Messaoud Ahmed Ouameur, Lê Dương Tuấn Anh, Daniel Massicotte, Gwanggil Jeon, Felipe Augusto Pereira de Figueiredo
{"title":"ris辅助OFDM通信的对抗强盗方法。","authors":"Messaoud Ahmed Ouameur, Lê Dương Tuấn Anh, Daniel Massicotte, Gwanggil Jeon, Felipe Augusto Pereira de Figueiredo","doi":"10.1186/s13638-022-02184-6","DOIUrl":null,"url":null,"abstract":"<p><p>To assist sixth-generation wireless systems in the management of a wide variety of services, ranging from mission-critical services to safety-critical tasks, key physical layer technologies such as reconfigurable intelligent surfaces (RISs) are proposed. Even though RISs are already used in various scenarios to enable the implementation of smart radio environments, they still face challenges with regard to real-time operation. Specifically, high dimensional fully passive RISs typically need costly system overhead for channel estimation. This paper, however, investigates a semi-passive RIS that requires a very low number of active elements, wherein only two pilots are required per channel coherence time. While in its infant stage, the application of deep learning (DL) tools shows promise in enabling feasible solutions. We propose two low-training overhead and energy-efficient adversarial bandit-based schemes with outstanding performance gains when compared to DL-based reflection beamforming reference methods. The resulting deep learning models are discussed using state-of-the-art model quality prediction trends.</p>","PeriodicalId":12040,"journal":{"name":"EURASIP Journal on Wireless Communications and Networking","volume":" ","pages":"111"},"PeriodicalIF":2.3000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9672029/pdf/","citationCount":"0","resultStr":"{\"title\":\"Adversarial bandit approach for RIS-aided OFDM communication.\",\"authors\":\"Messaoud Ahmed Ouameur, Lê Dương Tuấn Anh, Daniel Massicotte, Gwanggil Jeon, Felipe Augusto Pereira de Figueiredo\",\"doi\":\"10.1186/s13638-022-02184-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>To assist sixth-generation wireless systems in the management of a wide variety of services, ranging from mission-critical services to safety-critical tasks, key physical layer technologies such as reconfigurable intelligent surfaces (RISs) are proposed. Even though RISs are already used in various scenarios to enable the implementation of smart radio environments, they still face challenges with regard to real-time operation. Specifically, high dimensional fully passive RISs typically need costly system overhead for channel estimation. This paper, however, investigates a semi-passive RIS that requires a very low number of active elements, wherein only two pilots are required per channel coherence time. While in its infant stage, the application of deep learning (DL) tools shows promise in enabling feasible solutions. We propose two low-training overhead and energy-efficient adversarial bandit-based schemes with outstanding performance gains when compared to DL-based reflection beamforming reference methods. The resulting deep learning models are discussed using state-of-the-art model quality prediction trends.</p>\",\"PeriodicalId\":12040,\"journal\":{\"name\":\"EURASIP Journal on Wireless Communications and Networking\",\"volume\":\" \",\"pages\":\"111\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9672029/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EURASIP Journal on Wireless Communications and Networking\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1186/s13638-022-02184-6\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/11/17 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EURASIP Journal on Wireless Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1186/s13638-022-02184-6","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/11/17 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Adversarial bandit approach for RIS-aided OFDM communication.
To assist sixth-generation wireless systems in the management of a wide variety of services, ranging from mission-critical services to safety-critical tasks, key physical layer technologies such as reconfigurable intelligent surfaces (RISs) are proposed. Even though RISs are already used in various scenarios to enable the implementation of smart radio environments, they still face challenges with regard to real-time operation. Specifically, high dimensional fully passive RISs typically need costly system overhead for channel estimation. This paper, however, investigates a semi-passive RIS that requires a very low number of active elements, wherein only two pilots are required per channel coherence time. While in its infant stage, the application of deep learning (DL) tools shows promise in enabling feasible solutions. We propose two low-training overhead and energy-efficient adversarial bandit-based schemes with outstanding performance gains when compared to DL-based reflection beamforming reference methods. The resulting deep learning models are discussed using state-of-the-art model quality prediction trends.
期刊介绍:
The overall aim of the EURASIP Journal on Wireless Communications and Networking (EURASIP JWCN) is to bring together science and applications of wireless communications and networking technologies with emphasis on signal processing techniques and tools. It is directed at both practicing engineers and academic researchers. EURASIP Journal on Wireless Communications and Networking will highlight the continued growth and new challenges in wireless technology, for both application development and basic research. Articles should emphasize original results relating to the theory and/or applications of wireless communications and networking. Review articles, especially those emphasizing multidisciplinary views of communications and networking, are also welcome. EURASIP Journal on Wireless Communications and Networking employs a paperless, electronic submission and evaluation system to promote a rapid turnaround in the peer-review process.
The journal is an Open Access journal since 2004.