Mohsen Pourghasemian

Mobility-Aware Robust Resource Allocation and Computation Migration in Heterogeneous Virtualized Vehicular Networks by Low Overhead Multi-Agent DRL-based Approach

In emerging vehicular networks, delay-sensitive tasks can be processed in real time by offloading to

the edge computing servers. Unlike the legacy scenarios, in this paper a novel data offloading/delivery

decision making framework is proposed, where users have the option to divide their task into several

portions and partially offload their data to a complex multi-access edge computing (MEC) environment,

consisting of several MEC servers located on road side units (RSUs), base stations (BSs), and unused

Categories:: Machine Learning

314 Views

AI-Based Secure NOMA and Cognitive Radio enabled Green Communications: Channel State Information and Battery Value Uncertainties

In this paper, the security-aware robust resource allocation in energy harvesting cognitive radio networks is considered with cooperation between two transmitters while there are uncertainties in channel gains and battery energy value. To be specific, the primary access point harvests energy from the green resource and uses time switching protocol to send the energy and data towards the secondary access point (SAP).

Categories:: Artificial Intelligence
Machine Learning
Communications

464 Views

AI-Based and Mobility-aware Energy Efficient Resource Allocation and Trajectory Design for NFV enabled Aerial Networks

This repository includes the DDPG, MADDPG, HHCDA, and MAHHCDA based on the paper "AI-Based and Mobility-aware Energy Efficient Resource Allocation and Trajectory Design for NFV enabled Aerial Networks".

Categories:: Machine Learning
Communications

426 Views