[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

Diverse electromagnetic (EM) responses of a programmable metasurface with a relatively large scale have been investigated, where multiple functionalities are obtained on the same surface. The unit cell in the metasurface is integrated with one PIN diode, and thus a binary coded phase is realized for a single polarization. Exploiting this anisotropic characteristic, reconfigurable polarization conversion is presented first. Then the dynamic scattering performance for two kinds of sources, i.e. a plane wave and a point source, is carefully elaborated. To tailor the scattering properties, genetic algorithm, normally based on binary coding, is coupled with the scattering pattern analysis to optimize the coding matrix. Besides, inverse fast Fourier transform (IFFT) technique is also introduced to expedite the optimization process of a large metasurface. Since the coding control of each unit cell allows a local and direct modulation of EM wave, various EM phenomena including anomalous reflection, diffusion, beam steering and beam forming are successfully demonstrated by both simulations and experiments. It is worthwhile to point out that a real-time switch among these functionalities is also achieved by using a field-programmable gate array (FPGA). All the results suggest that the proposed programmable metasurface has great potentials for future applications.

/pdf/a-programmable-metasurface-with-dynamic-polarization-2stizain11.pdf

A programmable metasurface with dynamic polarization, scattering and focusing control

An electronically reconfigurable reflectarray antenna (RRA) with $10\times10$ elements is presented with a detailed design procedure for an improved beam-scanning performance. The element, designed at Ku band using a simple patch structure with one PIN diode and two substrate layers, can be electronically controlled to generate two states with 180° phase difference and low reflection loss. A reflectarray prototype is fabricated and experimentally studied for proof of principle. The limitations of the small aperture size are analyzed in detail, and synthetic optimizations of both feed location and aperture phase distribution are used to improve the beam-scanning performance of the prototype. Experimental results agree well with the full-wave simulations, and scan beams within ${\pm}{50}^\circ$ range are obtained with a maximum aperture efficiency of 17.9% at 12.5 GHz. Consistent scan beams are obtained from 11.75 to 13.25 GHz. Furthermore, the versatile beam-forming capability of the RRA is also demonstrated by a wide-beam pattern synthesis. A fast beam-switching time ( $12\;\upmu \text{s}$ ) is theoretically analyzed and verified by the measurement.

A 1-Bit $10 \times 10$ Reconfigurable Reflectarray Antenna: Design, Optimization, and Experiment

A domain decomposition scheme based on the equivalence principle, similar to Huygens' principle, for integral equation solvers and the method of moments is introduced. The equivalence principle allows the replacement of unknown currents distributed in a volume in space by equivalence currents residing on the surface that bounds the volume. It also allows the dissociation of the solution of one region from that of another region. In this manner, problems of high complexity can be encapsulated by surfaces of simpler shapes using less unknowns. It can aid in parallel algorithms, reusability of solutions, as well as improving the condition number of a matrix system when disparate mesh or adaptive mesh are needed. The challenge arises when an equivalence surface intercepts a current-carrying conductor, because the breakup of the current into separate pieces gives rise to charge singularity. A junction basis can be used to mitigate this singularity. However, a better solution is to introduce a tap basis to model the current that intercepts with the equivalence surfaces. Using this scheme, the current continuity is conserved and the singularity of the charges is avoided. The solution is shown to be accurate

Wave-Field Interaction With Complex Structures Using Equivalence Principle Algorithm

A dual-frequency reconfigurable reflectarray (RRA) is proposed and verified experimentally. The RRA consists of 1600 electronically controllable elements. By integrating only a single PIN diode, the proposed element is capable to operate at two working frequencies with 1-bit phase resolution. The dual-frequency mechanism is explained through the mode analysis, and a parametric study is performed to provide guidelines for determining the two working frequencies. As an example, a 1600-element RRA prototype is realized by assembling five identical $8 \times 40$ subarrays. An field programmable gate array control board is used to achieve real-time phase control of each element individually. The experimental results show that the broadside gains of the RRA are 29.3 and 30.8 dBi at 11.1 and 14.3 GHz, respectively. Excellent beam scanning performance is also obtained at both frequencies.

A 1600-Element Dual-Frequency Electronically Reconfigurable Reflectarray at X/Ku-Band

In recent years, deep learning (DL) is becoming an increasingly important tool for solving inverse scattering problems (ISPs). This paper reviews methods, promises, and pitfalls of deep learning as applied to ISPs. More specifically, we review several state-of-the-art methods of solving ISPs with DL, and we also offer some insights on how to combine neural networks with the knowledge of the underlying physics as well as traditional non-learning techniques. Despite the successes, DL also has its own challenges and limitations in solving ISPs. These fundamental questions are discussed, and possible suitable future research directions and countermeasures will be suggested.

/pdf/a-review-of-deep-learning-approaches-for-inverse-scattering-1dpsdp7162.pdf

Maokun Li

Papers

A programmable metasurface with dynamic polarization, scattering and focusing control

A 1-Bit $10 \times 10$ Reconfigurable Reflectarray Antenna: Design, Optimization, and Experiment

Wave-Field Interaction With Complex Structures Using Equivalence Principle Algorithm

A 1600-Element Dual-Frequency Electronically Reconfigurable Reflectarray at X/Ku-Band

A review of deep learning approaches for inverse scattering problems (invited review)