[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

The adoption of a reconfigurable intelligent surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to 300% higher energy efficiency in comparison with the use of regular multi-antenna amplify-and-forward relaying.

Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication

IRS is a new and revolutionizing technology that is able to significantly improve the performance of wireless communication networks, by smartly reconfiguring the wireless propagation environment with the use of massive low-cost passive reflecting elements integrated on a planar surface. Specifically, different elements of an IRS can independently reflect the incident signal by controlling its amplitude and/or phase and thereby collaboratively achieve fine-grained 3D passive beamforming for directional signal enhancement or nulling. In this article, we first provide an overview of the IRS technology, including its main applications in wireless communication, competitive advantages over existing technologies, hardware architecture as well as the corresponding new signal model. We then address the key challenges in designing and implementing the new IRS-aided hybrid (with both active and passive components) wireless network, as compared to the traditional network comprising active components only. Finally, numerical results are provided to show the great performance enhancement with the use of IRS in typical wireless networks.

Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network

Intelligent reflecting surface (IRS) is an enabling technology to engineer the radio signal propagation in wireless networks. By smartly tuning the signal reflection via a large number of low-cost passive reflecting elements, IRS is capable of dynamically altering wireless channels to enhance the communication performance. It is thus expected that the new IRS-aided hybrid wireless network comprising both active and passive components will be highly promising to achieve a sustainable capacity growth cost-effectively in the future. Despite its great potential, IRS faces new challenges to be efficiently integrated into wireless networks, such as reflection optimization, channel estimation, and deployment from communication design perspectives. In this paper, we provide a tutorial overview of IRS-aided wireless communications to address the above issues, and elaborate its reflection and channel models, hardware architecture and practical constraints, as well as various appealing applications in wireless networks. Moreover, we highlight important directions worthy of further investigation in future work.

Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial

The invention belongs to the technical field of electromagnetic wave phase modulation, in particular to a microwave millimeter wave and terahertz space electromagnetic wave phase modulator, which comprises a space phase modulation unit array, a unit phase control circuit and an antenna feed. The spatial phase modulation unit is a printed circuit or a metal surface, and generates a surface currentunder the illumination of an incident electromagnetic wave from an antenna feed source so as to radiate a scattered field to modulate the phase of the outgoing electromagnetic wave. The spatial phasemodulation unit realizes the real-time control of the spatial phase modulation unit by adding one or more electronically controllable devices. Printed circuit or metal surface shapes include: slots, rectangular patches, circular patches, through holes. Devices or materials include: PIN transistors, MEMS switches, varactor diodes, liquid crystals. The space electromagnetic wave phase modulator modulates the phase of the airborne electromagnetic wave, and the modulated electromagnetic wave will converge at a certain angle in the far field or near field, and then the electromagnetic wave beam scanning can be realized by changing the control bias voltage.

Microwave millimeter wave and terahertz space electromagnetic wave phase modulator

A beam-scanning reflectarray antenna with an offset mechanically rotational horn is presented in this paper. Bifocal design method is employed to reduce the phase error caused by the rotational horn and the offset-feed structure is utilized to minimize the feed blockage effect on the broadside beams. The simulation results show that good scanning performance can be achieved with aperture efficiency larger than 51.4% within ±15° scan angle and the gain loss of a 15° scanned beam is about 1.0 dB. The preliminary results demonstrate its promising prospect in satellite communication applications.

http://ieeexplore.ieee.org/iel7/7295716/7304376/07305529.pdf

Design of a beam-scanning reflectarray antenna with an offset mechanically rotational horn

The marine controlled-source electromagnetic (CSEM) technology has attracted much attention for its capability in directly detecting thin hydrocarbon reservoirs. The approach is based on comparing the electric field amplitude as a function of the source-receiver offset with a similar measurement for a non-hydrocarbon bearing reservoir.

Inversion Algorithms for Marine Controlled-source Electromagnetic Data

The past decade has witnessed the advances of artificial intelligence with various applications in engineering. Recently, artificial neural network empowered inverse design for metasurfaces has been developed that can design on-demand meta-atoms with diverse shapes and high performance, where the design process based on artificial intelligence is fast and automatic. However, once the inverse-designed static meta-atom is fabricated, the function of the metasurface is fixed. Reconfigurable metasurfaces can realize dynamic functions, while applying artificial intelligence to design practical reconfigurable meta-atoms inversely has not been reported yet. Here, we present a deep-learning-empowered inverse design method for freeform reconfigurable metasurfaces, which can generate on-demand reconfigurable coding meta-atoms at self-defined frequency bands. To reduce the scale of dataset, a decoupling method of the reconfigurable meta-atom based on microwave network theory is proposed at first, which can convert the inverse design process for reconfigurable coding meta-atoms to the inverse design for static structures. A convolutional neural network model is trained to predict the responses of free-shaped meta-atoms, and the genetic algorithm is applied to generate the optimal structure patterns rapidly. As a demonstration of concept, several inverse-designed examples are generated with different self-defined spectrum responses in microwave band, and an inverse-designed wideband reconfigurable metasurface prototype is fabricated and measured for beam scanning applications with broad bandwidth. Our work paves the way for the fast and automatic design process of high-performance reconfigurable metasurfaces.

Deep-Learning-Empowered Inverse Design for Freeform Reconfigurable Metasurfaces

Many electromagnetic devices can be modeled as quasi-periodic arrays such as reflectarray antennas, metasurfaces, and etc. These devices have similar array elements positioned on periodic grids. Compared with modeling of periodic arrays, efficient modeling of quasi-periodic arrays can be very challenging due to the loss of periodicity in the array. In this work we applied the reduced basis method to model quasi-periodic arrays based on the fact that a reduced basis set can be constructed from array elements due to their similarities. A new reduced basis set is constructed by considering the coupling between elements as well. Numerical examples also show a significant speed up in simulating 2D quasi-periodic arrays compared with direct modeling using integral equation solvers.

Maokun Li

Papers

Microwave millimeter wave and terahertz space electromagnetic wave phase modulator

Design of a beam-scanning reflectarray antenna with an offset mechanically rotational horn

Inversion Algorithms for Marine Controlled-source Electromagnetic Data

Deep-Learning-Empowered Inverse Design for Freeform Reconfigurable Metasurfaces

Quasi-periodic array modeling using reduced basis from elemental array