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Radio Propagation Analysis Using Quantum Annealing
... In [74] the imaging method, a variant of ray tracing, is approached with a quantum annealer. Given a number of VOLUME 11, 2023 interactions N and a set of M interaction objects, the problem to be solved is to find the dominant propagation path, i.e., the path that experiences exactly N reflections or diffractions and has minimal propagation loss (PL). ...
Modelling of electromagnetic wave propagation in telecommunications has evolved from empirical models to highly deterministic ray tracing and numerical methods. The extraordinary computational effort of these methods and their wave nature seem ideally suited to be approached by quantum algorithms. We first examine current progress by reviewing recent proposals in the field. We scrutinize potentially advantageous quantum architectures, ranging from mainstream gate-level computers and near-term, mid-scale noisy architectures with limited capabilities, to adiabatic and annealing approaches that are already in commercial use. We analyze the weaknesses and strengths of recent proposals. Beyond the core algorithm, mechanisms to bridge the quantum and classical worlds are of particular interest. Extremely diverse algorithm specifications, from those based on Hamiltonian simulations and emulation of variational optimization to the unconstrained binary formulation, are compared with the use of pure gate-level circuits and known quantum subroutines. We show that the graph Laplacian, given its ability to integrate boundary conditions, is uniquely suited for quantum propagation modelling algorithms rooted in differential numerical methods. Quantum computers could overcome the temporal and spatial limitations of classical methods for larger computational domains and, to some extent, address the problems of dispersion and stability in finite-difference approximations. The ability to express the solution of a problem as an eigenvalue problem turns out to be an advantage in the quantum world, where eigenvalues and eigenvectors are inextricably intertwined with quantum mechanics. In this paper, we identify the most promising techniques and scenarios that hold the greatest potential.
In this paper, a review of the achieved accuracy in the literature for ray tracing (RT) based channel modeling is presented with a focus on outdoor propagation scenarios in the sub-6 GHz frequency range. The achieved accuracy is analyzed from three perspectives: 1) The input parameters which include the environmental description in the form of digital maps and the corresponding constitutive material parameters; 2) from the interaction mechanisms perspective and 3) from the output perspective where the achieved accuracy of predicted path loss is reviewed. Uniform assignment of materials to the entire propagation scenario is observed in most of the works in the literature which is attributed to the composite nature of common building materials and the difficulty of characterizing all material properties especially for outdoor scenarios. The digital maps are shown to introduce a certain degree of uncertainty in the RT predictions as most common sources of the maps hardly publish the accuracy. Notwithstanding, the prediction of path loss in most RT tools is observed to be rather robust against the inaccuracies in the input parameters with most RT tools achieving a prediction accuracy with a mean error below 4 dB and a standard deviation (STD) below 8 dB.
In this article, we present our vision of the application scenarios, performance metrics, and potential key technologies of 6G wireless communication networks. We then comprehensively survey 6G wireless channel measurements, characteristics, and models for all frequency bands and all scenarios, focusing on millimeter-wave (mm-wave), terahertz, and optical wireless communication channels under all spectra; satellite, unmanned aerial vehicle (UAV), maritime, and underwater acoustic communication channels under global coverage scenarios; and high-speed train (HST), vehicle-to-vehicle (V2V), ultra-massive multiple-input, multiple-output (MIMO), orbital angular momentum (OAM), and industry Internet of Things (IoT) communication channels under full application scenarios. We also provide future research challenges of 6G channel measurements, a general standard 6G channel model framework, and models for intelligent reflection surface (IRS)-based 6G technologies and artificial intelligence (AI)-enabled channel measurements and models.
The Markov Random Field (MRF) is used for extracting feature information in images and is formed as an Ising-like model. The quantum annealing is a novel method to optimize objective functions, and objective functions have to be expressed in terms of the Ising model. Hence, the MRF can be embedded into the the quantum annealing method, and feature information of remote sensing images then can be extracted using a quantum annealing computer. Extracted information or features are used to segment an image.
A key enabler for the intelligent information society of 2030, 6G networks are expected to provide performance superior to 5G and satisfy emerging services and applications. In this article, we present our vision of what 6G will be and describe usage scenarios and requirements for multi-terabyte per second (Tb/s) and intelligent 6G networks. We present a large-dimensional and autonomous network architecture that integrates space, air, ground, and underwater networks to provide ubiquitous and unlimited wireless connectivity. We also discuss artificial intelligence (AI) and machine learning [1], [2] for autonomous networks and innovative air-interface design. Finally, we identify several promising technologies for the 6G ecosystem, including terahertz (THz) communications, very-large-scale antenna arrays [i.e., supermassive (SM) multiple-input, multiple-output (MIMO)], large intelligent surfaces (LISs) and holographic beamforming (HBF), orbital angular momentum (OAM) multiplexing, laser and visible-light communications (VLC), blockchain-based spectrum sharing, quantum communications and computing, molecular communications, and the Internet of Nano-Things.
With the advances in computer processing that have yielded an enormous increase in performance, numerical analytical approaches based on electromagnetic theory have recently been applied to mobile radio propagation analysis. One such approach is the ray-tracing method based on geometrical optics and the uniform geometrical theory of diffraction. In this paper, ray-tracing techniques that have been proposed in order to improve computational accuracy and speed are surveyed. First, imaging and ray-launching methods are described and their extended methods are surveyed as novel fundamental ray-tracing techniques. Next, various ray-tracing acceleration techniques are surveyed and categorized into three approaches, i.e., deterministic, heuristic, and brute force. Then, hybrid methods are surveyed such as those employing Physical optics, the Effective Roughness model, and the Finite-Difference Time-Domain method that have been proposed in order to improve analysis accuracy.
Multi-antenna techniques capable of exploiting the elevation dimension are
anticipated to be an important air-interface enhancement targeted to handle the
expected growth in mobile traffic. In order to enable the development and
evaluation of such multi-antenna techniques, the 3rd generation partnership
project (3GPP) has recently developed a 3-dimensional (3D) channel model. The
existing 2-dimensional (2D) channel models do not capture the elevation channel
characteristics lending them insufficient for such studies. This article
describes the main components of the newly developed 3D channel model and the
motivations behind introducing them. One key aspect is the ability to model
channels for users located on different floors of a building (at different
heights). This is achieved by capturing a user height dependency in modelling
some channel characteristics including pathloss, line-of-sight (LOS)
probability, etc. In general this 3D channel model follows the framework of
WINNERII/WINNER+ while also extending the applicability and the accuracy of the
model by introducing some height and distance dependent elevation related
parameters.
Report ITU-R M. 2412-0, Guidelines for evaluation of radio interface technologies for IMT-2020
- Itu-R M Report
Solving the Minimum Spanning Tree Problem with a Quantum Annealer
- W Oquinn
- S Mao