{"title":"在 SCMA 辅助无人机系统中实现总速率最大化的资源管理","authors":"Saumya Chaturvedi , Vivek Ashok Bohara , Zilong Liu , Anand Srivastava , Pei Xiao","doi":"10.1016/j.vehcom.2023.100714","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>This work presents a resource management framework for optimizing the sum-rate in a sparse code multiple access (SCMA)-assisted UAV<span><span> downlink system. We formulate two optimization problems for maximizing the overall sum-rate: the first problem addresses UAV 3D deployment and trajectory optimization with energy constraints, while the second focuses on optimizing SCMA </span>subcarrier and </span></span>power allocation<span><span> optimization, subject to factor graph matrix (FGM) constraints and a minimum user data rate. Since the optimization problems are non-convex, the complexity of finding the </span>global optimal solutions is prohibitive. We propose a gradient ascent-based </span></span>iterative algorithm<span> to compute the optimal UAV 3D deployment and trajectory. Further, an effective channel state information-based algorithm is proposed for FGM assignment, followed by a Lagrange<span> dual decomposition method to solve the power allocation problem efficiently. Our research findings demonstrate that the optimization of the UAV trajectory gives improved sum-rate within the specified energy budget. Further, employing CSI-based multiple subcarrier allocation and strategic power allocation can significantly improve system performance compared to the benchmark schemes.</span></span></p></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"45 ","pages":"Article 100714"},"PeriodicalIF":5.8000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Resource management for sum-rate maximization in SCMA-assisted UAV system\",\"authors\":\"Saumya Chaturvedi , Vivek Ashok Bohara , Zilong Liu , Anand Srivastava , Pei Xiao\",\"doi\":\"10.1016/j.vehcom.2023.100714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span><span>This work presents a resource management framework for optimizing the sum-rate in a sparse code multiple access (SCMA)-assisted UAV<span><span> downlink system. We formulate two optimization problems for maximizing the overall sum-rate: the first problem addresses UAV 3D deployment and trajectory optimization with energy constraints, while the second focuses on optimizing SCMA </span>subcarrier and </span></span>power allocation<span><span> optimization, subject to factor graph matrix (FGM) constraints and a minimum user data rate. Since the optimization problems are non-convex, the complexity of finding the </span>global optimal solutions is prohibitive. We propose a gradient ascent-based </span></span>iterative algorithm<span> to compute the optimal UAV 3D deployment and trajectory. Further, an effective channel state information-based algorithm is proposed for FGM assignment, followed by a Lagrange<span> dual decomposition method to solve the power allocation problem efficiently. Our research findings demonstrate that the optimization of the UAV trajectory gives improved sum-rate within the specified energy budget. Further, employing CSI-based multiple subcarrier allocation and strategic power allocation can significantly improve system performance compared to the benchmark schemes.</span></span></p></div>\",\"PeriodicalId\":54346,\"journal\":{\"name\":\"Vehicular Communications\",\"volume\":\"45 \",\"pages\":\"Article 100714\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2023-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Vehicular Communications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214209623001444\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vehicular Communications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214209623001444","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Resource management for sum-rate maximization in SCMA-assisted UAV system
This work presents a resource management framework for optimizing the sum-rate in a sparse code multiple access (SCMA)-assisted UAV downlink system. We formulate two optimization problems for maximizing the overall sum-rate: the first problem addresses UAV 3D deployment and trajectory optimization with energy constraints, while the second focuses on optimizing SCMA subcarrier and power allocation optimization, subject to factor graph matrix (FGM) constraints and a minimum user data rate. Since the optimization problems are non-convex, the complexity of finding the global optimal solutions is prohibitive. We propose a gradient ascent-based iterative algorithm to compute the optimal UAV 3D deployment and trajectory. Further, an effective channel state information-based algorithm is proposed for FGM assignment, followed by a Lagrange dual decomposition method to solve the power allocation problem efficiently. Our research findings demonstrate that the optimization of the UAV trajectory gives improved sum-rate within the specified energy budget. Further, employing CSI-based multiple subcarrier allocation and strategic power allocation can significantly improve system performance compared to the benchmark schemes.
期刊介绍:
Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier.
The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications:
Vehicle to vehicle and vehicle to infrastructure communications
Channel modelling, modulating and coding
Congestion Control and scalability issues
Protocol design, testing and verification
Routing in vehicular networks
Security issues and countermeasures
Deployment and field testing
Reducing energy consumption and enhancing safety of vehicles
Wireless in–car networks
Data collection and dissemination methods
Mobility and handover issues
Safety and driver assistance applications
UAV
Underwater communications
Autonomous cooperative driving
Social networks
Internet of vehicles
Standardization of protocols.