With expected widespread implementation of 5G networks and Internet Things (IoT), indoor localization is to become even further importance. Although Global Positioning System (GPS) ensures efficient outdoor localization, generally speaking, systems fail provide the same level efficiency. In this regard, there has been recent attention Angle Arrival (AoA) with application on Switch Antenna Array (SAA), as an method due its potential in determining location low estimation error. The AoA,...

Recent advancements in Internet of Things (IoTs) have brought about a surge interest indoor positioning for the purpose providing reliable, accurate, and energy-efficient navigation/localization systems. Ultra Wide Band (UWB) technology has been emerged as potential candidate to satisfy aforementioned requirements. Although UWB can enhance accuracy due use wide-frequency spectrum, there are key challenges ahead its efficient implementation. On one hand, achieving high precision relies on...

Bluetooth Low Energy (BLE) is one of the key technologies empowering Internet Things (IoT) for indoor positioning. In this regard, Angle Arrival (AoA) localization most reliable techniques because its low estimation error. BLE-based AoA localization, however, in infancy as only recently direction-finding feature introduced to BLE specification. Furthermore, AoA-based approaches are prone noise, multi-path, and path-loss effects. The paper proposes an efficient Convolutional Neural Network...

The paper is motivated by the urgent need, imposed COVID-19 pandemic, for trustworthy access to secure communication systems with highest achievable availability and minimum latency. In this regard, we focus on an ultra-dense wireless network consisting of Femto Access Points (FAPs) Unmanned Aerial Vehicles (UAVs), known as caching nodes, where there are more than one possible node handle user's request. To efficiently cope dynamic topology networks time-varying behavior ground users, our...

Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote learning/working and telemedicine has significantly increased. In this context, preserving high Quality Service (QoS) maintaining low-latency communication are paramount importance. cellular networks, incorporation unmanned aerial vehicles (UAVs) can result in enhanced connectivity outdoor users due to probability establishing Line Sight (LoS) links. The UAV's limited battery life its signal...

The cache replacement policy is a crucial phase in caching-based systems that deal with the process of selecting applicable contents. In this paper, we propose two novel algorithms based on dataset obtained from typical wireless femto network. first algorithm, called Weighted Least Frequently used an Adaptive Time Window (WLF-ATW), aim to make balance between network's traffic and recognition popular WLF-ATW algorithm takes frequency recency information files into account ascertain...

Mobile Edge Caching (MEC) is a revolutionary technology for the Sixth Generation (6G) of wireless networks with promise to significantly reduce users’ latency via offering storage capacities at edge network. The efficiency MEC network, however, critically depends on its ability dynamically predict/update caching nodes top-K popular contents. Conventional statistical schemes are not robust time-variant nature underlying pattern content requests, resulting in surge interest using Deep Neural...

Coded/uncoded content placement in Mobile Edge Caching (MEC) has evolved as an efficient solution to meet the significant growth of global mobile data traffic by boosting diversity storage caching nodes. To dynamic nature historical request pattern multimedia contents, main focus recent researches been shifted develop data-driven and real-time schemes. In this regard with assumption that users’ preferences remain unchanged over a short horizon, Top-퐾 popular contents are identified output...

Bluetooth Low Energy (BLE) is one of the key enabling technologies emerging Internet Things (IoT) concept. When it comes to BLE-based dynamic indoor tracking, however, due drastic fluctuations Received Signal Strength Indicator (RSSI), highly acceptable accuracies are not yet achieved. Although very recent introduction BLE v 5.1 promises prosperous future for following two issues in path: (i) Despite being age big data with huge emphasis on reproducibility research, there no unified dataset...

Recent developments and advancements in wireless networks have brought about new challenges including the backhaul bottleneck content download latency. The paper focuses on an enterprise network consisting of various candidate caching nodes to serve users' requests such as Femto Access Points (FAPs) Mobile Users (MUs), supported by Device-to-Device (D2D) communications. Due fact that user's mobility is one inherent features massive networks, where FAPs operate open access mode, small...

Internet of Things (IoT) has penetrated different aspects our modern life where smart sensors enabled with Bluetooth Low Energy (BLE) are deployed increasingly within surrounding indoor environments. BLE-based localization is, typically, performed based on Received Signal Strength Indicator (RSSI), which suffers from drawbacks due to its significant fluctuations. In this paper, we focus a multiplemodel estimation framework for analyzing and addressing effects orientation BLE-enabled device...

Angle of Arrival (AoA) approach with applications to Bluetooth Low Energy (BLE) has been recognized as an effective indoor localization method because its ability for position determination low estimation error. However, there are several issues including Carrier Frequency Offset (CFO), multipath effect, Inter-Symbol Interference (ISI), noise, and phase shifting faced by the AoA. To tackle these issues, we first highlight wireless signal model in BLE standard formulate transmitted signal,...

Recently, as a consequence of the coronavirus disease (COVID-19) pandemic, dependence on contact tracing (CT) models has significantly increased to prevent spread this highly contagious virus and be prepared for potential future ones. Since spreading probability novel in indoor environments is much higher than that outdoors, there an urgent unmet quest develop/design efficient, autonomous, trustworthy, secure CT solutions. Despite such urgency, field still its infancy. This article addresses...

Recently, as a consequence of the COVID-19 pandemic, dependence on Contact Tracing (CT) models has significantly increased to prevent spread this highly contagious virus and be prepared for potential future ones. Since spreading probability novel coronavirus in indoor environments is much higher than that outdoors, there an urgent unmet quest develop/design efficient, autonomous, trustworthy, secure CT solutions. Despite such urgency, field still its infancy. The paper addresses gap proposes...

Ultra-Wideband (UWB) is one of the key technolo-gies empowering Internet Thing (IoT) concept to per-form reliable, energy-efficient, and highly accurate monitoring, screening, localization in indoor environments. Performance UWB-based systems, however, can significantly degrade because Non Line Sight (NLoS) connections between a mobile user UWB beacons. To mitigate destructive effects NLoS connections, we target development Reinforcement Learning (RL) anchor selection framework that...

Smart grid is susceptance to a variety of cyber attacks, among which False Data Injection Attacks (FDIA) are shown be significantly disruptive nature. Complex, distributed, and interconnected aspects smart grids make detection stealthy FDIAs with high accuracy challenging. To address this issue, the paper proposes an innovative Adaptive Multi-Level Features Classification for Stealthy FDIA Detection (AMLFC-SFD) based on Alternating Current (AC) state estimation. More specifically, we focus...

Mobile Edge Caching (MEC) integrated with Deep Neural Networks (DNNs) is an innovative technology significant potential for the future generation of wireless networks, resulting in a considerable reduction users' latency. The MEC network's effectiveness, however, heavily relies on its capacity to predict and dynamically update storage caching nodes most popular contents. To be effective, DNN-based popularity prediction model needs have ability understand historical request patterns content,...

Mobile-edge caching (MEC) integrated with deep neural networks (DNNs) is an innovative technology significant potential for the future generation of wireless networks, resulting in a considerable reduction users' latency. The mobile-edge network's effectiveness, however, heavily relies on its capacity to predict and dynamically update storage nodes most popular contents. To be effective, DNN-based popularity prediction model needs have ability understand historical request patterns content,...

Ultra-Wideband (UWB) is one of the key technologies empowering Internet Thing (IoT) concept to perform reliable, energy-efficient, and highly accurate monitoring, screening, localization in indoor environments. Performance UWB-based systems, however, can significantly degrade because Non Line Sight (NLoS) connections between a mobile user UWB beacons. To mitigate destructive effects NLoS connections, we target development Reinforcement Learning (RL) anchor selection framework that...

Coded/uncoded content placement in Mobile Edge Caching (MEC) has evolved as an efficient solution to meet the significant growth of global mobile data traffic by boosting diversity storage caching nodes. To dynamic nature historical request pattern multimedia contents, main focus recent researches been shifted develop data-driven and real-time schemes. In this regard with assumption that users' preferences remain unchanged over a short horizon, Top-K popular contents are identified output...