Cognitive IoT based Health Monitoring Scheme using Non-Orthogonal Multiple Access

It has become very essential to address the limited spectrum capacity and their efficient utilization to support the increasing number of Internet of Things devices. When it comes to medical infrastructure, it becomes very imperative for medical devices to communicate with the base station. In such situations, communication over the wireless medium must provide optimized throughput (data rate) with effectual energy usage, which will ensure precise medical feedback by the responsible staff. Taking into account, it is necessary to operate wireless communication precisely at a higher frequency with more substantial bandwidth and low latency. Cognitive Radio (CR) is traditionally a viable choice, where it identifies and utilizes the vacant spectrum, thus maximizing the primary user's capacity and achieving spectral efficiency. To ensure such outcomes, the Non-Orthogonal Multiple Access (NOMA) techniques have proven to deliver an effective solution to the increasing number of devices with unimpaired performance, especially when the communication shifts towards a higher frequency band such as the mmWave band. In this chapter, IoT based CR network in uplink communication is proposed alongside employing NOMA techniques for optimal throughput, and energy efficiency for a medical infrastructure. Numerical results show that effectual throughput and energy efficiency for a High Reliable Communication (HRC) device and Moderate Reliable Communication (MRC) device improve over 83.13% and 73.95%, respectively and their corresponding energy efficacy values show vast improvement (83.11% and 73.96% respectively). Likewise, for interference case both the throughput and the energy efficiency improve approximately over 93% for all devices.

[1]  Himangi Pande,et al.  Adaptive energy efficient MAC protocol for increasing life of sensor nodes in Wireless Body Area Network , 2016, 2016 International Conference on Internet of Things and Applications (IOTA).

[2]  Masanori Hamamura,et al.  Two-slope path-loss design of energy harvesting in random cognitive radio networks , 2018, Comput. Networks.

[3]  Dong Yue,et al.  Adaptive TDMA-based MAC protocol in energy harvesting wireless body area network for mobile health , 2015, IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society.

[4]  Sungmee Park,et al.  Enhancing the quality of life through wearable technology , 2003, IEEE Engineering in Medicine and Biology Magazine.

[5]  Saifur Rahman Sabuj,et al.  Analysis of delay-sensitive performance in cognitive wireless sensor networks , 2019, Internet Technol. Lett..

[6]  Max J. Ammann,et al.  Impact of Hub Location on the Performance of Wireless Body Area Networks for Fitness Applications , 2015, IEEE Antennas and Wireless Propagation Letters.

[7]  Masanori Hamamura,et al.  Outage and energy-efficiency analysis of cognitive radio networks: A stochastic approach to transmit antenna selection , 2017, Pervasive Mob. Comput..

[8]  Jun Wang,et al.  An all dynamic MAC protocol for wireless body area network , 2015 .

[9]  Sang Kyu Park,et al.  Performance analysis of wireless body area network in indoor off-body communication , 2011, IEEE Transactions on Consumer Electronics.

[10]  D. Sridharan,et al.  A Review of Channel Access Techniques in Wireless Body Area Network , 2017, 2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM).

[11]  Xin Yang,et al.  Wireless Body Area Networks MAC Protocol For Energy Efficiency and Extending Lifetime , 2018, IEEE Sensors Letters.

[12]  Md. Obaidur Rahman,et al.  Multi-dimensional traffic adaptive energy-efficient MAC protocol for Wireless Body Area Networks , 2014, 2014 9th International Forum on Strategic Technology (IFOST).

[13]  Lin Chen,et al.  Multichannel Broadcast in Duty-Cycling WBANs via Channel Hopping , 2017, IEEE Internet of Things Journal.

[14]  Da-Ren Chen.  A QoS Bandwidth Allocation Method for Coexistence of Wireless Body Area Networks , 2017, 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP).

[15]  Abdul Fuad Abdul Rahman,et al.  Forensics readiness for Wireless Body Area Network (WBAN) system , 2014, 16th International Conference on Advanced Communication Technology.

[16]  Ahmed Mehaoua,et al.  Multi-channel broadcast in asymmetric duty cycling wireless body area networks , 2017, 2017 IEEE International Conference on Communications (ICC).

[17]  Hoi-Jun Yoo,et al.  Wireless body area network and its healthcare applications , 2013, 2013 Asia-Pacific Microwave Conference Proceedings (APMC).

[18]  Khalil Drira,et al.  A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare , 2017, IEEE Transactions on Emerging Topics in Computational Intelligence.

[19]  Ali Husein Alasiry,et al.  Mobile monitoring of muscular strain sensor based on Wireless Body Area Network , 2015, 2015 International Electronics Symposium (IES).

[20]  M. Shamim Hossain,et al.  Cloud-assisted Industrial Internet of Things (IIoT) - Enabled framework for health monitoring , 2016, Comput. Networks.

[21]  Hongnian Yu,et al.  TMP: Tele-Medicine Protocol for Slotted 802.15.4 With Duty-Cycle Optimization in Wireless Body Area Sensor Networks , 2017, IEEE Sensors Journal.

[22]  Ekram Hossain,et al.  Dynamic User Clustering and Power Allocation for Uplink and Downlink Non-Orthogonal Multiple Access (NOMA) Systems , 2016, IEEE Access.

[23]  Vera Stavroulaki,et al.  Cognitive Management for the Internet of Things: A Framework for Enabling Autonomous Applications , 2013, IEEE Vehicular Technology Magazine.

[24]  Driss Aboutajdine,et al.  Energy efficient of ARQ and FEC in wireless body area networks , 2015, 2015 Third World Conference on Complex Systems (WCCS).

[25]  Ehsan Soleimani-Nasab,et al.  Performance analysis of cooperative wireless body area networks over Gamma fading channels , 2016, 2016 8th International Symposium on Telecommunications (IST).

[26]  Mahta Moghaddam,et al.  Improving the Efficiency of Magnetic Induction-Based Wireless Body Area Network (WBAN) , 2018, 2018 IEEE International Microwave Biomedical Conference (IMBioC).

[27]  Abbas Jamalipour,et al.  Body Node Coordinator Placement Algorithms for Wireless Body Area Networks , 2015, IEEE Internet of Things Journal.

[28]  M. Shamim Hossain,et al.  Cognitive IoT-Cloud Integration for Smart Healthcare: Case Study for Epileptic Seizure Detection and Monitoring , 2018, Mob. Networks Appl..

[29]  Ahmed Mehaoua,et al.  Delay Analysis of IEEE 802.15.6 CSMA/CA Mechanism in Duty-Cycling WBANs , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[30]  P. Ponmuthuramalingam,et al.  A robust energy efficient and secure data dissemination protocol for wireless body area networks , 2016, 2016 IEEE International Conference on Advances in Computer Applications (ICACA).

[31]  Donald F. Towsley,et al.  Code red worm propagation modeling and analysis , 2002, CCS '02.

[32]  Swamy Laxminarayan,et al.  UNWIRED E-MED: the next generation of wireless and internet telemedicine systems , 2000, IEEE Transactions on Information Technology in Biomedicine.

[33]  P. Bonato,et al.  Wearable sensors/systems and their impact on biomedical engineering , 2003, IEEE Engineering in Medicine and Biology Magazine.

[34]  Yannick Le Moullec,et al.  Optimization of channel allocation in wireless body area networks by means of reinforcement learning , 2016, 2016 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob).

[35]  Emil Jovanov,et al.  Guest Editorial Introduction to the Special Section on M-Health: Beyond Seamless Mobility and Global Wireless Health-Care Connectivity , 2004, IEEE Transactions on Information Technology in Biomedicine.

[36]  William P. Marnane,et al.  Energy-Efficient Low Duty Cycle MAC Protocol for Wireless Body Area Networks , 2009, IEEE Transactions on Information Technology in Biomedicine.

[37]  Jari H. Iinatti,et al.  Energy efficiency evaluation of wake-up radio based MAC protocol for wireless body area networks , 2017, 2017 IEEE 17th International Conference on Ubiquitous Wireless Broadband (ICUWB).

[38]  Wang Zhijun,et al.  A game theoretic approach for inter-network interference mitigation in wireless body area networks , 2015, China Communications.

[39]  Fabio Di Franco,et al.  The effect of body shape and gender on wireless Body Area Network on-body channels , 2010, IEEE Middle East Conference on Antennas and Propagation (MECAP 2010).

[40]  M. Shamim Hossain,et al.  Emotion recognition using deep learning approach from audio-visual emotional big data , 2019, Inf. Fusion.

[41]  I. F. Akyildiz,et al.  Propagation Modeling and Analysis of Reconfigurable Intelligent Surfaces for Indoor and Outdoor Applications in 6G Wireless Systems , 2019, ArXiv.

[42]  Haifa Takruri-Rizk,et al.  Improving the energy efficiency for a WBSN based on a coordinate duty cycle and network coding , 2017, 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC).

[43]  Yan Liu,et al.  A harvesting-rate oriented self-adaptive algorithm in Energy-Harvesting Wireless Body Area Networks , 2015, 2015 IEEE 13th International Conference on Industrial Informatics (INDIN).

[44]  M. Shamim Hossain,et al.  Cognitive Smart Healthcare for Pathology Detection and Monitoring , 2019, IEEE Access.

[45]  Ahmed Mehaoua,et al.  Medium Access for Concurrent Traffic in Wireless Body Area Networks: Protocol Design and Analysis , 2017, IEEE Transactions on Vehicular Technology.