PMID- 36411764
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20221123
IS  - 1687-1472 (Print)
IS  - 1687-1499 (Electronic)
IS  - 1687-1472 (Linking)
VI  - 2022
IP  - 1
DP  - 2022
TI  - Adversarial bandit approach for RIS-aided OFDM communication.
PG  - 111
LID - 10.1186/s13638-022-02184-6 [doi]
LID - 111
AB  - 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.
CI  - (c) The Author(s) 2022.
FAU - Ahmed Ouameur, Messaoud
AU  - Ahmed Ouameur M
AD  - Department of Electrical and Computer Engineering, Universite du Quebec a 
      Trois-Rivieres, 3351 Boul des Forges, Trois-Rivieres, QC G9A 5H7 Canada. GRID: 
      grid.265703.5. ISNI: 0000 0001 2197 8284
FAU - Anh, Le Duong Tuan
AU  - Anh LDT
AD  - Department of Electrical and Computer Engineering, Universite du Quebec a 
      Trois-Rivieres, 3351 Boul des Forges, Trois-Rivieres, QC G9A 5H7 Canada. GRID: 
      grid.265703.5. ISNI: 0000 0001 2197 8284
AD  - Faculty of Information Technology, VNU-HCM University of Science, Ho Chi Minh 
      City, Vietnam. GRID: grid.454160.2. ISNI: 0000 0004 0642 8526
FAU - Massicotte, Daniel
AU  - Massicotte D
AUID- ORCID: 0000-0002-7807-7919
AD  - Department of Electrical and Computer Engineering, Universite du Quebec a 
      Trois-Rivieres, 3351 Boul des Forges, Trois-Rivieres, QC G9A 5H7 Canada. GRID: 
      grid.265703.5. ISNI: 0000 0001 2197 8284
FAU - Jeon, Gwanggil
AU  - Jeon G
AD  - Department of Embedded Systems Engineering, College of Information Technology, 
      Incheon National University, Incheon, South Korea. GRID: grid.412977.e. ISNI: 
      0000 0004 0532 7395
FAU - de Figueiredo, Felipe Augusto Pereira
AU  - de Figueiredo FAP
AD  - National Institute of Telecommunications, Santa Rita Do Sapucai, Minas Gerais 
      Brazil. GRID: grid.454284.b. ISNI: 0000 0001 0753 533X
LA  - eng
PT  - Journal Article
PT  - Review
DEP - 20221117
PL  - Germany
TA  - EURASIP J Wirel Commun Netw
JT  - EURASIP journal on wireless communications and networking
JID - 101637335
PMC - PMC9672029
OTO - NOTNLM
OT  - Adversarial bandit
OT  - Deep learning
OT  - Exponential-weight algorithm for exploration and exploitation
OT  - Follow the perturbed leader (FPL)
OT  - Machine learning
OT  - Reconfigurable intelligent surfaces
OT  - Reflection beamforming prediction
OT  - Sixth-generation (6G) wireless systems
COIS- Competing interestsThe authors declare that they have no competing interests.
EDAT- 2022/11/23 06:00
MHDA- 2022/11/23 06:01
PMCR- 2022/11/17
CRDT- 2022/11/22 01:43
PHST- 2022/01/10 00:00 [received]
PHST- 2022/09/27 00:00 [accepted]
PHST- 2022/11/22 01:43 [entrez]
PHST- 2022/11/23 06:00 [pubmed]
PHST- 2022/11/23 06:01 [medline]
PHST- 2022/11/17 00:00 [pmc-release]
AID - 2184 [pii]
AID - 10.1186/s13638-022-02184-6 [doi]
PST - ppublish
SO  - EURASIP J Wirel Commun Netw. 2022;2022(1):111. doi: 10.1186/s13638-022-02184-6. 
      Epub 2022 Nov 17.