no code implementations • 3 Dec 2024 • Alexis I. Aravanis, Thanh Tu Lam, Olga Muñoz, Antonio Pascual-Iserte, Marco Di Renzo
In this course, the present paper introduces an accurate approximation for the moment generating function (MGF) of the aggregate other-cell interference created by base stations whose positions follow a Poisson point process of given spatial density.
no code implementations • 17 Nov 2024 • Mohammad Soleymani, Ignacio Santamaria, Eduard Jorswieck, Marco Di Renzo, Robert Schober, Lajos Hanzo
The performance of modern wireless communication systems is typically limited by interference.
no code implementations • 28 Oct 2024 • Mohammad Soleymani, Alessio Zappone, Eduard Jorswieck, Marco Di Renzo, Ignacio Santamaria
We analyze the finite-block-length rate region of wireless systems aided by reconfigurable intelligent surfaces (RISs), employing treating interference as noise.
no code implementations • 7 Oct 2024 • Houfeng Chen, Shaohua Yue, Marco Di Renzo, Hongliang Zhang
In this paper, we propose a novel method to calculate the DoF of HMIMO in multi-user near-field channels.
no code implementations • 2 Sep 2024 • Zhou Zhang, Saman Atapattu, Yizhu Wang, Marco Di Renzo
This paper addresses the challenges of throughput optimization in wireless cache-aided cooperative networks.
no code implementations • 28 Aug 2024 • Mehdi Monemi, Mehdi Rasti, Arthur S. de Sena, Mohammad Amir Fallah, Matti Latva-aho, Marco Di Renzo
While not an ideal solution, we discuss how ultra-narrowband metasurfaces can be incorporated into the manufacturing of RISs to mitigate some challenges of RIS deployment in wireless networks.
no code implementations • 17 Aug 2024 • Robert Kuku Fotock, Agbotiname Lucky Imoize, Alessio Zappone, Marco Di Renzo, Roberto Garello
The complexity of the proposed method is analyzed and numerical results are provided to show the performance of the proposed optimization method.
no code implementations • 8 Aug 2024 • Mohammad Soleymani, Ignacio Santamaria, Eduard Jorswieck, Marco Di Renzo, Jesús Gutiérrez
In a globally passive RIS, the power of the output signal of the RIS is not greater than its input power, but some RIS elements can amplify the signal.
no code implementations • 26 Jun 2024 • Mayur V. Katwe, Aryan Kaushik, Keshav Singh, Marco Di Renzo, Shu Sun, Doohwan Lee, Ana G. Armada, Yonina C. Eldar, Octavia A. Dobre, Theodore S. Rappaport
Sixth-generation (6G) networks are poised to revolutionize communication by exploring alternative spectrum options, aiming to capitalize on strengths while mitigating limitations in current fifth-generation (5G) spectrum.
no code implementations • 11 Jun 2024 • Robert Kuku Fotock, Alessio Zappone, Marco Di Renzo
This work proposes a provably convergent and low complexity optimization algorithm for the maximization of the secrecy energy efficiency in the uplink of a wireless network aided by a Reconfigurable Intelligent Surface (RIS), in the presence of an eavesdropper.
no code implementations • 9 Jun 2024 • Ruiqi Liu, Shuang Zheng, Qingqing Wu, Yifan Jiang, Nan Zhang, Yuanwei Liu, Marco Di Renzo, and George C. Alexandropoulos
Reconfigurable Intelligent Surfaces (RISs) are a novel form of ultra-low power devices that are capable to increase the communication data rates as well as the cell coverage in a cost- and energy-efficient way.
no code implementations • 16 Feb 2024 • Zhangjie Peng, Zhibo Zhang, Cunhua Pan, Marco Di Renzo, Octavia A. Dobre, Jiangzhou Wang
Specifically, by exploiting the majorization-minimization approach, each subproblem is reformulated into a tractable surrogate problem, whose closed-form solutions are obtained by Lagrange dual decomposition approach and element-wise alternating sequential optimization method.
no code implementations • 28 Jan 2024 • Ahmed Magbool, Vaibhav Kumar, Qingqing Wu, Marco Di Renzo, Mark F. Flanagan
To provide a comprehensive overview, we begin with fundamentals of ISAC and metasurfaces.
no code implementations • 13 Nov 2023 • Zixing Tang, Yuanbin Chen, Ying Wang, Tianqi Mao, Qingqing Wu, Marco Di Renzo, Lajos Hanzo
To tackle this challenge, we exploit the sparsity inherent in the cascaded channel.
no code implementations • 16 Oct 2023 • Guillermo Encinas-Lago, Antonio Albanese, Vincenzo Sciancalepore, Marco Di Renzo, Xavier Costa-Pérez
The advent of reconfigurable intelligent surfaces(RISs) brings along significant improvements for wireless technology on the verge of beyond-fifth-generation networks (B5G). The proven flexibility in influencing the propagation environment opens up the possibility of programmatically altering the wireless channel to the advantage of network designers, enabling the exploitation of higher-frequency bands for superior throughput overcoming the challenging electromagnetic (EM) propagation properties at these frequency bands.
no code implementations • 4 Oct 2023 • Hongyu Li, Shanpu Shen, Matteo Nerini, Marco Di Renzo, Bruno Clerckx
This work studies the modeling and optimization of beyond diagonal reconfigurable intelligent surface (BD-RIS) aided wireless communication systems in the presence of mutual coupling among the RIS elements.
no code implementations • 12 Sep 2023 • Gurjot Singh Bhatia, Yoann Corre, Marco Di Renzo
This paper presents an innovative method that can be used to produce deterministic channel models for 5G industrial internet-of-things (IIoT) scenarios.
no code implementations • 28 Aug 2023 • Tierui Gong, Chongwen Huang, Jiguang He, Marco Di Renzo, Mérouane Debbah, Chau Yuen
To support the extremely high spectral efficiency and energy efficiency requirements, and emerging applications of future wireless communications, holographic multiple-input multiple-output (H-MIMO) technology is envisioned as one of the most promising enablers.
no code implementations • 19 Jul 2023 • Wei Jiang, Qiuheng Zhou, Jiguang He, Mohammad Asif Habibi, Sergiy Melnyk, Mohammed El Absi, Bin Han, Marco Di Renzo, Hans Dieter Schotten, Fa-Long Luo, Tarek S. El-Bawab, Markku Juntti, Merouane Debbah, Victor C. M. Leung
Different from earlier surveys, this paper presents a comprehensive treatment and technology survey on THz communications and sensing in terms of advantages, applications, propagation characterization, channel modeling, measurement campaigns, antennas, transceiver devices, beamforming, networking, the integration of communications and sensing, and experimental testbeds.
no code implementations • 1 Jun 2023 • Marouan Mizmizi, Dario Tagliaferri, Marco Di Renzo, Umberto Spagnolini
Space-time modulated metasurfaces (STMMs) are a recently proposed generalization of reconfigurable intelligent surfaces, which include a proper time-varying phase at the metasurface elements, enabling higher flexibility and control of the reflected signals.
no code implementations • 13 Apr 2023 • Juan Carlos Ruiz-Sicilia, Marco Di Renzo, Merouane Debbah, H. Vincent Poor
The synergy of metasurface-based holographic surfaces (HoloS) and reconfigurable intelligent surfaces (RIS) is considered a key aspect for future communication networks.
no code implementations • 6 Mar 2023 • Robert K. Fotock, Alessio Zappone, Marco Di Renzo
This work addresses the issue of energy efficiency maximization in a multi-user network aided by reconfigurable intelligent surface (RIS) with global reflection capabilities.
no code implementations • 3 Mar 2023 • Yongqing Xu, Yong Li, J. Andrew Zhang, Marco Di Renzo, Tony Q. S. Quek
However, due to multiple performance metrics used for communication and sensing, the limited degrees-of-freedom (DoF) in optimizing ISAC systems poses a challenge.
no code implementations • 28 Feb 2023 • Cheng-Xiang Wang, Xiaohu You, Xiqi Gao, Xiuming Zhu, Zixin Li, Chuan Zhang, Haiming Wang, Yongming Huang, Yunfei Chen, Harald Haas, John S. Thompson, Erik G. Larsson, Marco Di Renzo, Wen Tong, Peiying Zhu, Xuemin, Shen, H. Vincent Poor, Lajos Hanzo
A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc.
no code implementations • 9 Feb 2023 • Sheng Hong, Minghui Li, Cunhua Pan, Marco Di Renzo, Wei zhang, Lajos Hanzo
A two-step positioning scheme is exploited, where the channel parameters are first acquired, and the position-related parameters are then estimated.
no code implementations • 8 Feb 2023 • Mengbing Liu, Chongwen Huang, Marco Di Renzo, Merouane Debbah, Chau Yuen
Reconfigurable intelligent surface (RIS) is considered as a promising solution for next-generation wireless communication networks due to a variety of merits, e. g., customizing the communication environment.
no code implementations • 4 Feb 2023 • Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Dimitrios Pliatsios, Konstantinos Ntontin, Panagiotis Sarigiannidis, Symeon Chatzinotas, Marco Di Renzo
Finally, insights that arise from the presented analysis are summarized and used to highlight the most important future directions for localization in 6G wireless systems.
no code implementations • 10 Dec 2022 • Alexandros-Apostolos A. Boulogeorgos, Angeliki Alexiou, Marco Di Renzo
Reconfigurable intelligent surface (RIS)-assisted unmanned areal vehicles (UAV) communications have been identified as a key enabler of a number of next-generation applications.
no code implementations • 6 Sep 2022 • Fan Jiang, Andrea Abrardo, Kamran Keykhoshravi, Henk Wymeersch, Davide Dardari, Marco Di Renzo
Reconfigurable intelligent surfaces (RISs) have tremendous potential to boost communication performance, especially when the line-of-sight (LOS) path between the user equipment (UE) and base station (BS) is blocked.
1 code implementation • 25 Aug 2022 • Vaibhav Kumar, Rui Zhang, Marco Di Renzo, Le-Nam Tran
In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phase-shifts of the intelligent reflecting surface (IRS) / reconfigurable intelligent surface (RIS) to minimize the transmit power, subject to quality-of-service constraints at individual users in an IRS-assisted multiuser multiple-input single-output downlink communication system.
no code implementations • 17 Aug 2022 • Alexandros-Apostolos A. Boulogeorgos, Edwin Yaqub, Rachana Desai, Tachporn Sanguanpuak, Nikos Katzouris, Fotis Lazarakis, Angeliki Alexiou, Marco Di Renzo
In more detail, a fast and centralized joint user association, radio resource allocation, and blockage avoidance by means of a novel metaheuristic-machine learning framework is documented, that maximizes the THz networks performance, while minimizing the association latency by approximately three orders of magnitude.
no code implementations • 16 Aug 2022 • Guoliang Li, Shuai Wang, Kejiang Ye, Miaowen Wen, Derrick Wing Kwan Ng, Marco Di Renzo
Integrated sensing and communication (ISAC) represents a paradigm shift, where previously competing wireless transmissions are jointly designed to operate in harmony via the shared use of the hardware platform for improving the spectral and energy efficiencies.
no code implementations • 13 Aug 2022 • Zhichao Shao, Xiaojun Yuan, Wei zhang, Marco Di Renzo
A grid based parametric model is constructed and the joint estimation problem is formulated as a compressive sensing problem.
no code implementations • 27 Jun 2022 • Abdelhamed Mohamed, Nemanja Stefan Perović, Marco Di Renzo
In this paper, we consider intelligent omni-surfaces (IOSs), which are capable of simultaneously reflecting and refracting electromagnetic waves.
no code implementations • 14 Jun 2022 • Nour Awarkeh, Dinh-Thuy Phan-Huy, Marco Di Renzo
However, in some cases, where the BS serves the same user for a long period, and in some propagation conditions, such systems reduce their transmit power to avoid creating unwanted regions of electromagnetic field exposure exceeding the regulatory threshold, beyond the circle around the BS that limits the distance between people and the BS antenna.
no code implementations • 14 Jun 2022 • Nour Awarkeh, Dinh-Thuy Phan-Huy, Raphael Visoz, Marco Di Renzo
In some propagation conditions, when the base station serves the same target user equipment for a long period, it reduces the transmit power (and degrades the received power) to avoid creating high exposure regions located in the vicinity of the antenna and concentrated in few directions (corresponding to the best propagation paths between the antenna and the receiver).
no code implementations • 13 Feb 2022 • Alexandros-Apostolos A. Boulogeorgos, Nestor Chatzidiamantis, Harilaos G. Sandalidis, Angeliki Alexiou, Marco Di Renzo
In this paper, we introduce a theoretical framework for analyzing the performance of multi-reconfigurable intelligence surface (RIS) empowered terahertz (THz) wireless systems subject to turbulence and stochastic beam misalignment.
no code implementations • 28 Jan 2022 • Alexandros-Apostolos A. Boulogeorgos, Angeliki Alexiou, Marco Di Renzo
In this paper, we analyze the performance of a reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV) wireless system that is affected by mixture-gamma small-scale fading, stochastic disorientation, and misalignment, as well as transceivers hardware imperfections.
no code implementations • 11 Dec 2021 • Cunhua Pan, Gui Zhou, Kangda Zhi, Sheng Hong, Tuo Wu, Yijin Pan, Hong Ren, Marco Di Renzo, A. Lee Swindlehurst, Rui Zhang, Angela Yingjun Zhang
In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying on the design of various sophisticated transmission/reception schemes.
no code implementations • 2 Nov 2021 • Romain Fara, Dinh-Thuy Phan-Huy, Abdelwaheb Ourir, Yvan Kokar, Jean-Christophe Prévotet, Maryline Hélard, Marco Di Renzo, Julien de Rosny
In this paper, we propose a polarization-based reconfigurable antenna in order to improve the robustness of the tag-to-reader link against the source-to-reader direct interference.
no code implementations • 2 Nov 2021 • Romain Fara, Nada Bel-Haj-Maati, Dinh-Thuy Phan-Huy, Nadine Malhouroux, Marco Di Renzo
A mobile device transmits a signal that is backscattered by a tag and received by the reader.
no code implementations • 2 Nov 2021 • Romain Fara, Dinh-Thuy Phan-Huy, Abdelwaheb Ourir, Marco Di Renzo, Julien de Rosny
In this paper, for the first time, we propose to exploit a "polarization reconfigurable" antenna to improve robustness of the tag-to-reader link against the source-to-reader direct interference.
no code implementations • 3 Sep 2021 • Bo Yang, Xuelin Cao, Chongwen Huang, Yong Liang Guan, Chau Yuen, Marco Di Renzo, Dusit Niyato, Merouane Debbah, Lajos Hanzo
In the sixth-generation (6G) era, emerging large-scale computing based applications (for example processing enormous amounts of images in real-time in autonomous driving) tend to lead to excessive energy consumption for the end users, whose devices are usually energy-constrained.
1 code implementation • 27 Jul 2021 • Jiguang He, Henk Wymeersch, Marco Di Renzo, Markku Juntti
Inspired by the remarkable learning and prediction performance of deep neural networks (DNNs), we apply one special type of DNN framework, known as model-driven deep unfolding neural network, to reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) single-input multiple-output (SIMO) systems.
no code implementations • 27 Jul 2021 • Xiaonan Liu, Yansha Deng, Chong Han, Marco Di Renzo
This high data rate over short transmission distances may be achieved via abundant bandwidth in the terahertz (THz) band.
no code implementations • 29 Jun 2021 • Alexandros-Apostolos A. Boulogeorgos, Nestor Chatzidiamantis, Harilaos G. Sandalidis, Angeliki Alexiou, Marco Di Renzo
Building upon the derived analytical expressions, we present novel closed-form formulas that quantify the joint impact of turbulence and misalignment on the outage performance for two scenarios of high interest namely cascaded multi-RIS-empowered free space optics (FSO) and terahertz (THz) wireless systems.
no code implementations • 25 May 2021 • Romain Fara, Philippe Ratajczak, Dinh-Thuy Phan Huy, Abdelwaheb Ourir, Marco Di Renzo, Julien de Rosny
On the other hand, ambient backscatter communications (AmBC) is another promising technology that is tailored for addressing the energy efficiency requirements for the Internet of Things (IoT).
no code implementations • 22 Apr 2021 • Xisuo Ma, Zhen Gao, Feifei Gao, Marco Di Renzo
To reduce the uplink pilot overhead for estimating the high-dimensional channels from a limited number of radio frequency (RF) chains at the base station (BS), we propose to jointly train the phase shift network and the channel estimator as an auto-encoder.
no code implementations • 15 Mar 2021 • Romain Fara, Dinh-Thuy Phan-Huy, Philippe Ratajczak, Abdelwaheb Ourir, Marco Di Renzo, Julien de Rosny
On the other hand, in an ambient backscatter system, a device, named tag, communicates towards a reader by backscattering the waves of an ambient source (such as a TV tower).
no code implementations • 2 Mar 2021 • Bo Yang, Xuelin Cao, Chongwen Huang, Chau Yuen, Lijun Qian, Marco Di Renzo
Reconfigurable intelligent surface (RIS) has become a promising technology for enhancing the reliability of wireless communications, which is capable of reflecting the desired signals through appropriate phase shifts.
no code implementations • 21 Jan 2021 • Wankai Tang, Xiangyu Chen, Ming Zheng Chen, Jun Yan Dai, Yu Han, Marco Di Renzo, Shi Jin, Qiang Cheng, Tie Jun Cui
The refined model gives more accurate estimates of the path loss of RISs comprised of unit cells with a deep sub-wavelength size.
no code implementations • 18 Jan 2021 • Thang X. Vu, Symeon Chatzinotas, Van-Dinh Nguyen, Dinh Thai Hoang, Diep N. Nguyen, Marco Di Renzo, Bjorn Ottersten
We investigate the performance of multi-user multiple-antenna downlink systems in which a BS serves multiple users via a shared wireless medium.
Information Theory Information Theory
no code implementations • 9 Dec 2020 • Nemanja Stefan Perović, Le-Nam Tran, Marco Di Renzo, Mark F. Flanagan
The main difficulty concerning optimizing the mutual information (MI) in reconfigurable intelligent surface (RIS)-aided communication systems with discrete signaling is the inability to formulate this optimization problem in an analytically tractable manner.
Information Theory Information Theory
no code implementations • 27 Nov 2020 • Yue Xiu, Jun Zhao, Ertugrul Basar, Marco Di Renzo, Wei Sun, Guan Gui, Ning Wei
In this letter, we investigate the uplink of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) multi-user system.
no code implementations • 25 Nov 2020 • Jingzhi Hu, Hongliang Zhang, Kaigui Bian, Marco Di Renzo, Zhu Han, Lingyang Song
To tackle this challenge, we formulate an optimization problem for minimizing the cross-entropy loss of the sensing outcome, and propose a deep reinforcement learning algorithm to jointly compute the optimal beamformer patterns and the mapping of the received signals.
no code implementations • 9 Nov 2020 • Cunhua Pan, Hong Ren, Kezhi Wang, Jonas Florentin Kolb, Maged Elkashlan, Ming Chen, Marco Di Renzo, Yang Hao, Jiangzhou Wang, A. Lee Swindlehurst, Xiaohu You, Lajos Hanzo
Reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRSs), are regarded as one of the most promising and revolutionizing techniques for enhancing the spectrum and/or energy efficiency of wireless systems.
no code implementations • 2 Nov 2020 • Shuhang Zhang, Hongliang Zhang, Boya Di, Yunhua Tan, Marco Di Renzo, Zhu Han, H. Vincent Poor, Lingyang Song
Intelligent reflecting surface (IRS), which is capable to adjust propagation conditions by controlling phase shifts of the reflected waves that impinge on the surface, has been widely analyzed for enhancing the performance of wireless systems.
no code implementations • 21 Sep 2020 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Maged Elkashlan, Marco Di Renzo
To enhance the robustness of hybrid analog-digital beamforming in the presence of random blockages, we formulate a stochastic optimization problem based on the minimization of the sum outage probability.
no code implementations • 22 Jul 2020 • Zhangjie Peng, Tianshu Li, Cunhua Pan, Hong Ren, Wei Xu, Marco Di Renzo
Simulation results verify the correctness of the obtained results and show that the proposed GA method has almost the same performance as the globally optimal solution.
no code implementations • 11 Jul 2020 • Yue Xiu, Jun Zhao, Wei Sun, Marco Di Renzo, Guan Gui, Zhongpei Zhang, Ning Wei
Then, we solve the power allocation problem under fixed phase shifts of the RIS and hybrid beamforming.
no code implementations • 7 Jul 2020 • Yuanwei Liu, Xiao Liu, Xidong Mu, Tianwei Hou, Jiaqi Xu, Marco Di Renzo, Naofal Al-Dhahir
In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies.
no code implementations • 30 Jun 2020 • Imene Trigui, Sofiene Affes, Marco Di Renzo, Dushantha Nalin K. Jayakody
In this paper, we develop an innovative approach to quantitatively characterize the performance of ultra-dense wireless networks in a plethora of propagation environments.
2 code implementations • 3 Jun 2020 • Shicong Liu, Zhen Gao, Jun Zhang, Marco Di Renzo, Mohamed-Slim Alouini
Integrating large intelligent reflecting surfaces (IRS) into millimeter-wave (mmWave) massive multi-input-multi-ouput (MIMO) has been a promising approach for improved coverage and throughput.
no code implementations • 23 Feb 2020 • Haris Gacanin, Marco Di Renzo
We introduce "Wireless 2. 0": The future generation of wireless communication networks, where the radio environment becomes controllable, programmable, and intelligent by leveraging the emerging technologies of reconfigurable metasurfaces and artificial intelligence (AI).
no code implementations • 7 Dec 2019 • Huimei Han, Jun Zhao, Zehui Xiong, Dusit Niyato, Wenchao Zhai, Marco Di Renzo, Quoc-Viet Pham, Weidang Lu
Our goalis to minimize the transmit power at the BS by jointly designing the transmit beamforming at the BSand the phase shifts of the passive elements at the RIS.
no code implementations • 27 Nov 2019 • Chongwen Huang, Sha Hu, George C. Alexandropoulos, Alessio Zappone, Chau Yuen, Rui Zhang, Marco Di Renzo, Mérouane Debbah
Future wireless networks are expected to evolve towards an intelligent and software reconfigurable paradigm enabling ubiquitous communications between humans and mobile devices.
no code implementations • 14 Nov 2019 • Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Marco Di Renzo, Arumugam Nallanathan
In this paper, we study the worst-case robust beamforming design for an IRS-aided multiuser multiple-input single-output (MU-MISO) system under the assumption of imperfect CSI.
no code implementations • 13 Nov 2019 • Wankai Tang, Ming Zheng Chen, Xiangyu Chen, Jun Yan Dai, Yu Han, Marco Di Renzo, Yong Zeng, Shi Jin, Qiang Cheng, Tie Jun Cui
The measurement results match well with the modeling results, thus validating the proposed free-space path loss models for RIS, which may pave the way for further theoretical studies and practical applications in this field.