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Network Flying Platforms (NFPs) such as unmanned aerial vehicles, unmanned balloons or drones flying at low/medium/high altitude can be employed to enhance network coverage and capacity by deploying a swarm of flying platforms that…
Unmanned aerial vehicles (UAVs) are capable of serving as flying base stations (BSs) for supporting data collection, artificial intelligence (AI) model training, and wireless communications. However, due to the privacy concerns of devices…
With the rapidly growing expansion in the use of UAVs, the ability to autonomously navigate in varying environments and weather conditions remains a highly desirable but as-of-yet unsolved challenge. In this work, we use Deep Reinforcement…
Networks are designed with functionality, security, performance, and cost in mind. Tools exist to check or optimize individual properties of a network. These properties may conflict, so it is not always possible to run these tools in series…
Edge AI systems often operate under stringent energy and volume constraints that demand extreme efficiency under limited battery capacity, with requirements worsening as intelligent capability demands advance. Prior literature suggests that…
The emerging paradigm of Non-Conventional Internet of Things (NC IoT), which is focused on the usefulness of information as opposed to the notion of high volume data collection and transmission, will be an important and dominant part of…
Unmanned aerial vehicles (UAVs) enhance coverage and provide flexible deployment in 5G and next-generation wireless networks. The performance of such wireless networks can be improved by developing new navigation and wireless adaptation…
This paper presents an innovative framework that boosts computing power by utilizing ubiquitous computing power distribution and enabling higher computing node accessibility via adaptive UAV positioning, establishing a UAV-enabled Computing…
Recent breakthroughs in Deep Neural Networks (DNNs) have fueled a tremendously growing demand for bringing DNN-powered intelligence into mobile platforms. While the potential of deploying DNNs on resource-constrained platforms has been…
In the ever-expanding landscape of the IoT, managing the intricate network of interconnected devices presents a fundamental challenge. This leads us to ask: "What if we invite the IoT devices to collaboratively participate in real-time…
In the future 6th generation networks, ultra-reliable and low-latency communications (URLLC) will lay the foundation for emerging mission-critical applications that have stringent requirements on end-to-end delay and reliability. Existing…
Modeling heterogeneity by extraction and exploitation of high-order information from heterogeneous information networks (HINs) has been attracting immense research attention in recent times. Such heterogeneous network embedding (HNE)…
Machine learning (ML) has been widely used for efficient resource allocation (RA) in wireless networks. Although superb performance is achieved on small and simple networks, most existing ML-based approaches are confronted with difficulties…
Underwater sensor networks (UWSNs) are of interest to gather data from underwater sensor nodes (SNs) and deliver information to a terrestrial access point (AP) in the uplink transmission, and transfer data from the AP to the SNs in the…
Near-space information networks (NSINs) composed of high-altitude platforms (HAPs) and high- and low-altitude unmanned aerial vehicles (UAVs) are a new regime for providing quick, robust, and cost-efficient sensing and communication…
This paper designs a post-disaster powered communication intelligent network (PDPCIN) to address communication disruptions caused by ground base station (GBS) failures within the post-disaster area. PDPCIN employs unmanned aerial vehicles…
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The effective management of SAGIN resources is a prerequisite for high-reliability communication. However, the storage capacity of space-air network segment…
Hybrid light fidelity (LiFi) and wireless fidelity (WiFi) networks (HLWNets) are an emerging indoor wireless communication paradigm, which combines the advantages of the capacious optical spectra of LiFi and ubiquitous coverage of WiFi.…
The fast and accurate prediction of unsteady flow becomes a serious challenge in fluid dynamics, due to the high-dimensional and nonlinear characteristics. A novel hybrid deep neural network (DNN) architecture was designed to capture the…
Synchronous Flooding (SF) protocols can enhance the wireless connectivity between Internet of Things (IoT) devices. However, existing SF solutions fail to introduce sufficient security measures due to strict time synchronisation…