Predictive Closed-Loop Service Automation in O-RAN based Network Slicing

no code implementations • 4 Feb 2022 • Joseph Thaliath, Solmaz Niknam, Sukhdeep Singh, Rahul Banerji, Navrati Saxena, Harpreet S. Dhillon, Jeffrey H. Reed, Ali Kashif Bashir, Avinash Bhat, Abhishek Roy

To cater to the dynamic service requirements of these verticals and meet the required quality-of-service (QoS) mentioned in the service-level agreement (SLA), network slices need to be isolated through dedicated elements and resources.

Management

Intelligent O-RAN for Beyond 5G and 6G Wireless Networks

no code implementations • 17 May 2020 • Solmaz Niknam, Abhishek Roy, Harpreet S. Dhillon, Sukhdeep Singh, Rahul Banerji, Jeffery H. Reed, Navrati Saxena, Seungil Yoon

Building on the principles of openness and intelligence, there has been a concerted global effort from the operators towards enhancing the radio access network (RAN) architecture.

Management

Reinforcement Learning for Mitigating Intermittent Interference in Terahertz Communication Networks

no code implementations • 10 Mar 2020 • Reza Barazideh, Omid Semiari, Solmaz Niknam, Balasubramaniam Natarajan

Emerging wireless services with extremely high data rate requirements, such as real-time extended reality applications, mandate novel solutions to further increase the capacity of future wireless networks.

reinforcement-learning Reinforcement Learning (RL)

Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges

no code implementations • 30 Jul 2019 • Solmaz Niknam, Harpreet S. Dhillon, Jeffery H. Reed

There is a growing interest in the wireless communications community to complement the traditional model-based design approaches with data-driven machine learning (ML)-based solutions.

Federated Learning Privacy Preserving