Blockchain applications in sustainable smart cities
Sustainable smart cities aim to optimize projected complexities, costs, and environmental
challenges accompanied by growing urbanization. The fundamental objectives of …
challenges accompanied by growing urbanization. The fundamental objectives of …
Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
A gentle introduction to reinforcement learning and its application in different fields
Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …
become one of the most important and useful technology. It is a learning method where a …
The role of llms in sustainable smart cities: Applications, challenges, and future directions
Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living
standards, facilitating the rapid expansion of urban areas while efficiently managing …
standards, facilitating the rapid expansion of urban areas while efficiently managing …
Optimal user scheduling in multi antenna system using multi agent reinforcement learning
Multiple Input Multiple Output (MIMO) systems have been gaining significant attention from
the research community due to their potential to improve data rates. However, a suitable …
the research community due to their potential to improve data rates. However, a suitable …
Joint power allocation and scheduling techniques for BER minimization in multiuser MIMO systems
In contrast to the 4G LTE, one of the key requirements of 5G and beyond networks is ultra-
high reliability. Towards this end, we investigate the problem of scheduling with joint power …
high reliability. Towards this end, we investigate the problem of scheduling with joint power …
[PDF][PDF] A New Processing Approach for Scheduling Time Minimization in 5G-IoT Networks.
AM Mahmood, AR Kareem - … Journal of Intelligent Engineering & Systems, 2021 - inass.org
Increasing the number of mobile network connections represented by humans and
machines leads to a higher demand for resources, which have to be allocated for all User …
machines leads to a higher demand for resources, which have to be allocated for all User …
A Hybrid Multi-Agent Reinforcement Learning Approach for Spectrum Sharing in Vehicular Networks
Efficient spectrum sharing is essential for maximizing data communication performance in
Vehicular Networks (VNs). In this article, we propose a novel hybrid framework that …
Vehicular Networks (VNs). In this article, we propose a novel hybrid framework that …
[HTML][HTML] A Hybrid Genetic Algorithm with Tabu Search Using a Layered Process for High-Order QAM in MIMO Detection
T Kim, G Kong - Mathematics, 2024 - mdpi.com
In this paper, we propose a hybrid genetic algorithm (HGA) that embeds the tabu search
mechanism into the genetic algorithm (GA) for multiple-input multiple-output (MIMO) …
mechanism into the genetic algorithm (GA) for multiple-input multiple-output (MIMO) …
Self-Adapted Resource Allocation in V2X Communication
The intelligent transportation system (ITS) along with vehicular communications are making
our daily life safer and easier eg, saving time, traffic control, safe driving, etc. Many …
our daily life safer and easier eg, saving time, traffic control, safe driving, etc. Many …