相关论文: Novel energy detection using uniform noise distrib…
The availability of inexpensive devices allows nowadays to implement cognitive radio functionalities in large-scale networks such as the internet-of-things and future mobile cellular systems. In this paper, we focus on wideband spectrum…
We consider several detection situations where, under the alternative hypothesis, the signal admits a low complexity model and, under both the null and the alternative hypotheses, the distribution of the background noise is {unknown}. We…
Ultra-high-energy neutrinos and cosmic rays are excellent probes of astroparticle physics phenomena. For astroparticle physics analyses, robust and accurate reconstruction of signal parameters such as arrival direction and energy is…
This paper presents a new cooperative wireless communication network strategy that incorporates energy cooperation and data cooperation. The model establishment, design goal formulations, and algorithms for throughput maximization of the…
The IceCube collaboration has reported the first detection of high-energy astrophysical neutrinos including $\sim 50$ high-energy starting events, but no individual sources have been identified. It is therefore important to develop the most…
The sensitivity to New Physics of a low threshold scintillating argon bubble chamber measuring coherent elastic neutrino-nucleus scattering in reactors is reported. Namely, light scalar mediators, sterile neutrino oscillations, unitarity…
A beam-energy-spread monitor is under development in order to control and stabilize the energy spread of high-current single-bunch electron beams for producing a sufficient number of positrons. The author has proposed a new monitor using…
In this paper, we investigate the performance of energy detection-based spectrum sensing over F composite fading channels. To this end, an analytical expression for the average detection probability is firstly derived. This expression is…
This paper investigates a machine learning-based power allocation design for secure transmission in a cognitive radio (CR) network. In particular, a neural network (NN)-based approach is proposed to maximize the secrecy rate of the…
Development of an accurate, flexible, and numerically efficient uncertainty quantification (UQ) method is one of fundamental challenges in machine learning. Previously, a UQ method called DISCO Nets has been proposed (Bouchacourt et al.,…
This paper introduces a machine learning based collaborative multi-band spectrum sensing policy for cognitive radios. The proposed sensing policy guides secondary users to focus the search of unused radio spectrum to those frequencies that…
With the surging popularity of edge computing, the need to efficiently perform neural network inference on battery-constrained IoT devices has greatly increased. While algorithmic developments enable neural networks to solve increasingly…
A new flame detector, three orders of magnitude more powerful than the existing ones, is presented. This detector needs to be mass-produced for its use in order to be incorporated in an early forest fire detection system. A project able to…
A central goal in experimental high energy physics is to detect new physics signals that are not explained by known physics. In this paper, we aim to search for new signals that appear as deviations from known Standard Model physics in…
A steadily growing share of renewable energies with uctuating and decentralized generation as well as rising peak loads require novel solutions to ensure the reliability of electricity supply. More speci cally, grid stability is endangered…
Nuclear recoil ionization yield constitutes a critical uncertainty source in low-energy detection for dark matter (DM) and coherent elastic neutrino-nucleus scattering (CE$\nu$NS) experiments. We present a novel methodology employing…
In nuclear, particle and astroparticle physics experiments, calorimeters are used to measure the properties of particles with kinetic energies that range from a fraction of 1 eV to 10^20 eV or more. These properties are not necessarily…
Energy harvester based cognitive radio is a promising solution to address the shortage of both spectrum and energy. Since the spectrum access and power consumption patterns are interdependent, and the power value harvested from certain…
In continuation of an earlier study, we explore a Neymann-Pearson hypothesis testing scenario where, under the null hypothesis ($\cal{H}_0$), the received signal is a white noise process $N_t$, which is not Gaussian in general, and under…
This paper studies the classical problem of detecting the locations of signal occurrences in a one-dimensional noisy measurement. Assuming the signal occurrences do not overlap, we formulate the detection task as a constrained likelihood…