The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
目的:分析二肽基肽酶样蛋白-6(dipeptidyl-peptidase-like protein 6,DPPX)抗体相关脑炎患者的临床特征。方法:对2016年1月—2025年2月南京医科大学附属脑科医院就诊的5例DPPX抗体相关脑炎患者的临床特点、脑电图、磁共振成像(magnetic ...目的:分析二肽基肽酶样蛋白-6(dipeptidyl-peptidase-like protein 6,DPPX)抗体相关脑炎患者的临床特征。方法:对2016年1月—2025年2月南京医科大学附属脑科医院就诊的5例DPPX抗体相关脑炎患者的临床特点、脑电图、磁共振成像(magnetic resonance imaging,MRI)及预后进行回顾性研究。结果:5例均为男性,年龄14~56岁。5例患者血清DPPX抗体均为阳性,滴度1∶100~1∶10,其中1例合并血清接触蛋白关联蛋白2(contactin-associated protein-like 2,CASPR2)抗体阳性,4例脑脊液DPPX抗体阴性,1例滴度1∶1。2例患者以行为异常起病,1例以癫痫发作起病,1例以记忆力减退起病,1例合并CASPR2抗体阳性患者以多部位游走性肌阵挛起病。4例患者头颅MRI正常,1例头颅MRI提示双侧颞叶异常信号。以癫痫发作起病的患者脑电图背景重度异常合并左前颞尖波、尖慢波频发。结论:DPPX抗体相关脑炎临床表现具有异质性,早期诊断与鉴别困难,免疫治疗有效,易复发。展开更多
基于IPv6的段路由(segment routing over IPv6,SRv6)作为下一代网络架构的关键使能技术,通过引入灵活的段路由转发平面,为提升网络智能化水平、拓展业务服务能力带来革新机遇.旨在全面梳理近年来SRv6的演进趋势和研究现状.首先,系统总结...基于IPv6的段路由(segment routing over IPv6,SRv6)作为下一代网络架构的关键使能技术,通过引入灵活的段路由转发平面,为提升网络智能化水平、拓展业务服务能力带来革新机遇.旨在全面梳理近年来SRv6的演进趋势和研究现状.首先,系统总结SRv6在网络架构与性能、网络管理与运维以及新兴业务支撑等方面的应用,凸显了SRv6精细调度、灵活编程、服务融合等独特优势.与此同时,深入剖析SRv6在性能与效率、可靠性与安全性、部署与演进策略这3个方面所面临的关键挑战,并重点讨论当前主流的解决思路和发展趋势.最后,立足产业生态构建、人工智能引入、行业融合创新等视角,对SRv6未来的发展方向和挑战进行前瞻性思考和展望.研究成果将为运营商构建开放、智能、安全的新一代网络提供理论参考和实践指导.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
文摘基于IPv6的段路由(segment routing over IPv6,SRv6)作为下一代网络架构的关键使能技术,通过引入灵活的段路由转发平面,为提升网络智能化水平、拓展业务服务能力带来革新机遇.旨在全面梳理近年来SRv6的演进趋势和研究现状.首先,系统总结SRv6在网络架构与性能、网络管理与运维以及新兴业务支撑等方面的应用,凸显了SRv6精细调度、灵活编程、服务融合等独特优势.与此同时,深入剖析SRv6在性能与效率、可靠性与安全性、部署与演进策略这3个方面所面临的关键挑战,并重点讨论当前主流的解决思路和发展趋势.最后,立足产业生态构建、人工智能引入、行业融合创新等视角,对SRv6未来的发展方向和挑战进行前瞻性思考和展望.研究成果将为运营商构建开放、智能、安全的新一代网络提供理论参考和实践指导.
