相关论文: Cooperative Deep Reinforcement Learning for Multip…

Ultra-dense IoT networks require an effective non-orthogonal multiple access (NOMA) scheme, yet they experience intense interference because of fixed code assignment. We suggest a reinforcement learning (RL) model of dynamic Gold code…

Time-critical data aggregation in Internet of Things (IoT) networks demands efficient, collision-free scheduling to minimize latency for applications like smart cities and industrial automation. Traditional heuristic methods, with two-phase…

This paper studies the problem of minimizing the age of information (AoI) in cellular vehicle-to-everything communications. To provide minimal AoI and high reliability for vehicles' safety information, NOMA is exploited. We reformulate a…

In recent years, long-term evolution (LTE) and 5G NR (5th Generation New Radio) technologies have showed great potential to utilize Machine Learning (ML) algorithms in optimizing their operations, both thanks to the availability of…

Bistatic backscatter communication facilitates ubiquitous, massive connectivity of passive tags for future Internet-of-Things (IoT) networks. The tags communicate with readers by reflecting carrier emitter (CE) signals. This work addresses…

This paper investigates a cognitive unmanned aerial vehicle (UAV) enabled Internet of Things (IoT) network, where secondary/cognitive IoT devices upload their data to the UAV hub following a non-orthogonal multiple access (NOMA) protocol in…

An increasing number of emerging applications, e.g., internet of things, vehicular communications, augmented reality, and the growing complexity due to the interoperability requirements of these systems, lead to the need to change the tools…

In the Internet-of-Things (IoT), massive sensitive and confidential information is transmitted wirelessly, making security a serious concern. This is particularly true when technologies, such as non-orthogonal multiple access (NOMA), are…

In this work, we present an energy-efficient distributed learning framework using low-resolution ADCs and coarsely quantized signals for Internet of Things (IoT) networks. In particular, we develop a distributed quantization-aware…

Cell-edge users (CEUs) in cellular networks typically suffer from poor channel conditions due to long distances from serving base stations and physical obstructions, resulting in much lower data rates compared to cell-center users (CCUs).…

The quantum internet holds transformative potential for global communication by harnessing the principles of quantum information processing. Despite significant advancements in quantum communication technologies, the efficient distribution…

A wireless network operator typically divides the radio spectrum it possesses into a number of subbands. In a cellular network those subbands are then reused in many cells. To mitigate co-channel interference, a joint spectrum and power…

Internet-of-Things (IoT) technology is envisioned to enable a variety of real-time applications by interconnecting billions of sensors/devices deployed to observe some random physical processes. These IoT devices rely on low-power wide-area…

There have been significant issues given the IoT, with heterogeneity of billions of devices and with a large amount of data. This paper proposed an innovative design of the Internet of Things (IoT) Environment Intrusion Detection System (or…

Very few available individual bandwidth reservation schemes provide efficient and cost-effective bandwidth reservation that is required for safety-critical and time-sensitive vehicular networked applications. These schemes allow vehicles to…

As a main use case of 5G and Beyond wireless network, the ever-increasing machine type communications (MTC) devices pose critical challenges over MTC network in recent years. It is imperative to support massive MTC devices with limited…

This project addresses the challenge of automated stock trading, where traditional methods and direct reinforcement learning (RL) struggle with market noise, complexity, and generalization. Our proposed solution is an integrated deep…

Recent advancements in edge computing have significantly enhanced the AI capabilities of Internet of Things (IoT) devices. However, these advancements introduce new challenges in knowledge exchange and resource management, particularly…

One effective way to optimize the offloading process is by minimizing the transmission time. This is particularly true in a Vehicular Adhoc Network (VANET) where vehicles frequently download and upload High-definition (HD) map data which…

Solving optimization tasks using variational quantum algorithms has emerged as a crucial application of the current noisy intermediate-scale quantum devices. However, these algorithms face several difficulties like finding suitable ansatz…