A Mathematical Approach for Hidden Node Problem in Cognitive Radio Networks

Cognitive radio (CR) technology has emerged as a realistic solution to the spectrum scarcity problem in present day wireless networks. A major challenge in CR radio networks is the hidden node problem, which is the inability of the CR nodes to detect the primary user. This paper proposes energy detector-based distributed sequential cooperative spectrum sensing over Nakagami-m fading, as a tool to solve the hidden node problem. The derivation of energy detection performance over Nakagami-m fading channel is presented. Since the observation represents a random variable, likelihood ratio test (LRT) is known to be optimal in this type of detection problem. The LRT is implemented using the Neyman-Pearson Criterion (maximizing the probability of detection but at a constraint of false alarm probability). The performance of the proposed method has been evaluated both by numerical analysis and simulations. The effect of cooperation among a group of CR nodes and system parameters such as SNR, detection threshold and number of samples per CR nodes is investigated. Results show improved detection performance by implementing the proposed model

Investigation of HAPs Propagation Channel for Wireless Access in a Tropical Region at Ka-Band

In the last few years, High Altitude Platforms (HAPs) have attracted considerable effort due to their ability to exploit the advantages of satellite and terrestrial-based systems. Rain attenuation is the most dominant atmospheric impairment, especially at such frequency band. This paper addresses the modelling of rain attenuation and describes a propagation channel model for HAPs at Ka-band to provide efficient and robust wireless access for tropical regions. The attenuation due to rain is modeled based on three years measured data for Johor Bahru to estimate the actual effect of rain on signals at Ka band. The radio propagation channel is usually characterized as a random multipath channel. Specifically, a statistical derivation of probability distribution function for Rayleigh and Rician fading channels are presented. The model consists of multiple path scattering effects, time dispersion, and Doppler shifts acting on the HAPs communication link. Simulation results represent the fading signal level variations. Results show perfect agreement between simulation and theoretical, thereby conforming to the multipath structures. The information obtained will be useful to system engineers for HAPs link budget analysis in order to obtain the required fade margin for optimal system performance in tropical regions

Active Inference for Sum Rate Maximization in UAV-Assisted Cognitive NOMA Networks

Given the surge in wireless data traffic driven by the emerging Internet of Things (IoT), unmanned aerial vehicles (UAVs), cognitive radio (CR), and non-orthogonal multiple access (NOMA) have been recognized as promising techniques to overcome massive connectivity issues. As a result, there is an increasing need to intelligently improve the channel capacity of future wireless networks. Motivated by active inference from cognitive neuroscience, this paper investigates joint subchannel and power allocation for an uplink UAV-assisted cognitive NOMA network. Maximizing the sum rate is often a highly challenging optimization problem due to dynamic network conditions and power constraints. To address this challenge, we propose an active inference-based algorithm. We transform the sum rate maximization problem into abnormality minimization by utilizing a generalized state-space model to characterize the time-changing network environment. The problem is then solved using an Active Generalized Dynamic Bayesian Network (Active-GDBN). The proposed framework consists of an offline perception stage, in which a UAV employs a hierarchical GDBN structure to learn an optimal generative model of discrete subchannels and continuous power allocation. In the online active inference stage, the UAV dynamically selects discrete subchannels and continuous power to maximize the sum rate of secondary users. By leveraging the errors in each episode, the UAV can adapt its resource allocation policies and belief updating to improve its performance over time. Simulation results demonstrate the effectiveness of our proposed algorithm in terms of cumulative sum rate compared to benchmark schemes.Comment: This paper has been accepted for the 2023 IEEE 9th World Forum on Internet of Things (IEEE WFIoT2023

Recent Advances in Chemical Functionalisation of Graphene and Sensing Applications

Graphene, a one-atom-thick, sp2-hybridised allotrope of carbon has attracted massive interest due to its outstanding electrical, mechanical, thermal and optical properties. The material of graphene is remarkably stable, with a huge potential for developing various types of sensors, including biomedical sensing where enhanced specificity, sensitivity, label-free nature and cost effectiveness for rapid point-of-care detection of diseases are paramount. This is due to the simplicity with which its electronic properties can be modified since each atom in the structure directly interacts with the sensing environment. These unique characteristics can be exploited for several kinds of sensing applications such as electrochemical and electrical sensors as well as optical sensors. While pristine graphene is desirable for applications that require high electrical conductivity, many other applications require functionalised graphene for optimal performance. Therefore, the functionalisation of graphene is a significant step towards tuning its structure for various sensing applications. In this review, we report recent technological progress in the chemical functionalisation of graphene and its sensing applications

Carbon nanotube field effect transistors: toward future nanoscale electronics

As the scaling down of silicon MOSFET is approaching its utmost limit, different materials are effectively being examined in order to keep the scaling trend. Among these, carbon nanotubes (CNTs) have emerged as one of the most extensively studied materials due to their excellent performance properties such as minimal short channel effects, high mobility, and high normalized drive currents. CNTs are the backbone of carbon nanotube field effect transistor, which is considered as the most preferred candidate for the replacement of silicon transistors. Despite their practical significance, a well-organized framework, and consistent review are still lacking. To this end, this paper presents an intensive review in order to define the state of the art in this field from a fresh and unifying viewpoint while elucidating fruitful insights into recent advances and future trends. In particular, we review material properties and structures. Specifically, we emphasize on the most relevant device fabrication and current modeling concepts. Furthermore, we distill key insights into recent advances and challenges that may sustain or expand future applications. The future research directions are also carefully analyzed

The evolution of Ethernet Passive Optical Network (EPON) and future trends

The tremendous Internet traffic growth has confirmed that the telecommunications backbone is moving aggressively from a time division multiplexing (TDM) orientation to a focus on Ethernet solution. Ethernet PON, which presents the convergence of low-cost Ethernet and fiber infrastructures, has taken over the market initially dominated by Digital Subscriber Line (DSL) and cable modems. It is a new technology that is simple, inexpensive, and scalable, having the ability to deliver massive data services to end-users over a single network. This paper reviewed the evolution of Ethernet Passive Optical Network (EPON), with focus on the current development process of the future high-data-rate access networks such as Next-Generation Passive Optical Network Stage 2 (NG-PON2), Wavelength Division Multiplexing (WDM) PON, and Orthogonal Frequency Division Multiplexing (OFDM) PON. In addition, the recently concluded 100 Gb Ethernet Passive Optical Network (100G-EPON) is reviewed with the aim of highlighting the recent developments in the field. With this comprehensive and up-to-date review, we equip network operators and interested practitioners to focus on common priorities and timelines. Another goal of this study is to identify technical remedies for future investigation

Theoretical modelling of charge transport properties of individual single-wall carbon nanotubes

Experimental projection of transport properties of semiconductor devices faces a challenge nowadays. As devices scale to nanometre scale range, the classical transport equations used in current device simulators can no longer be applied. Conversely, the use of a more accurate and better non-equilibrium green function (NEGF) is limited by the fact that it requires excessive quantum of memory and computational time, having quasi-separable matrices that are extremely convoluted to solve. This work exploits the Boltzmann Transport Equation (BTE) to assess the transport properties of carbon nanotubes. Previous works on solving the BTE have employed either a stochastic method or an approximate method, both of which do not possess the necessary properties for practical device applications. Therefore, this work represents the first direct theoretical solution of the BTE for one-dimensional carbon nanotubes that can be utilized for practical device applications. The complete spectrum of transport in CNTs extending from ohmic to high-field through ballistic transmission is examined to delineate plethora of transport properties. The transport for arbitrary values of the electric field is based on the BTE applied to experimental data on CNTs. In the limit of low field, the mobility expressions are obtained in terms of the mean free path (mfp) that is distinctly shorter than the length of the sample. The ohmic resistance is quantized a value of 6.453k-ohms consistent with experimental findings with transmission approaching unity as channel length shrinks below the carrier mfp. The emission of a quantum was observed to lower the saturation velocity that is independent of scattering and hence ballistic. Transition to ballistic domain was found to occur when the channel length is scaled below the ballistic limit that is shown to be the extended version of the long-channel mfp modulated by injections from the contacts, yet the mobility degrades. The mobility degradation is shown to be the cause of resistance quantum in the low-channel length limit. These findings are important in predicting the transport properties of low-dimensional CNTs

Carbon Nanotube-Graphene hybrid: Recent Synthesis Methodologies and Applications

The melding of one-dimensional (1D) carbon nanotubes (CNTs) and two-dimensional (2D) graphene to generate a CNT-graphene hybrid with 3-dimensional (3D) features has generated a lot of scientific interest owing to the synergistic consequences of the resulting interface hybrid on the electrical, mechanical, electrochemical and optical properties, which presents plethora of opportunities in both fundamental research and device applications. The review presents an overview of the recent perspectives made in the field of CNT-graphene hybrid architectures. The possible applications particularly in device sensing, as well as challenges are also presented