Human Bond Communications: Architectures, Challenges, and Possibilities

Iftikhar, T.; Khattak, Hasan Ali; Ameer, Zoobia; Shah, Munam Ali; Qureshi, Faisal Fayyaz; Shakir, Muhammad Zeeshan

doi:10.1109/mcom.2018.1800531

Cited by 12 publications

(8 citation statements)

References 15 publications

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“…In the considered network, sensing data can be transmitted to the SU-HP and SU-MP devices via two types of links: (1) The sensing data are cached by CUAV (CUAV-SU-HP/SU-MP) and (2) The sensing data are cached by MBS and CUAV (MBS-CUAV-SU-HP/SU-MP). In the present study, the throughput is calculated according to MBS-CUAV-SU-HP/SU-MP 3 .…”

Section: ) Downlink Phasementioning

confidence: 99%

“…that will prove to be a massive step toward achieving precise health applications, sensing, surgical operations, identifying emotions, collection of biological data for diagnosis purposes, remote contact with the human body, and neural communication [1,2,3].…”

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confidence: 99%

“…The main motivation for developing HBC-compatible technology is to mitigate most of the complexities in healthcare diagnosis. For example, to efficiently monitor the impulsive nature and attention variation of a patient, an HBC-compatible system that can diagnose, process, and deliver all five-sense data for all-inclusive collaboration between the patient and the medical practitioner is an effective step toward modern diagnosis and treatment [2]. Similarly, with some specific modifications, this framework can also support patients with partial paralysis, blindness, disability, old age, and mental illness.…”

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confidence: 99%

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Cognitive Unmanned Aerial Vehicle-Aided Human Bond Communication System: Modeling and Performance Analysis

et al. 2022

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Effective networking over wireless media has become extremely essential today as communication between massive Internet of things (IoT) devices is on an increase, thereby leading to a limited spectrum resource for utilisation. Specifically, for healthcare infrastructure in a remote or critical situation, providing uninterrupted communication between the macro base station and IoT devices or user nodes is imperative. However, owing to their limited spectral capacity, unmanned aerial vehicles (UAVs)-based networks can provide an efficient solution and utilise both licensed and unlicensed bands for communication among users or devices. In this paper, our focus is on cache-enabled cognitive networking for secondary users (SUs) that accredits precise communication delivery for critical healthcare systems that are performed by the cognitive UAV (CUAV). In addition, we develop a caching strategy wherein a CUAV is capable of caching relevant information from high-power (HP) and moderate-power (MP) devices in its local and cloud storage by applying a non-orthogonal multiple-access method. In the downlink scenario, the CUAV proactively transmits the requested HP and MP information to the designated SUs considering this entire model over two states, namely effectual state and interference state, which we can realise by any presence or absence of interference. To maximise this system's energy efficiency, we formulate an optimisation problem to minimise the transmission power and satisfy the target performance in terms of throughput for SUs. We solve the optimisation issue using the Lagrangian approach and the Karush-Kuhn-Tucker conditions. In all simulations, the energy efficiency during the effectual state renders an average performance of approximately 400% better than that of the interference state.INDEX TERMS Caching, cognitive radio network, energy efficiency, human bond communication, nonorthogonal multiple access, optimisation, throughput, unmanned aerial vehicle. I. INTRODUCTION A. BACKGROUND AND MOTIVATIONSome of the key objectives of the potential universal communication environment are to enhance the standard of living by increasing convenience and enriching the experiences and circumstances of our daily activities. To realise this, several major technological advancements have centred on improving human interactions. The conventional approach to communication technology has always been to improve the information or signal so that the communication entities can manage them with the utmost efficiency. The limitation is that there is no transfer of information by such communication systems directly to the users' awareness that will allow for a more integrative sharing of sensory data. In relation to this, several articles have introduced the concept of human bond communication (HBC) to understand this dynamic growth

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Cognitive Unmanned Aerial Vehicle-Aided Human Bond Communication System: Modeling and Performance Analysis

et al. 2022

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“…In the biomedical field, nano-sensors are used in drug delivery and medical treatment applications [3], [4]. Likewise, nanosensors are used in health tracking systems and human body communication, promoting medical body area networks that allow medical personnel to have remote access and monitoring to the patient's body [5]. Through wearable health trackers, doctors can monitor real-time measurements of the human body like heartbeats rate, blood pressure and breath tests to get early detection of sickness [4], [6].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Models for Traffic Classification in Electromagnetic Nano-Networks

Galal

Hesselbach

2022

IEEE Access

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The number of nano-sensors connected to wireless electromagnetic nano-network generates different traffic volumes that have increased dramatically, enabling various applications of the Internet of nano-things. Nano-network traffic classification is more challenging nowadays to analyze different types of flows and study the overall performance of a nano-network that connects to the Internet through micro/nanogateways. There are traditional techniques to classify traffic, such as port-based technique and load-based technique, however the most promising technique used recently is machine learning. As machine learning models have a great impact on traffic classification and network performance evaluation in general, it is difficult to declare which is the best or the most suitable model to address the analysis of large volumes of traffic collected in operational nano-networks. In this paper, we study the classification problem of nano-network traffic captured by micro/nano-gateway, and then five supervised machine learning algorithms are used to analyze and classify the nano-network traffic from traditional traffic. Experimental analysis of the proposed models is evaluated and compared to show the most adequate classifier for nano-network traffic that gives very good accuracy and performance score to other classifiers.

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“…As the 5G wireless communication and Internet of Things step into their booming period, networks are going to contain a huge amount of devices [6], [7]. Therefore, concepts like Body Area Network [8] and human bond communication [9] are thriving. Meanwhile, the aging problem, biomedical development, recreational needs, and endless pursuit of living quality all boost the demand for wearable wireless devices [10], [11].…”

Section: Introductionmentioning

confidence: 99%

Wristwatch-Style Wearable Dielectric Resonator Antennas for Applications on Limps

Pan

Wang

et al. 2020

IEEE Access

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A wristwatch-style wearable dielectric resonator antenna (DRA) is proposed for the 2.45-GHz ISM band and sub-6 GHz 5G NR bands around 2.5 GHz, such as the commercial band for China Mobile Communications Corporation. The antenna is designed for applications on forearms and ankles. Practical concerns, including the aligning method, platform size, specific absorption rate, and user effects are investigated. Coplanar feeding structure is applied for alignment and isolation. Analysis of the watchband-like substrate is highlighted to avoid performance degradation. Given that platform configurations are not discretionary in actual devices, parasitic loading is introduced to attain desirable substrate effects and suppress unwanted ones. The user-device interplay is studied in light of actual application scenarios. The specific absorption rate is calculated through multilayer biological tissue models. Meanwhile, radiation variation caused by users is estimated based on human phantom models and measurements. INDEX TERMS Dielectric resonator antennas (DRAs), specific absorption rate (SAR), substrate effects, user effects, wearable antennas.

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Human Bond Communications: Architectures, Challenges, and Possibilities

Cited by 12 publications

References 15 publications

Cognitive Unmanned Aerial Vehicle-Aided Human Bond Communication System: Modeling and Performance Analysis

Cognitive Unmanned Aerial Vehicle-Aided Human Bond Communication System: Modeling and Performance Analysis

Machine Learning Models for Traffic Classification in Electromagnetic Nano-Networks

Wristwatch-Style Wearable Dielectric Resonator Antennas for Applications on Limps

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