arXiv subjects

Nasir Saeed

Publications and source records attributed to Nasir Saeed.

At least 37 records · Page 2Linked to original sources

arXiv2023

Adaptive Control of IoT/M2M Devices in Smart Buildings using Heterogeneous Wireless Networks

With the rapid development of wireless communication technology, the Internet of Things (IoT) and Machine-to-Machine (M2M) are becoming essential for many applications. One of the most emblematic IoT/M2M applications is smart buildings. The current Building Automation Systems (BAS) are limited by many factors, including the lack of integration of IoT and M2M technologies, unfriendly user interfacing, and the lack of a convergent solution. Therefore, this paper proposes a better approach of using heterogeneous wireless networks consisting of Wireless Sensor Networks (WSNs) and Mobile Cellular Networks (MCNs) for IoT/M2M smart building systems. One of the most significant outcomes of this research is to provide accurate readings to the server, and very low latency, through which users can easily control and monitor remotely the proposed system that consists of several innovative services, namely smart parking, garden irrigation automation, intrusion alarm, smart door, fire and gas detection, smart lighting, smart medication reminder, and indoor air quality monitoring. All these services are designed and implemented to control and monitor from afar the building via our free mobile application named Raniso which is a local server that allows remote control of the building. This IoT/M2M smart building system is customizable to meet the needs of users, improving safety and quality of life while reducing energy consumption. Additionally, it helps prevent the loss of resources and human lives by detecting and managing risks.

cs.NI↗

arXiv2023

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs.

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arXiv2022

Maritime Communications: A Survey on Enabling Technologies, Opportunities, and Challenges

Water covers 71% of the Earth's surface, where the steady increase in oceanic activities has promoted the need for reliable maritime communication technologies. The existing maritime communication systems involve terrestrial, aerial, and satellite networks. This paper presents a holistic overview of the different forms of maritime communications and provides the latest advances in various marine technologies. The paper first introduces the different techniques used for maritime communications over the RF and optical bands. Then, we present the channel models for RF and optical bands, modulation and coding schemes, coverage and capacity, and radio resource management in maritime communications. After that, the paper presents some emerging use cases of maritime networks, such as the Internet of Ships (IoS) and the ship-to-underwater Internet of things (IoT). Finally, we highlight a few exciting open challenges and identify a set of future research directions for maritime communication, including bringing broadband connectivity to the deep sea, using THz and visible light signals for on-board applications, and data-driven modeling for radio and optical marine propagation.

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arXiv2022

Towards Sustainable Internet of Underwater Things: UAV-aided Energy Efficient Wake-up Solutions

With the advancements in underwater wireless communications, internet of underwater things (IoUT) realization is inevitable to enable many practical applications, such as exploring ocean resources, ocean monitoring, underwater navigation, and surveillance. The IoUT network comprises battery-operated sensor nodes, and replacing or charging such batteries is challenging due to the harsh ocean environment. Hence, an energy-efficient IoUT network development becomes vital to improve the network lifetime. Therefore, this paper proposes unmanned aerial vehicle (UAV)-aided energy-efficient wake-up designs to activate the underwater IoT nodes on-demand and reduce their energy consumption. Specifically, the UAV communicates with water surface nodes, i.e., buoys, to send wake-up signals to activate the IoUT sensor nodes from sleep mode. We present three different technologies to enable underwater wake-up: acoustic, optical, and magnetic induction-based solutions. Moreover, we verify the significance of each technology through simulations using the performance metrics of received power and lifetime. Also, the results of the proposed on-demand wake-up approach are compared to conventional duty cycling, showing the superior performance of the proposed schemes. Finally, we present some exciting research challenges and future directions.

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arXiv2022

Post-Disaster Communications: Enabling Technologies, Architectures, and Open Challenges

The number of disasters has increased over the past decade where these calamities significantly affect the functionality of communication networks. In the context of 6G, airborne and spaceborne networks offer hope in disaster recovery to serve the underserved and to be resilient in calamities. Therefore, this paper surveys the state-of-the-art literature on post-disaster wireless communication networks and provides insights for the future establishment of such networks. In particular, we first give an overview of the works investigating the general procedures and strategies for counteracting any large-scale disasters. Then, we present the possible technological solutions for post-disaster communications, such as the recovery of the terrestrial infrastructure, installing aerial networks, and using spaceborne networks. Afterward, we shed light on the technological aspects of post-disaster networks, primarily the physical and networking issues. We present the literature on channel modeling, coverage and capacity, radio resource management, localization, and energy efficiency in the physical layer and discuss the integrated space-air-ground architectures, routing, delay-tolerant/software-defined networks, and edge computing in the networking layer. This paper also presents interesting simulation results which can provide practical guidelines about the deployment of ad hoc network architectures in emergency scenarios. Finally, we present several promising research directions, namely backhauling, placement optimization of aerial base stations, and the mobility-related aspects that come into play when deploying aerial networks, such as planning their trajectories and the consequent handovers.

cs.NI↗

arXiv2022

UAVs-Enabled Maritime Communications: Opportunities and Challenges

The next generation of wireless communication systems will integrate terrestrial and non-terrestrial networks targeting to cover the undercovered regions, especially connecting the marine activities. Unmanned aerial vehicles (UAVs) based connectivity solutions offer significant advances to support the conventional terrestrial networks. However, the use of UAVs for maritime communication is still an unexplored area of research. Therefore, this paper highlights different aspects of UAV-based maritime communication, including the basic architecture, various channel characteristics, and use cases. The article, afterward, discusses several open research problems such as mobility management, trajectory optimization, interference management, and beamforming.

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arXiv2022

Edge Computing in IoT: A 6G Perspective

Edge computing is one of the key driving forces to enable Beyond 5G (B5G) and 6G networks. Due to the unprecedented increase in traffic volumes and computation demands of future networks, multi-access (or mobile) edge computing (MEC) is considered as a promising solution to provide cloud-computing capabilities within the radio access network (RAN) closer to the end users. There has been a significant amount of research on MEC and its potential applications; however, very little has been said about the key factors of MEC deployment to meet the diverse demands of future applications. In this article, we present key considerations for edge deployments in B5G/6G networks including edge architecture, server location and capacity, user density, security etc. We further provide state-of-the-art edge-centric services in future B5G/6G networks. The paper also present experimental evaluation of edge-based services deployment including video transcoding and deep learning inference. Lastly, we present some interesting insights and open research problems in edge computing for 6G networks.

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arXiv2022

Interference Aware Cooperative Routing for Edge Computing-enabled 5G Networks

Recently, there has been growing research on developing interference-aware routing (IAR) protocols for supporting multiple concurrent transmission in next-generation wireless communication systems. The existing IAR protocols do not consider node cooperation while establishing the routes because motivating the nodes to cooperate and modeling that cooperation is not a trivial task. In addition, the information about the cooperative behavior of a node is not directly visible to neighboring nodes. Therefore, in this paper, we develop a new routing method in which the nodes' cooperation information is utilized to improve the performance of edge computing-enabled 5G networks. The proposed metric is a function of created and received interference in the network. The received interference term ensures that the Signal to Interference plus Noise Ratio (SINR) at the route remains above the threshold value, while the created interference term ensures that those nodes are selected to forward the packet that creates low interference for other nodes. The results show that the proposed solution improves ad hoc networks' performance compared to conventional routing protocols in terms of high network throughput and low outage probability.

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arXiv2021

Neural Networks for Infectious Diseases Detection: Prospects and Challenges

Artificial neural network (ANN) ability to learn, correct errors, and transform a large amount of raw data into useful medical decisions for treatment and care have increased its popularity for enhanced patient safety and quality of care. Therefore, this paper reviews the critical role of ANNs in providing valuable insights for patients' healthcare decisions and efficient disease diagnosis. We thoroughly review different types of ANNs presented in the existing literature that advanced ANNs adaptation for complex applications. Moreover, we also investigate ANN's advances for various disease diagnoses and treatments such as viral, skin, cancer, and COVID-19. Furthermore, we propose a novel deep Convolutional Neural Network (CNN) model called ConXNet for improving the detection accuracy of COVID-19 disease. ConXNet is trained and tested using different datasets, and it achieves more than 97% detection accuracy and precision, which is significantly better than existing models. Finally, we highlight future research directions and challenges such as complexity of the algorithms, insufficient available data, privacy and security, and integration of biosensing with ANNs. These research directions require considerable attention for improving the scope of ANNs for medical diagnostic and treatment applications.

cs.LG↗

arXiv2021

Towards 6G Internet of Things: Recent Advances, Use Cases, and Open Challenges

Smart services based on the Internet of Everything (IoE) are gaining considerable popularity due to the ever-increasing demands of wireless networks. This demands the appraisal of the wireless networks with enhanced properties as next-generation communication systems. Although 5G networks show great potential to support numerous IoE based services, it is not adequate to meet the complete requirements of the new smart applications. Therefore, there is an increased demand for envisioning the 6G wireless communication systems to overcome the major limitations in the existing 5G networks. Moreover, incorporating artificial intelligence in 6G will provide solutions for very complex problems relevant to network optimization. Furthermore, to add further value to the future 6G networks, researchers are investigating new technologies, such as THz and quantum communications. The requirements of future 6G wireless communications demand to support massive data-driven applications and the increasing number of users. This paper presents recent advances in the 6G wireless networks, including the evolution from 1G to 5G communications, the research trends for 6G, enabling technologies, and state-of-the-art 6G projects.

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arXiv2021

Bayesian Multidimensional Scaling for Location Awareness in Hybrid-Internet of Underwater Things

Localization of sensor nodes in the Internet of Underwater Things (IoUT) is of considerable significance due to its various applications, such as navigation, data tagging, and detection of underwater objects. Therefore, in this paper, we propose a hybrid Bayesian multidimensional scaling (BMDS) based localization technique that can work on a fully hybrid IoUT network where the nodes can communicate using either optical, magnetic induction, and acoustic technologies. These technologies are already used for communication in the underwater environment; however, lacking localization solutions. Optical and magnetic induction communication achieves higher data rates for short communication. On the contrary, acoustic waves provide a low data rate for long-range underwater communication. The proposed method collectively uses optical, magnetic induction, and acoustic communication-based ranging to estimate the underwater sensor nodes' final locations. Moreover, we also analyze the proposed scheme by deriving the hybrid Cramer Rao lower bound (HCRLB). Simulation results provide a complete comparative analysis of the proposed method with the literature.

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arXiv2020

Point-to-Point Communication in Integrated Satellite-Aerial Networks: State-of-the-art and Future Challenges

This paper overviews point-to-point (P2P) links for integrated satellite-aerial networks, which are envisioned to be among the key enablers of the sixth-generation (6G) of wireless networks vision. The paper first outlines the unique characteristics of such integrated large-scale complex networks, often denoted by spatial networks, and focuses on two particular space-air infrastructures, namely, satellites networks and high-altitude platforms (HAPs). The paper then classifies the connecting P2P communications links as satellite-to-satellite links at the same layer (SSLL), satellite-to-satellite links at different layers (SSLD), and HAP-to-HAP links (HHL). The paper overviews each layer of such spatial networks separately, and highlights the possible natures of the connecting links (i.e., radio-frequency or free-space optics) with a dedicated overview to the existing link-budget results. The paper, afterwards, presents the prospective merit of realizing such an integrated satellite-HAP network towards providing broadband services in under-served and remote areas. Finally, the paper sheds light on several future research directions in the context of spatial networks, namely large-scale network optimization, intelligent offloading, smart platforms, energy efficiency, multiple access schemes, and distributed spatial networks.

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arXiv2020

Intelligent Surfaces for 6G Wireless Networks: A Survey of Optimization and Performance Analysis Techniques

This paper surveys the optimization frameworks and performance analysis methods for large intelligent surfaces (LIS), which have been emerging as strong candidates to support the sixth-generation wireless physical platforms (6G). Due to their ability to adjust the behavior of interacting electromagnetic (EM) waves through intelligent manipulations of the reflections phase shifts, LIS have shown promising merits at improving the spectral efficiency of wireless networks. In this context, researchers have been recently exploring LIS technology in depth as a means to achieve programmable, virtualized, and distributed wireless network infrastructures. From a system level perspective, LIS have also been proven to be a low-cost, green, sustainable, and energy-efficient solution for 6G systems. This paper provides a unique blend that surveys the principles of operation of LIS, together with their optimization and performance analysis frameworks. The paper first introduces the LIS technology and its physical working principle. Then, it presents various optimization frameworks that aim to optimize specific objectives, namely, maximizing energy efficiency, sum-rate, secrecy-rate, and coverage. The paper afterwards discusses various relevant performance analysis works including capacity analysis, the impact of hardware impairments on capacity, uplink/downlink data rate analysis, and outage probability. The paper further presents the impact of adopting the LIS technology for positioning applications. Finally, we identify numerous exciting open challenges for LIS-aided 6G wireless networks, including resource allocation problems, hybrid radio frequency/visible light communication (RF-VLC) systems, health considerations, and localization.

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arXiv2020

Deep Learning in Industrial Internet of Things: Potentials, Challenges, and Emerging Applications

The recent advancements in the Internet of Things (IoT) are giving rise to the proliferation of interconnected devices, enabling various smart applications. These enormous number of IoT devices generates a large capacity of data that further require intelligent data analysis and processing methods, such as Deep Learning (DL). Notably, the DL algorithms, when applied in the Industrial Internet of Things (IIoT), can enable various applications such as smart assembling, smart manufacturing, efficient networking, and accident detection-and-prevention. Therefore, motivated by these numerous applications; in this paper, we present the key potentials of DL in IIoT. First, we review various DL techniques, including convolutional neural networks, auto-encoders, and recurrent neural networks and there use in different industries. Then, we outline numerous use cases of DL for IIoT systems, including smart manufacturing, smart metering, smart agriculture, etc. Moreover, we categorize several research challenges regarding the effective design and appropriate implementation of DL-IIoT. Finally, we present several future research directions to inspire and motivate further research in this area.

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arXiv2020

When Wireless Communication Faces COVID-19: Combating the Pandemic and Saving the Economy

The year 2020 is experiencing a global health and economic crisis due to the COVID-19 pandemic. Countries across the world are using digital technologies to fight this global crisis. These digital technologies, in one way or another, strongly rely on the availability of wireless communication technologies. In this paper, we present the role of wireless communications in the COVID-19 pandemic from different perspectives. First, we show how these technologies are helping to combat this pandemic, including monitoring of the virus spread, enabling healthcare automation, and allowing virtual education and conferencing. Also, we show the importance of digital inclusiveness in the pandemic and possible solutions to connect the unconnected. Next, we discuss the challenges faced by wireless technologies, including privacy, security, and misinformation. Then, we present the importance of wireless communication technologies in the survival of the global economy, such as automation of industries and supply chain, e-commerce, and supporting occupations that are at risk. Finally, we reveal that how the technologies developed during the pandemic can be helpful in the post-pandemic era.

cs.CY↗

arXiv2020

Climate Monitoring using Internet of X-Things

Global climate change is significantly affecting the life on planet Earth. Predicting timely changes in the climate is a big challenge and requires great attention from the scientific community. Research now suggests that using the internet of X-things (X-IoT) helps in monitoring global climate change.

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arXiv2020

Next Generation Terahertz Communications: A Rendezvous of Sensing, Imaging, and Localization

Terahertz (THz)-band communications are celebrated as a key enabling technology for next-generation wireless systems that promises to integrate a wide range of data-demanding and delay-sensitive applications. Following recent advancements in optical, electronic, and plasmonic transceiver design, integrated, adaptive, and efficient THz systems are no longer far-fetched. In this paper, we present a progressive vision of how the traditional "THz gap" will transform into a "THz rush" over the next few years. We posit that the breakthrough that the THz band will introduce will not be solely driven by achievable high data rates, but more profoundly by the interaction between THz sensing, imaging, and localization applications. We first detail the peculiarities of each of these applications at the THz band. Then, we illustrate how their coalescence results in enhanced environment-aware system performance in beyond-5G use cases. We further discuss the implementation aspects of this merging of applications in the context of shared and dedicated resource allocation, highlighting the role of machine learning.

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arXiv2020

CubeSat Communications: Recent Advances and Future Challenges

Given the increasing number of space-related applications, research in the emerging space industry is becoming more and more attractive. One compelling area of current space research is the design of miniaturized satellites, known as CubeSats, which are enticing because of their numerous applications and low design-and-deployment cost. The new paradigm of connected space through CubeSats makes possible a wide range of applications, such as Earth remote sensing, space exploration, and rural connectivity. CubeSats further provide a complementary connectivity solution to the pervasive Internet of Things (IoT) networks, leading to a globally connected cyber-physical system. This paper presents a holistic overview of various aspects of CubeSat missions and provides a thorough review of the topic from both academic and industrial perspectives. We further present recent advances in the area of CubeSat communications, with an emphasis on constellation-and-coverage issues, channel modeling, modulation and coding, and networking. Finally, we identify several future research directions for CubeSat communications, including Internet of space things, low-power long-range networks, and machine learning for CubeSat resource allocation.

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