A Resilient 2-D Waveguide Communication Fabric for Hybrid Wired-Wireless NoC Design

Hybrid wired-wireless Network-on-Chip (WiNoC) has emerged as an alternative solution to the poor scalability and performance issues of conventional wireline NoC design for future System-on-Chip (SoC). Existing feasible wireless solution for WiNoCs in the form of millimeter wave (mm-Wave) relies on free space signal radiation which has high power dissipation with high degradation rate in the signal strength per transmission distance. Moreover, over the lossy wireless medium, combining wireless and wireline channels drastically reduces the total reliability of the communication fabric. Surface wave has been proposed as an alternative wireless technology for low power on-chip communication. With the right design considerations, the reliability and performance benefits of the surface wave channel could be extended. In this paper, we propose a surface wave communication fabric for emerging WiNoCs that is able to match the reliability of traditional wireline NoCs. First, we propose a realistic channel model which demonstrates that existing mm-Wave WiNoCs suffers from not only free-space spreading loss (FSSL) but also molecular absorption attenuation (MAA), especially at high frequency band, which reduces the reliability of the system. Consequently, we employ a carefully designed transducer and commercially available thin metal conductor coated with a low cost dielectric material to generate surface wave signals with improved transmission gain. Our experimental results demonstrate that the proposed communication fabric can achieve a 5dB operational bandwidth of about 60GHz around the center frequency (60GHz). By improving the transmission reliability of wireless layer, the proposed communication fabric can improve maximum sustainable load of NoCs by an average of 20:9% and 133:3% compared to existing WiNoCs and wireline NoCs, respectively

A resilient 2-D waveguide communication fabric for hybrid wired-wireless NoC design

Hybrid wired-wireless Network-on-Chip (WiNoC) has emerged as an alternative solution to the poor scalability and performance issues of conventional wireline NoC design for future System-on-Chip (SoC). Existing feasible wireless solution for WiNoCs in the form of millimeter wave (mm-Wave) relies on free space signal radiation which has high power dissipation with high degradation rate in the signal strength per transmission distance. Moreover, over the lossy wireless medium, combining wireless and wireline channels drastically reduces the total reliability of the communication fabric. Surface wave has been proposed as an alternative wireless technology for low power on-chip communication. With the right design considerations, the reliability and performance benefits of the surface wave channel could be extended. In this paper, we propose a surface wave communication fabric for emerging WiNoCs that is able to match the reliability of traditional wireline NoCs. First, we propose a realistic channel model which demonstrates that existing mm-Wave WiNoCs suffers from not only free-space spreading loss (FSSL) but also molecular absorption attenuation (MAA), especially at high frequency band, which reduces the reliability of the system. Consequently, we employ a carefully designed transducer and commercially available thin metal conductor coated with a low cost dielectric material to generate surface wave signals with improved transmission gain. Our experimental results demonstrate that the proposed communication fabric can achieve a 5dB operational bandwidth of about 60GHz around the center frequency (60GHz). By improving the transmission reliability of wireless layer, the proposed communication fabric can improve maximum sustainable load of NoCs by an average of 20:9% and 133:3% compared to existing WiNoCs and wireline NoCs, respectively

Nano/Bio-Receiver Architectures and Detection Methods for Molecular Communications

Internet of Nano Things (IoNT) is an emerging technology, which aims at extending the connectivity into nanoscale and biological environments with collaborative networks of artificial nanomachines and biological entities integrated into the Internet. To enable the IoNT and its groundbreaking applications, such as real-time intrabody health monitoring, it is imperative to devise nanoscale communication techniques with low-complexity transceiver architectures. Bio-inspired molecular communications (MC), which uses molecules to transfer information, is the most promising technique to realise IoNT due to its inherent biocompatibility and reliability in physiologically-relevant environments. Despite the substantial body of work concerning MC, the implications of an interface between MC channel and practical MC transceiver architectures are largely neglected, leading to a major gap between theory and practice. As the first step to remove this discrepancy, in this thesis, I develop a realistic analytical ICT model for microfluidic MC with surface-based receivers as a convection-diffusion-reaction system. In the second part, I focus on biological MC receivers, which can be implemented in living cells using synthetic biology tools. In this direction, I theoretically develop low-complexity and reliable MC detection methods exploiting the various statistics of the stochastic ligand-receptor interactions at the membrane of biological MC receivers. The estimation and detection theoretical analysis of these detection methods demonstrate that even single type of receptors can provide sufficient statistics to overcome the receptor saturation problem, cope with the interference of non-cognate molecules, and simultaneously sense the concentration of multiple types of ligands. I also propose synthetic receptor designs for the transduction of decision statistics into a representation by concentration of intracellular molecules, and design chemical reaction networks performing decoding with intracellular reactions. Finally, I fabricate a micro/nanoscale MC receiver based on graphene field-effect transistor biosensors and perform its ICT characterisation in a custom-designed microfluidic MC system with the information encoded into the concentration of DNAs. This experimental platform is the first practical demonstration of micro/nanoscale MC, and can serve as a testbed for developing realistic MC methods

Transmitter and Receiver Architectures for Molecular Communications: A Survey on Physical Design with Modulation, Coding, and Detection Techniques

Inspired by nature, molecular communications (MC), i.e., the use of molecules to encode, transmit, and receive information, stands as the most promising communication paradigm to realize the nanonetworks. Even though there has been extensive theoretical research toward nanoscale MC, there are no examples of implemented nanoscale MC networks. The main reason for this lies in the peculiarities of nanoscale physics, challenges in nanoscale fabrication, and highly stochastic nature of the biochemical domain of envisioned nanonetwork applications. This mandates developing novel device architectures and communication methods compatible with MC constraints. To that end, various transmitter and receiver designs for MC have been proposed in the literature together with numerable modulation, coding, and detection techniques. However, these works fall into domains of a very wide spectrum of disciplines, including, but not limited to, information and communication theory, quantum physics, materials science, nanofabrication, physiology, and synthetic biology. Therefore, we believe it is imperative for the progress of the field that an organized exposition of cumulative knowledge on the subject matter can be compiled. Thus, to fill this gap, in this comprehensive survey, we review the existing literature on transmitter and receiver architectures toward realizing MC among nanomaterial-based nanomachines and/or biological entities and provide a complete overview of modulation, coding, and detection techniques employed for MC. Moreover, we identify the most significant shortcomings and challenges in all these research areas and propose potential solutions to overcome some of them.This work was supported in part by the European Research Council (ERC) Projects MINERVA under Grant ERC-2013-CoG #616922 and MINERGRACE under Grant ERC-2017-PoC #780645

Terahertz Communications and Sensing for 6G and Beyond: A Comprehensive View

The next-generation wireless technologies, commonly referred to as the sixth generation (6G), are envisioned to support extreme communications capacity and in particular disruption in the network sensing capabilities. The terahertz (THz) band is one potential enabler for those due to the enormous unused frequency bands and the high spatial resolution enabled by both short wavelengths and bandwidths. Different from earlier surveys, this paper presents a comprehensive treatment and technology survey on THz communications and sensing in terms of the advantages, applications, propagation characterization, channel modeling, measurement campaigns, antennas, transceiver devices, beamforming, networking, the integration of communications and sensing, and experimental testbeds. Starting from the motivation and use cases, we survey the development and historical perspective of THz communications and sensing with the anticipated 6G requirements. We explore the radio propagation, channel modeling, and measurements for THz band. The transceiver requirements, architectures, technological challenges, and approaches together with means to compensate for the high propagation losses by appropriate antenna and beamforming solutions. We survey also several system technologies required by or beneficial for THz systems. The synergistic design of sensing and communications is explored with depth. Practical trials, demonstrations, and experiments are also summarized. The paper gives a holistic view of the current state of the art and highlights the issues and challenges that are open for further research towards 6G.Comment: 55 pages, 10 figures, 8 tables, submitted to IEEE Communications Surveys & Tutorial

Abnormality detection using molecular communications based nano-scale sensor networks

Abnormality detection is one of the most highly anticipated application areas of Molecular Communication (MC) based nanonetworks. .is task entails sensing, detection, and reporting of abnormal changes in a fluid medium that may characterize a disease or disorder using a network of collaborating nanoscale sensors. Such distributed detection (DD) problems are of paramount interest in applications of nanonetworks. For the first time in literature, we proposed to employ sequential probability ratio test (SPRT) to decision fusion (DF). .e proposed approach yields considerable gains in the average number of samples required for the decision resulting in significant improvement in decision delay, which is one of the main challenges encountered in a molecular communications based sensor network. Existing strategies for such distributed collaborative detection problems require a complete statistical characterization of the underlying communication channel between the sensors and the fusion centre (FC), with the assumption of perfectly-known or accurately estimated channel parameters. .is assumption is usually impractical both due to mathematical intractability of the analytical channel models for MC except in a few ideal cases, and the slow and dispersive signal propagation characteristics that make the channel estimation a difficult task even in these ideal cases. .is work, for the first time in the literature, proposes to employ a machine learning (ML) approach to this task and shows that this approach provides the robustness and flexibility required for practical implementation. We focus on detection based on deep learning, specifically on a feed-forward neural network and a recurrent neural network structure that learn the underlying model from data. .is study shows that the proposed DF strategy can perform well without any knowledge of the communication channel

On the development of slime mould morphological, intracellular and heterotic computing devices

The use of live biological substrates in the fabrication of unconventional computing (UC) devices is steadily transcending the barriers between science fiction and reality, but efforts in this direction are impeded by ethical considerations, the field’s restrictively broad multidisciplinarity and our incomplete knowledge of fundamental biological processes. As such, very few functional prototypes of biological UC devices have been produced to date. This thesis aims to demonstrate the computational polymorphism and polyfunctionality of a chosen biological substrate — slime mould Physarum polycephalum, an arguably ‘simple’ single-celled organism — and how these properties can be harnessed to create laboratory experimental prototypes of functionally-useful biological UC prototypes. Computing devices utilising live slime mould as their key constituent element can be developed into a) heterotic, or hybrid devices, which are based on electrical recognition of slime mould behaviour via machine-organism interfaces, b) whole-organism-scale morphological processors, whose output is the organism’s morphological adaptation to environmental stimuli (input) and c) intracellular processors wherein data are represented by energetic signalling events mediated by the cytoskeleton, a nano-scale protein network. It is demonstrated that each category of device is capable of implementing logic and furthermore, specific applications for each class may be engineered, such as image processing applications for morphological processors and biosensors in the case of heterotic devices. The results presented are supported by a range of computer modelling experiments using cellular automata and multi-agent modelling. We conclude that P. polycephalum is a polymorphic UC substrate insofar as it can process multimodal sensory input and polyfunctional in its demonstrable ability to undertake a variety of computing problems. Furthermore, our results are highly applicable to the study of other living UC substrates and will inform future work in UC, biosensing, and biomedicine