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Radar Aided 6G Beam Prediction: Deep Learning Algorithms and Real-World Demonstration [article]

Umut Demirhan, Ahmed Alkhateeb
2021 arXiv   pre-print
This paper presents the first machine learning based real-world demonstration for radar-aided beam prediction in a practical vehicular communication scenario.  ...  The proposed radar-aided beam prediction solutions are evaluated using the large-scale real-world dataset DeepSense 6G, which comprises co-existing mmWave beam training and radar measurements.  ...  In this work, we develop machine learning based algorithms for radar-aided mmWave beam prediction and demonstrate their performance using a real-world dataset in a realistic vehicular communication scenario  ... 
arXiv:2111.09676v1 fatcat:wklzbrjirbeu3jeccuxiwqvgmy

Integrated Sensing and Communication for 6G: Ten Key Machine Learning Roles [article]

Umut Demirhan, Ahmed Alkhateeb
2022 arXiv   pre-print
The article also presents real-world results for some of these machine learning roles based on the large-scale real-world dataset DeepSense 6G, which could be adopted in investigating a wide range of integrated  ...  This article focuses on ten key machine learning roles for joint sensing and communication, sensing-aided communication, and communication-aided sensing systems, explains why and how machine learning can  ...  Real-World Evaluation: A demonstration of the radar aided blockage prediction application using a large-scale realworld dataset was first presented in [4] .  ... 
arXiv:2208.02157v2 fatcat:obypfcwomzdxfbrw6w64pq3xsm

Introduction to the Special Issue on Tensor Decomposition for Signal Processing and Machine Learning

Hongyang Chen, Sergiy A. Vorobyov, Hing Cheung So, Fauzia Ahmad, Fatih Porikli
2021 IEEE Journal on Selected Topics in Signal Processing  
An end-to-end compression algorithm is also presented that includes quantization and encoding, facilitating its direct application in real-world problems.  ...  and comparable results to deep Q-learning.  ... 
doi:10.1109/jstsp.2021.3065184 fatcat:qbvihejwkfaa5hoztety77pnwi

AI-Aided Integrated Terrestrial and Non-Terrestrial 6G Solutions for Sustainable Maritime Networking [article]

Salwa Saafi, Olga Vikhrova, Gábor Fodor, Jiri Hosek, Sergey Andreev
2022 arXiv   pre-print
The key enablers in these processes are always-available connectivity and content delivery services, which can not only aid shipping companies in improving their operational efficiency and reducing carbon  ...  To cope with the increased complexity of managing these integrated systems, this article advocates the use of artificial intelligence and machine learning-based approaches to meet the service requirements  ...  This work was also supported by the Academy of Finland (projects Emc2-ML, RADIANT, and IDEA-MILL). G. Fodor was partially supported by the European Celtic project 6G-SKY with project ID C2021/1-9.  ... 
arXiv:2201.06947v2 fatcat:u7owlfpmz5f43jlbkvh2ztfvti

A Survey of Simultaneous Localization and Mapping with an Envision in 6G Wireless Networks [article]

Baichuan Huang, Jun Zhao, Jingbin Liu
2020 arXiv   pre-print
For Lidar or visual SLAM, the survey illustrates the basic type and product of sensors, open source system in sort and history, deep learning embedded, the challenge and future.  ...  The open question and forward thinking with an envision in 6G wireless networks end the paper.  ...  world and M8 is the mechanical Lidar.  ... 
arXiv:1909.05214v4 fatcat:itnluvkewfd6fel7x65wdgig3e

Going Beyond RF: How AI-enabled Multimodal Beamforming will Shape the NextG Standard [article]

Debashri Roy, Batool Salehi, Stella Banou, Subhramoy Mohanti, Guillem Reus-Muns, Mauro Belgiovine, Prashant Ganesh, Carlos Bocanegra, Chris Dick, Kaushik Chowdhury
2022 arXiv   pre-print
The survey describes relevant deep learning architectures for multimodal beamforming, identifies computational challenges and the role of edge computing in this process, dataset generation tools, and finally  ...  This so called idea of multimodal beamforming will require deep learning based fusion techniques, which will serve to augment the current RF-only and classical signal processing methods that do not scale  ...  With the recent progress in computer vision and deep learning, powerful algorithms are now available that can be used for processing the images in real time for beamforming.  ... 
arXiv:2203.16706v1 fatcat:44pger2flveondbtachzhcdgam

Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey [article]

M. Mahdi Azari, Sourabh Solanki, Symeon Chatzinotas, Oltjon Kodheli, Hazem Sallouha, Achiel Colpaert, Jesus Fabian Mendoza Montoya, Sofie Pollin, Alireza Haqiqatnejad, Arsham Mostaani, Eva Lagunas, Bjorn Ottersten
2022 arXiv   pre-print
Our survey further includes the major progress and outcomes from academic research as well as industrial efforts representing the main industrial trends, field trials, and prototyping towards the 6G networks  ...  This article comprehensively surveys the evolution of NTNs highlighting their relevance to 5G networks and essentially, how it will play a pivotal role in the development of 6G ecosystem.  ...  Same approach in path loss prediction using deep learning is adopted in [243] , [244] .  ... 
arXiv:2107.06881v2 fatcat:ap7uchcpqzbchohcn3pnrlubzm

6G for Vehicle-to-Everything (V2X) Communications: Enabling Technologies, Challenges, and Opportunities [article]

Md. Noor-A-Rahim, Zilong Liu, Haeyoung Lee, M. Omar Khyam, Jianhua He, Dirk Pesch, Klaus Moessner, Walid Saad, H. Vincent Poor
2022 arXiv   pre-print
To this end, we provide an overview on the recent advances of machine learning in 6G vehicular networks.  ...  In this article, we outline a series of key enabling technologies from a range of domains, such as new materials, algorithms, and system architectures.  ...  Moreover, extensive real-world experiments are required to demonstrate the effectiveness of BCVs, as most of the existing works on BCV has been verified through simulation only. D.  ... 
arXiv:2012.07753v2 fatcat:u5edqsewbzgthlkgc3nooqmdo4

A Comprehensive Survey of 6G Wireless Communications [article]

Yang Zhao, Wenchao Zhai, Jun Zhao, Tinghao Zhang, Sumei Sun, Dusit Niyato, Kwok-Yan Lam
2021 arXiv   pre-print
Finally, we predict real-world applications built on the technologies and features of 6G; for example, smart healthcare, smart city, and smart manufacturing will be implemented by taking advantage of AI  ...  First, we give an overview of 6G from perspectives of technologies, security and privacy, and applications.  ...  [153] believe that IRSs will be utilized in 6G, because they predict that future's wireless networks will serve as an intelligent platform connecting the physical world and the digital world seamlessly  ... 
arXiv:2101.03889v2 fatcat:35sfasu4bbgttg3cnsfzp62oda

Explainable AI for B5G/6G: Technical Aspects, Use Cases, and Research Challenges [article]

Shen Wang, M.Atif Qureshi, Luis Miralles-Pechuaán, Thien Huynh-The, Thippa Reddy Gadekallu, Madhusanka Liyanage
2021 arXiv   pre-print
Moreover, we summarised the lessons learned from the recent attempts and outlined important research challenges in applying XAI for building 6G systems.  ...  This survey paper highlights the need for XAI towards the upcoming 6G age in every aspect, including 6G technologies (e.g., intelligent radio, zero-touch network management) and 6G use cases (e.g., industry  ...  deep-learning based 6G autonomy.  ... 
arXiv:2112.04698v1 fatcat:y7ss4opmrjbsbjm3ip2vgkkgky

Evolution of Wireless Communication to 6G: Potential Applications and Research Directions

Muhammad Zeeshan Asghar, Shafique Ahmed Memon, Jyri Hämäläinen
2022 Sustainability  
This study intends to see the world beyond 5G with the transition to 6G assuming the lead as future wireless communication technology.  ...  This article explores main impediments and challenges that the 5G–6G transition may face in achieving these greater ideals.  ...  DL-based "radar-aided beam prediction" approaches for mmWave/sub-THz .  ... 
doi:10.3390/su14106356 fatcat:uh5hg5jzljcwbm4ygesghgfbhq

ViWi Vision-Aided mmWave Beam Tracking: Dataset, Task, and Baseline Solutions [article]

Muhammad Alrabeiah, Jayden Booth, Andrew Hredzak, Ahmed Alkhateeb
2020 arXiv   pre-print
Vision-aided wireless communication is motivated by the recent advances in deep learning and computer vision as well as the increasing dependence on line-of-sight links in millimeter wave (mmWave) and  ...  By leveraging vision, this new research direction enables an interesting set of new capabilities such as vision-aided mmWave beam and blockage prediction, proactive hand-off, and resource allocation among  ...  Such algorithms in machine learning could be described as a prediction function f Θ (S) parameterized by a set of parameters Θ.  ... 
arXiv:2002.02445v3 fatcat:esojrxoyhbcq5f4ekwwcudsp2i

6G Wireless Communications Networks: A Comprehensive Survey

Muntadher Alsabah, Marwah Abdulrazzaq Naser, Basheera M. Mahmmod, Sadiq H. Abdulhussain, Mohammad R. Eissa, Ahmed Al-Baidhani, Nor K. Noordin, Sadiq M. Sait, Khaled A. Al-Utaibi, Fazirul Hashim
2021 IEEE Access  
Therefore, it is essential to provide a prospective vision of the 6G and the key enabling technologies for realizing future networks.  ...  To this end, this paper presents a comprehensive review/survey of the future evolution of 6G networks.  ...  Such applications would use a computer-simulated platform with reality experience and create a virtual world that looks exactly like the real world.  ... 
doi:10.1109/access.2021.3124812 fatcat:qomuon5t4remrfoxzjksauto6q

6G Ecosystem: Current Status and Future Perspective

Jagadeesha R Bhat, Salman A. AlQahtani
2021 IEEE Access  
A comparison of 5G and 6G using support for verticals (a) 5G and (b) 6G.  ...  Further, we highlight the key requirements of 6G based on contemporary research such as UN sustainability goals, business model, edge intelligence, digital divide, and the trends in machine learning for  ...  Deep learning is one of the promising methods for predicting the appropriate coding length by learning the channel codeword length.  ... 
doi:10.1109/access.2021.3054833 fatcat:d5pkupvwobh45dp2k3jr67yrgu

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mohammed Najah Mahdi, Abdul Rahim Ahmad, Qais Saif Qassim, Hayder Natiq, Mohammed Ahmed Subhi, Moamin Mahmoud
2021 Applied Sciences  
This work presents a thorough review of 370 papers on the application of energy, IoT and machine learning in 5G and 6G from three major libraries: Web of Science, ACM Digital Library, and IEEE Explore.  ...  In this work, we have considered the applications of three of the highly demanding domains, namely: energy, Internet-of-Things (IoT) and machine learning.  ...  ML Proposed the first online learning method designed to aid beam selection in mmWave vehicular systems. in particular, see this as a multi-armed bandit problem.  ... 
doi:10.3390/app11178117 fatcat:4vtzn5cae5eqtnzobtvzysi6mm
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