Publications with Fulltext

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

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    PublicationOpen Access
    A queueing-theoretical delay analysis for intra-body nervous nanonetwork
    (Elsevier, 2015) Department of Electrical and Electronics Engineering; Abbasi, Naveed Ahmed; Akan, Özgür Barış; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering
    Nanonetworks is an emerging field of study where nanomachines communicate to work beyond their individual limited processing capabilities and perform complicated tasks. The human body is an example of a very large nanoscale communication network, where individual constituents communicate by means of molecular nanonetworks. Amongst the various intra-body networks, the nervous system forms the largest and the most complex network. In this paper, we introduce a queueing theory based delay analysis model for neuro-spike communication between two neurons. Using standard queueing model blocks such as servers, queues and fork-join networks, impulse reception and processing through the nervous system is modeled as arrival and service processes in queues. Simulations show that the response time characteristics of the model are comparable to those of the biological neurons.
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    PublicationOpen Access
    An information theoretical analysis of human insulin-glucose system toward the internet of bio-nano things
    (Institute of Electrical and Electronics Engineers (IEEE), 2017) Department of Electrical and Electronics Engineering; Abbasi, Naveed Ahmed; Akan, Özgür Barış; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering
    Molecular communication is an important tool to understand biological communications with many promising applications in Internet of Bio-Nano Things (IoBNT). The insulin-glucose system is of key significance among the major intra-body nanonetworks, since it fulfills metabolic requirements of the body. The study of biological networks from information and communication theoretical (ICT) perspective is necessary for their introduction in the IoBNT framework. Therefore, the objective of this paper is to provide and analyze for the first time in the literature, a simple molecular communication model of the human insulin-glucose system from ICT perspective. The data rate, channel capacity, and the group propagation delay are analyzed for a two-cell network between a pancreatic beta cell and a muscle cell that are connected through a capillary. The results point out a correlation between an increase in insulin resistance and a decrease in the data rate and channel capacity, an increase in the insulin transmission rate, and an increase in the propagation delay. We also propose applications for the introduction of the system in the IoBNT framework. Multi-cell insulin glucose system models may be based on this simple model to help in the investigation, diagnosis, and treatment of insulin resistance by means of novel IoBNT applications.
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    PublicationOpen Access
    Controlled information transfer through an in vivo nervous system
    (Nature Publishing Group (NPG), 2018) Department of Electrical and Electronics Engineering; Abbasi, Naveed Ahmed; Lafçı, Dilan; Akan, Özgür Barış; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering
    The nervous system holds a central position among the major in-body networks. It comprises of cells known as neurons that are responsible to carry messages between different parts of the body and make decisions based on those messages. In this work, further to the extensive theoretical studies, we demonstrate the first controlled information transfer through an in vivo nervous system by modulating digital data from macro-scale devices onto the nervous system of common earthworms and conducting successful transmissions. The results and analysis of our experiments provide a method to model networks of neurons, calculate the channel propagation delay, create their simulation models, indicate optimum parameters such as frequency, amplitude and modulation schemes for such networks, and identify average nerve spikes per input pulse as the nervous information coding scheme. Future studies on neuron characterization and artificial neurons may benefit from the results of our work.
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    PublicationOpen Access
    Fundamentals of molecular information and communication science
    (Institute of Electrical and Electronics Engineers (IEEE), 2017) Department of Electrical and Electronics Engineering; Ramezani, Hamideh; Khan, Tooba; Abbasi, Naveed Ahmed; Kuşcu, Murat; Akan, Özgür Barış; PhD Student; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering
    Molecular communication (MC) is the most promising communication paradigm for nanonetwork realization since it is a natural phenomenon observed among living entities with nanoscale components. Since MC significantly differs from classical communication systems, it mandates re-investigation of information and communication theoretical fundamentals. The closest examples of MC architectures are present inside our own body. Therefore, in this paper, we investigate the existing literature on intrabody nanonetworks and different MC paradigms to establish and introduce the fundamentals of molecular information and communication science. We highlight future research directions and open issues that need to be addressed for revealing the fundamental limits of this science. Although the scope of this development encompasses wide range of applications, we particularly emphasize its significance for life sciences by introducing potential diagnosis and treatment techniques for diseases caused by dysfunction of intrabody nanonetworks.
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    PublicationOpen Access
    Information and communication theoretical understanding and treatment of spinal cord injuries: state-of-the-art and research challenges
    (Institute of Electrical and Electronics Engineers (IEEE), 2021) Bilgin, Bilgesu Arif; Department of Electrical and Electronics Engineering; Akan, Özgür Barış; Civaş, Meltem; Çetinkaya, Oktay; Ramezani, Hamideh; Abbasi, Naveed Ahmed; Faculty Member; Researcher; PhD Student; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering
    Among the various key networks in the human body, the nervous system occupies central importance. The debilitating effects of spinal cord injuries (SCI) impact a significant number of people throughout the world, and to date, there is no satisfactory method to treat them. In this paper, we review the major treatment techniques for SCI that include promising solutions based on information and communication technology (ICT) and identify the key characteristics of such systems. We then introduce two novel ICT-based treatment approaches for SCI. The first proposal is based on neural interface systems (NIS) with enhanced feedback, where the external machines are interfaced with the brain and the spinal cord such that the brain signals are directly routed to the limbs for movement. The second proposal relates to the design of self-organizing artificial neurons (ANs) that can be used to replace the injured or dead biological neurons. Apart from SCI treatment, the proposed methods may also be utilized as enabling technologies for neural interface applications by acting as bio-cyber interfaces between the nervous system and machines. Furthermore, under the framework of Internet of BioNano Things (IoBNT), experience gained from SCI treatment techniques can be transferred to nano communication research.
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    PublicationOpen Access
    Statistical characterization and analysis of low-THz communication channel for 5G Internet of Things
    (Elsevier, 2019) Department of Electrical and Electronics Engineering; Akan, Özgür Barış; Abbasi, Naveed Ahmed; Khalid, Nabil; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 6647; N/A; N/A
    This paper presents measurements and statistical characterization to compare three potential bands of the low-THz channel, namely, the 300 to 319 GHz, 340 to 359 GHz and 380 to 399 GHz bands. From the large set of measurements performed in line-of-sight (LoS) and non-LoS (NLoS) environments, parameters for path loss model with shadowing are evaluated. Our results show that the path loss exponents for the band around 310 GHz, 350 GHz, and 390 GHz is 2.07, 1.90 and 1.96, respectively. The impacts of different materials acting as surfaces in LoS channels and reflectors in NLoS environments are also examined. Additionally, the statistical analysis due to temporal, spatial and multipath propagation is performed to determine the best fit distributions. Finally, we look at some networking scenarios in THz Band communication to derive the expressions for the number of connections a user can make based on antenna characteristics, data rate requirements and antenna mobility as well as network density. Our results suggest fundamental parameters that can be used in future THz Band analysis with applications in both macro and micro scale Internet of Things (IoT).