Academic literature on the topic 'Surface intelligent reconfigurable'
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Journal articles on the topic "Surface intelligent reconfigurable"
Jun, Dongsoo, and Chan-Byoung Chae. "Design and Performance Analysis of Reconfigurable Intelligent Surface with Meta-Devices." Journal of Korean Institute of Communications and Information Sciences 47, no. 6 (June 30, 2022): 882–89. http://dx.doi.org/10.7840/kics.2022.47.6.882.
Full textHou, Tianwei, Yuanwei Liu, Zhengyu Song, Xin Sun, Yue Chen, and Lajos Hanzo. "Reconfigurable Intelligent Surface Aided NOMA Networks." IEEE Journal on Selected Areas in Communications 38, no. 11 (November 2020): 2575–88. http://dx.doi.org/10.1109/jsac.2020.3007039.
Full textMa, Teng, Yue Xiao, Xia Lei, Wenhui Xiong, and Yuan Ding. "Indoor Localization With Reconfigurable Intelligent Surface." IEEE Communications Letters 25, no. 1 (January 2021): 161–65. http://dx.doi.org/10.1109/lcomm.2020.3025320.
Full textJiang, Tao, and Wei Yu. "Interference Nulling Using Reconfigurable Intelligent Surface." IEEE Journal on Selected Areas in Communications 40, no. 5 (May 2022): 1392–406. http://dx.doi.org/10.1109/jsac.2022.3143220.
Full textCanbilen, Ayse E., Ertugrul Basar, and Salama S. Ikki. "Reconfigurable Intelligent Surface-Assisted Space Shift Keying." IEEE Wireless Communications Letters 9, no. 9 (September 2020): 1495–99. http://dx.doi.org/10.1109/lwc.2020.2994930.
Full textLong, Ruizhe, Ying-Chang Liang, Yiyang Pei, and Erik G. Larsson. "Active Reconfigurable Intelligent Surface-Aided Wireless Communications." IEEE Transactions on Wireless Communications 20, no. 8 (August 2021): 4962–75. http://dx.doi.org/10.1109/twc.2021.3064024.
Full textHua, Sheng, Yong Zhou, Kai Yang, Yuanming Shi, and Kunlun Wang. "Reconfigurable Intelligent Surface for Green Edge Inference." IEEE Transactions on Green Communications and Networking 5, no. 2 (June 2021): 964–79. http://dx.doi.org/10.1109/tgcn.2021.3058657.
Full textDong, Limeng, Hui-Ming Wang, and Jiale Bai. "Active Reconfigurable Intelligent Surface Aided Secure Transmission." IEEE Transactions on Vehicular Technology 71, no. 2 (February 2022): 2181–86. http://dx.doi.org/10.1109/tvt.2021.3135498.
Full textZhu, Xusheng, Lei Yuan, Kyeong Jin Kim, Qingqing Li, and Jiliang Zhang. "Reconfigurable Intelligent Surface-Assisted Spatial Scattering Modulation." IEEE Communications Letters 26, no. 1 (January 2022): 192–96. http://dx.doi.org/10.1109/lcomm.2021.3127020.
Full textBai, Tong, Cunhua Pan, Chao Han, and Lajos Hanzo. "Reconfigurable Intelligent Surface Aided Mobile Edge Computing." IEEE Wireless Communications 28, no. 6 (December 2021): 80–86. http://dx.doi.org/10.1109/mwc.001.2100142.
Full textDissertations / Theses on the topic "Surface intelligent reconfigurable"
Bachu, Krishna Prasad. "Signal processing at EM level using metasurfaces." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24693/.
Full textGiorgini, Giacomo. "Channel estimation schemes in the presence of reconfigurable intelligent surfaces." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22878/.
Full textMursia, Placido. "Multi-antenna methods for scalable beyond-5G access networks." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS532.
Full textThe exponential increase of wireless user equipments (UEs) and network services associated with current 5G deployments poses several unprecedented design challenges that need to be addressed with the advent of future beyond-5G networks and novel signal processing and transmission schemes. In this regard, massive MIMO is a well-established access technology, which allows to serve many tens of UEs using the same time-frequency resources. However, massive MIMO exhibits scalability issues in massive access scenarios where the UE population is composed of a large number of heterogeneous devices. In this thesis, we propose novel scalable multiple antenna methods for performance enhancement in several scenarios of interest. Specifically, we describe the fundamental role played by statistical channel state information (CSI) that can be leveraged for reduction of both complexity and overhead for CSI acquisition, and for multiuser interference suppression. Moreover, we exploit device-to-device communications to overcome the fundamental bottleneck of conventional multicasting. Lastly, in the context of millimiter wave communications, we explore the benefits of the recently proposed reconfigurable intelligent surfaces (RISs). Thanks to their inherently passive structure, RISs allow to control the propagation environment and effectively counteract propagation losses and substantially increase the network performance
Song, Jian. "A Stochastic Geometry Approach to the Analysis and Optimization of Cellular Networks." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS545.
Full textThe main focus of this thesis is on modeling, performance evaluation and system-level optimization of next-generation cellular networks by using stochastic geometry. In addition, the emerging technology of Reconfigurable Intelligent Surfaces (RISs) is investigated for application to future wireless networks. In particular, relying on a Poisson-based abstraction model for the spatial distribution of nodes and access points, this thesis develops a set of new analytical frameworks for the computation of important performance metrics, such as the coverage probability and potential spectral efficiency, which can be used for system-level analysis and optimization. More specifically, a new analytical methodology for the analysis of three-dimensional cellular networks is introduced and employed for system optimization. A novel resource allocation problem is formulated and solved by jointly combining for the first time stochastic geometry and mixed-integer non-linear programming. The impact of deploying intelligent reflecting surfaces throughout a wireless network is quantified with the aid of line point processes, and the potential benefits of RISs against relaying are investigated with the aid of numerical simulations
Massari, Devis. "Smart Radio Environments using Reconfigurable Meta-Surfaces." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19590/.
Full textPraia, João Miguel Rocha. "Um projeto de sistema de comunicações com reconhecimento de contexto para a banda THz." Master's thesis, 2021. http://hdl.handle.net/10071/24172.
Full textTerahertz (THz)-band communications are considered a crucial technology for ultrahigh data rate transmission in future-generation wireless communication systems. The extensive available bandwidths at THz frequencies come at the cost of severe propagation losses and power limitations, which results in very short communication distances. Reconfigurable intelligent surfaces are a promising technology to overcome this limitation as they can be used to shape THz waves by adequately adjusting the phase shifts. This dissertation focuses on the study of an effective system for THz wireless communications environment. In this dissertation, we design a RIS-assisted ultra-massive multiple-input multiple-output (UM-MIMO) wireless communication system. To maximize the achievable rate of the system, while coping with the large problem setting that is typical in RIS-aided UM-MIMO systems, a low complexity accelerated proximal gradient (APG) algorithm is developed for computing the phase-shifts of the RIS elements. We also consider the adoption of hybrid precoding which is necessary for viable UM-MIMO THz implementations and evaluate the impact of non-idealities that are typical in practical implementations of the system. Numerical results demonstrate that the larger the RIS is, the higher data rate the system achieves, and that it should be located in the vicinity of the receiver or transmitter. The effectiveness of the proposed algorithm is also proven, even when considering realistic quantization of discrete phase shifts and imperfect channel knowledge.
Books on the topic "Surface intelligent reconfigurable"
Zhang, Hongliang, Boya Di, Lingyang Song, and Zhu Han. Reconfigurable Intelligent Surface-Empowered 6G. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73499-2.
Full textBook chapters on the topic "Surface intelligent reconfigurable"
Zhang, Hongliang, Boya Di, Lingyang Song, and Zhu Han. "RIS Aided MIMO Communications." In Reconfigurable Intelligent Surface-Empowered 6G, 19–104. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73499-2_2.
Full textZhang, Hongliang, Boya Di, Lingyang Song, and Zhu Han. "Convergences of RISs with Existing Wireless Technologies." In Reconfigurable Intelligent Surface-Empowered 6G, 105–60. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73499-2_3.
Full textZhang, Hongliang, Boya Di, Lingyang Song, and Zhu Han. "Introductions and Basics." In Reconfigurable Intelligent Surface-Empowered 6G, 1–17. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73499-2_1.
Full textZhang, Hongliang, Boya Di, Lingyang Song, and Zhu Han. "RIS Aided RF Sensing and Localization." In Reconfigurable Intelligent Surface-Empowered 6G, 161–251. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73499-2_4.
Full textLiu, Hang, Xiaojun Yuan, and Ying-Jun Angela Zhang. "PHY-Layer Design Challenges in Reconfigurable Intelligent Surface Aided 6G Wireless Networks." In Computer Communications and Networks, 53–81. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72777-2_5.
Full textLe, Chi-Bao, Dinh-Thuan Do, and Samarendra Nath Sur. "Reconfigurable Intelligent Surface (RIS)-Assisted Wireless Systems: Potentials for 6G and a Case Study." In Advances in Communication, Devices and Networking, 367–78. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2911-2_39.
Full textTruong, Phuc Quang, and Ca Phan Van. "Reconfigurable Intelligent Surfaces for Downlink Cellular Networks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 20–32. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08878-0_2.
Full textJaafar, Wael, Lina Bariah, Sami Muhaidat, and Halim Yanikomeroglu. "Enhancing UAV-Based Public Safety Networks with Reconfigurable Intelligent Surfaces." In Intelligent Unmanned Air Vehicles Communications for Public Safety Networks, 145–67. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1292-4_7.
Full textBoulogeorgos, Alexandros-Apostolos A., and Angeliki Alexiou. "Reconfigurable Intelligent Surfaces for Exploitation of the Randomness of Wireless Environments." In Statistical Modeling of Reliability Structures and Industrial Processes, 195–216. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003203124-12.
Full textPogaku, Arjun Chakravarthi, Nhan Duc Nguyen, Anh-Tu Le, and Dinh-Thuan Do. "Enabling Cognitive Radio in NOMA-Assisted Reconfigurable Intelligent Surfaces: Outage Performance Analysis." In Advances in Communication, Devices and Networking, 569–81. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2004-2_52.
Full textConference papers on the topic "Surface intelligent reconfigurable"
Liu, Yiming, Erwu Liu, Rui Wang, and Yuanzhe Geng. "Reconfigurable Intelligent Surface Aided Wireless Localization." In ICC 2021 - IEEE International Conference on Communications. IEEE, 2021. http://dx.doi.org/10.1109/icc42927.2021.9500437.
Full textAnim, Kyei, Md Abu Saleh Tajin, Chelsea E. Amanatides, Genevieve Dion, and Kapil R. Dandekar. "Conductive Fabric-Based Reconfigurable Intelligent Surface." In 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/USNC-URSI). IEEE, 2022. http://dx.doi.org/10.1109/ap-s/usnc-ursi47032.2022.9887182.
Full textAtapattu, Saman, Rongfei Fan, Prathapasinghe Dharmawansa, Gongpu Wang, and Jamie Evans. "Two–Way Communications via Reconfigurable Intelligent Surface." In 2020 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2020. http://dx.doi.org/10.1109/wcnc45663.2020.9120479.
Full textTao, Yang, and Zhaoyang Zhang. "Distributed Computational Imaging with Reconfigurable Intelligent Surface." In 2020 International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2020. http://dx.doi.org/10.1109/wcsp49889.2020.9299878.
Full textHe, Jinglian, Kaiqiang Yu, Yong Zhou, and Yuanming Shi. "Reconfigurable Intelligent Surface Enhanced Cognitive Radio Networks." In 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall). IEEE, 2020. http://dx.doi.org/10.1109/vtc2020-fall49728.2020.9348788.
Full textLin, Shaoe, Miaowen Wen, Marco Di Renzo, and Fangjiong Chen. "Reconfigurable Intelligent Surface-Based Quadrature Reflection Modulation." In ICC 2021 - IEEE International Conference on Communications. IEEE, 2021. http://dx.doi.org/10.1109/icc42927.2021.9500782.
Full textHuang, Shanfeng, Shuai Wang, Rui Wang, Miaowen Wen, and Kaibin Huang. "Reconfigurable Intelligent Surface Assisted Edge Machine Learning." In ICC 2021 - IEEE International Conference on Communications. IEEE, 2021. http://dx.doi.org/10.1109/icc42927.2021.9500445.
Full textWang, Wen, Hui Tian, Wanli Ni, and Meihui Hua. "Reconfigurable Intelligent Surface Aided Secure UAV Communications." In 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2021. http://dx.doi.org/10.1109/pimrc50174.2021.9569667.
Full textWang, Jun, Ying-Chang Liang, Yiyang Pei, and Xuemin Sherman Shen. "Reconfigurable Intelligent Surface for Small Cell Network." In GLOBECOM 2021 - 2021 IEEE Global Communications Conference. IEEE, 2021. http://dx.doi.org/10.1109/globecom46510.2021.9685214.
Full textMohammed, Neekar M., Stephen C. Creagh, Sergio Terranova, Hamidreza Taghvaee, Mir Lodro, Gregor Tanner, and Gabriele Gradoni. "Reconfigurable intelligent surface design in phase-space." In 2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC). IEEE, 2022. http://dx.doi.org/10.23919/at-ap-rasc54737.2022.9814368.
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