Dimitrios Tyrovolas, Nikos A. Mitsiou, Thomas G. Boufikos, Prodromos-Vasileios Mekikis, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, Sotiris Ioannidis, Christos K. Liaskos, George K. Karagiannidis
{"title":"Energy-aware Trajectory Optimization for UAV-mounted RIS and Full-duplex Relay","authors":"Dimitrios Tyrovolas, Nikos A. Mitsiou, Thomas G. Boufikos, Prodromos-Vasileios Mekikis, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, Sotiris Ioannidis, Christos K. Liaskos, George K. Karagiannidis","doi":"arxiv-2401.12107","DOIUrl":null,"url":null,"abstract":"In the evolving landscape of sixth-generation (6G) wireless networks,\nunmanned aerial vehicles (UAVs) have emerged as transformative tools for\ndynamic and adaptive connectivity. However, dynamically adjusting their\nposition to offer favorable communication channels introduces operational\nchallenges in terms of energy consumption, especially when integrating advanced\ncommunication technologies like reconfigurable intelligent surfaces (RISs) and\nfull-duplex relays (FDRs). To this end, by recognizing the pivotal role of UAV\nmobility, the paper introduces an energy-aware trajectory design for\nUAV-mounted RISs and UAV-mounted FDRs using the decode and forward (DF)\nprotocol, aiming to maximize the network minimum rate and enhance user\nfairness, while taking into consideration the available on-board energy.\nSpecifically, this work highlights their distinct energy consumption\ncharacteristics and their associated integration challenges by developing\nappropriate energy consumption models for both UAV-mounted RISs and FDRs that\ncapture the intricate relationship between key factors such as weight, and\ntheir operational characteristics. Furthermore, a joint time-division multiple\naccess (TDMA) user scheduling-UAV trajectory optimization problem is\nformulated, considering the power dynamics of both systems, while assuring that\nthe UAV energy is not depleted mid-air. Finally, simulation results underscore\nthe importance of energy considerations in determining the optimal trajectory\nand scheduling and provide insights into the performance comparison of\nUAV-mounted RISs and FDRs in UAV-assisted wireless networks.","PeriodicalId":501433,"journal":{"name":"arXiv - CS - Information Theory","volume":"16 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Information Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2401.12107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the evolving landscape of sixth-generation (6G) wireless networks,
unmanned aerial vehicles (UAVs) have emerged as transformative tools for
dynamic and adaptive connectivity. However, dynamically adjusting their
position to offer favorable communication channels introduces operational
challenges in terms of energy consumption, especially when integrating advanced
communication technologies like reconfigurable intelligent surfaces (RISs) and
full-duplex relays (FDRs). To this end, by recognizing the pivotal role of UAV
mobility, the paper introduces an energy-aware trajectory design for
UAV-mounted RISs and UAV-mounted FDRs using the decode and forward (DF)
protocol, aiming to maximize the network minimum rate and enhance user
fairness, while taking into consideration the available on-board energy.
Specifically, this work highlights their distinct energy consumption
characteristics and their associated integration challenges by developing
appropriate energy consumption models for both UAV-mounted RISs and FDRs that
capture the intricate relationship between key factors such as weight, and
their operational characteristics. Furthermore, a joint time-division multiple
access (TDMA) user scheduling-UAV trajectory optimization problem is
formulated, considering the power dynamics of both systems, while assuring that
the UAV energy is not depleted mid-air. Finally, simulation results underscore
the importance of energy considerations in determining the optimal trajectory
and scheduling and provide insights into the performance comparison of
UAV-mounted RISs and FDRs in UAV-assisted wireless networks.