimized network.
Journal ArticleDOI

CubeSat Communications: Recent Advances and Future Challenges

TL;DR: This paper presents a holistic overview of various aspects of CubeSat missions and provides a thorough review of the topic from both academic and industrial perspectives, and presents recent advances in the area of Cubesat communications.
Proceedings ArticleDOI

Coordinated beamforming for the multi-cell multi-antenna wireless system

TL;DR: Simulation results show that a coordinated beamforming system can significantly outperform a conventional system with per-cell signal processing and also naturally leads to a distributed implementation.
Journal ArticleDOI

Cost-effective hybrid RF/FSO backhaul solution for next generation wireless systems

TL;DR: A cost-effective hybrid RF/free-space optical (FSO) solution to combine the advantages of RF backhauls (low cost, NLOS applications) and FSO backhauling (high-rate, low latency) is proposed.
Journal ArticleDOI

Intelligent Surfaces for 6G Wireless Networks: A Survey of Optimization and Performance Analysis Techniques

TL;DR: This paper provides a unique blend that surveys the principles of operation of LIS, together with their optimization and performance analysis frameworks, and presents various optimization frameworks that aim to optimize specific objectives, namely, maximizing energy efficiency, sum- rate, secrecy-rate, and coverage.