[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Reconfigurable intelligent surfaces (RISs) are an emerging transmission technology for application to wireless communications. RISs can be realized in different ways, which include (i) large arrays of inexpensive antennas that are usually spaced half of the wavelength apart; and (ii) metamaterial-based planar or conformal large surfaces whose scattering elements have sizes and inter-distances much smaller than the wavelength. Compared with other transmission technologies, e.g., phased arrays, multi-antenna transmitters, and relays, RISs require the largest number of scattering elements, but each of them needs to be backed by the fewest and least costly components. Also, no power amplifiers are usually needed. For these reasons, RISs constitute a promising software-defined architecture that can be realized at reduced cost, size, weight, and power (C-SWaP design), and are regarded as an enabling technology for realizing the emerging concept of smart radio environments (SREs). In this paper, we (i) introduce the emerging research field of RIS-empowered SREs; (ii) overview the most suitable applications of RISs in wireless networks; (iii) present an electromagnetic-based communication-theoretic framework for analyzing and optimizing metamaterial-based RISs; (iv) provide a comprehensive overview of the current state of research; and (v) discuss the most important research issues to tackle. Owing to the interdisciplinary essence of RIS-empowered SREs, finally, we put forth the need of reconciling and reuniting C. E. Shannon’s mathematical theory of communication with G. Green’s and J. C. Maxwell’s mathematical theories of electromagnetism for appropriately modeling, analyzing, optimizing, and deploying future wireless networks empowered by RISs.

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Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

In this chapter we deal with the following nonlinear fractional programming problem: 

$$P:\mathop{{\max }}\limits_{{x \in s}} q(x) = (f(x) + \alpha )/((x) + \beta )$$

where f, g: R n → R, α, β ∈ R, S ⊆ R n . To simplify things, and without restricting the generality of the problem, it is usually assumed that, g(x) + β + 0 for all x ∈ S,S is non-empty and that the objective function has a finite optimal value.

Nonlinear Fractional Programming

What is a reconfigurable intelligent surface? What is a smart radio environment? What is a metasurface? How do metasurfaces work and how to model them? How to reconcile the mathematical theories of communication and electromagnetism? What are the most suitable uses and applications of reconfigurable intelligent surfaces in wireless networks? What are the most promising smart radio environments for wireless applications? What is the current state of research? What are the most important and challenging research issues to tackle? 
These are a few of the many questions that we investigate in this short opus, which has the threefold objective of introducing the emerging research field of smart radio environments empowered by reconfigurable intelligent surfaces, putting forth the need of reconciling and reuniting C. E. Shannon's mathematical theory of communication with G. Green's and J. C. Maxwell's mathematical theories of electromagnetism, and reporting pragmatic guidelines and recipes for employing appropriate physics-based models of metasurfaces in wireless communications.

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead.

Radio access technologies for cellular mobile communications are typically characterized by multiple access schemes, e.g., frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA), and OFDMA. In the 4th generation (4G) mobile communication systems such as Long-Term Evolution (LTE) (Au et al., Uplink contention based SCMA for 5G radio access. Globecom Workshops (GC Wkshps), 2014. doi:10.1109/GLOCOMW.2014.7063547) and LTE-Advanced (Baracca et al., IEEE Trans. Commun., 2011. doi:10.1109/TCOMM.2011.121410.090252; Barry et al., Digital Communication, Kluwer, Dordrecht, 2004), standardized by the 3rd Generation Partnership Project (3GPP), orthogonal multiple access based on OFDMA or single carrier (SC)-FDMA is adopted. Orthogonal multiple access was a reasonable choice for achieving good system-level throughput performance with simple single-user detection. However, considering the trend in 5G, achieving significant gains in capacity and system throughput performance is a high priority requirement in view of the recent exponential increase in the volume of mobile traffic. In addition the proposed system should be able to support enhanced delay-sensitive high-volume services such as video streaming and cloud computing. Another high-level target of 5G is reduced cost, higher energy efficiency and robustness against emergencies.

Non-Orthogonal Multiple Access (NOMA) for cellular future radio access

Compared with the Multiple-Input Multiple-Output (MIMO) systems coded with Space-Time Block Code (STBC), Spatial Modulation (SM) has high spectral efficiency and low diversity gain. After combined with Space-Time Block Code (STBC), so called STBC-SM is able to obtain higher diversity gain at the same time. In this paper, we propose a new full-diversity STBC-SM scheme for spatial modulation systems with four transmit antennas. The transmitted information is partitioned into two parts for STBC-SM codeword selection and modulation symbol mapping, respectively. The proposed codeword matrices are constructed by simultaneously choosing the transmit antennas of one pair of orthogonal STBC instead of only one. Precoding and symbol-crossing of the modulated symbols are carried out to ensure higher diversity gain. By theoretical analysis, the designed scheme is proved to be full diversity. Finally, simulation results is presented and show that the proposed STBC-SM obviously improves the diversity gain and system performance.

A Design of Space-Time Block Code for Spatial Modulation Systems

The invention discloses a lapping rubber support high main pressure shearing fatigue testing device which comprises flange, pressing bolt and pressure sensor, the lapping rubber support is fixed on the flange between the motion plate and side wall and is pressed tightly with the pressing bolt the pressing force of which is monitoring by the sensor. The invention acquires the dual direction shearing fatigue loading when adding pressure, and is able to perform the test with normal test machine. The invention is of simple structure and operation.

Laminated rubber support high-cycle press-shear fatigue performance testing device

In this paper, the interference-efficient based resource allocation for uplink transmission in an OFDMA-based cognitive radio network is studied. The interference efficiency (IE) is defined as the total data rate of secondary users (SUs) over sum interference power imposed on primary users (PUs). The objective is to maximize the total IE of SUs subject to transmit power constraints of SUs, subcarrier assignment constraint and the interference power threshold constraints of SUs. The original mixed integer fractional programming problem is converted into the convex one which is solved by using the convex optimization technique. Simulation results show the effectiveness of the proposed algorithm in terms of the interference to PUs and transmission efficiency.

Resource Allocation for OFDMA-Based Cognitive Networks: An Interference-Efficient Perspective

In consideration of all possible channel uncertainties without the assumption of perfect channel state information (CSI), a robust power allocation algorithm for underlay orthogonal frequency division multiple cognitive radio networks is presented. This algorithm can assign transmission power of each secondary user (SU) on each sub-carrier based on total transmission power minimization of SUs under the constraints corresponding to signal-to-interference-noise ratio of SUs and the interference power constraint to guarantee the quality of service of primary users (PUs). In addition, the CSI errors are assumed to be bounded with ellipsoid and interval sets. Through the worst case approach, the original optimization problem is converted into a convex one solved by Lagrange dual decomposition method. The proposed robust algorithm provides a trade-off between robustness and system performance. Simulation results prove that the suboptimal solution can achieve a satisfactory performance for both SUs and PUs at the same time.

Robust Power Allocation for OFDM Based Underlay Cognitive Radio Networks with Channel Uncertainties

The invention relates to the technical field of resource allocation in a heterogeneous wireless network, in particular to a robust resource allocation method for a heterogeneous energy-carrying communication network under a non-ideal channel. The method comprises the following steps: initializing system parameters; converting the optimal energy efficiency model of the system into a transmitting power-power shunt coefficient joint optimization problem; converting a nonlinear optimization problem containing probability constraints into a convex problem through a maximum probability machine method; fixing the initialized power flow coefficient, and obtaining the optimal transmitting power by using the Lagrange duality principle; fixing the optimal transmitting power, obtaining the optimal power distribution coefficient, and obtaining the optimal distribution scheme of the system. The method not only can improve the system energy efficiency, but also can improve the system robustness, andhas certain guiding significance in the practical application aspects of effectively reducing the outage probability of the mobile terminal, improving the data transmission stability and the like.

Yongjun Xu

Papers

A Design of Space-Time Block Code for Spatial Modulation Systems

Laminated rubber support high-cycle press-shear fatigue performance testing device

Resource Allocation for OFDMA-Based Cognitive Networks: An Interference-Efficient Perspective

Robust Power Allocation for OFDM Based Underlay Cognitive Radio Networks with Channel Uncertainties

Robust resource allocation method for heterogeneous energy-carrying communication network under non-ideal channel