Related papers: Artificial Intelligence Based Cognitive Routing fo…
Artificial neural networks (NNs) can be implemented using chemical reaction networks (CRNs), where the concentrations of species act as inputs and outputs. In such biochemical computing, noise-robust computing is crucial due to the…
Traditional artificial neural networks consist of nodes with non-oscillatory dynamics. Biological neural networks, on the other hand, consist of oscillatory components embedded in an oscillatory environment. Motivated by this feature of…
This work investigates online learning techniques for a cognitive radar network utilizing feedback from a central coordinator. The available spectrum is divided into channels, and each radar node must transmit in one channel per time step.…
Powerful spectrum sensing schemes enable cognitive radios (CRs) to find transmission opportunities in spectral resources allocated exclusively to the primary users. In this paper, maximizing the average throughput of a secondary user by…
The field of wireless networks has been rapidly developed during the past decade due to the increasing popularity of the mobile devices. The great demand for mobility and connectivity makes wireless networking a field whose continuous…
Routing, as a basic phenomena, by itself, has got umpteen scopes to analyse, discuss and arrive at an optimal solution for the technocrats over years. Routing is analysed based on many factors; few key constraints that decide the factors…
Cognitive radio networks (CRNs) is the next generation of wireless communication. This type of network requires efficent spectrum allocation methods. This paper presents a new meta-heuristic evolutionary method for solving the channel…
Over the past 50 years, conventional network routing design has undergone substantial growth, evolving from small networks with static nodes to large systems connecting billions of devices. This progress has been achieved through the…
In this letter, we investigate joint application of reconfigurable intelligent surface (RIS) and vertical beamforming in cognitive radio networks (CRN). After properly modeling the network, an optimization problem is formed to jointly…
Unmanned aerial vehicles (UAVs) can provide wireless access services to terrestrial users without geographical limitations and will become an essential part of the future communication system. However, the openness of wireless channels and…
Recurrent Networks are one of the most powerful and promising artificial neural network algorithms to processing the sequential data such as natural languages, sound, time series data. Unlike traditional feed-forward network, Recurrent…
Unmanned aerial vehicles (UAVs) have been widely employed to enhance the end-to-end performance of wireless communications since the links between UAVs and terrestrial nodes are line-of-sight (LoS) with high probability. However, the…
Recent work suggests goal-driven training of neural networks can be used to model neural activity in the brain. While response properties of neurons in artificial neural networks bear similarities to those in the brain, the network…
In recent years, several studies have provided insight on the functioning of the brain which consists of neurons and form networks via interconnection among them by synapses. Neural networks are formed by interconnected systems of neurons,…
Cognitive Radio Network (CRN) provides effective capabilities for resource allocation with the valuable spectrum resources in the network. It provides the effective allocation of resources to the unlicensed users or Secondary Users (SUs) to…
This paper describes the architecture and performance of ORACLE, an approach for detecting a unique radio from a large pool of bit-similar devices (same hardware, protocol, physical address, MAC ID) using only IQ samples at the physical…
Cognitive radio (CR) technology enables an intelligent wireless communication system. CR provides an efficient solution for the inefficient spectrum utilization by allowing dynamic and opportunistic spectrum access. In designing CR…
Artificial intelligence (AI) is envisioned to play a key role in future wireless technologies, with deep neural networks (DNNs) enabling digital receivers to learn to operate in challenging communication scenarios. However, wireless…
A fundamental problem in cognitive radio systems is that the cognitive radio is ignorant of the primary channel state and, hence, of the amount of actual harm it inflicts on the primary license holder. Sensing the primary transmitter does…
5G networks offer exceptional reliability and availability, ensuring consistent performance and user satisfaction. Yet they might still fail when confronted with the unexpected. A resilient system is able to adapt to real-world complexity,…