面向6G网络的技术发展,综述了世界各国和第三代合作伙伴计划(The 3rd Generation Partnership Project,3GPP)、电气和电子工程师协会(Institute of Electrical and Electronics Engineers,IEEE)、等国际组织在该领域的规划和已开展工作...面向6G网络的技术发展,综述了世界各国和第三代合作伙伴计划(The 3rd Generation Partnership Project,3GPP)、电气和电子工程师协会(Institute of Electrical and Electronics Engineers,IEEE)、等国际组织在该领域的规划和已开展工作情况,阐述了6G愿景和主要技术指标体系。针对无线接入这一核心技术环节,介绍了6G阶段新型波形、多址接入、信道编码以及无蜂窝大规模MIMO等技术研究和发展情况,重点叙述了全频谱、全覆盖、内生安全、全应用及人工智能等6G新范式的内涵、关键技术以及目前研究重点,最后对6G技术的未来发展进行了展望。展开更多
Satellite communication offers the prospect of service continuity over uncovered and under-covered areas,service ubiquity,and service scalability.However,several challenges must first be addressed to realize these ben...Satellite communication offers the prospect of service continuity over uncovered and under-covered areas,service ubiquity,and service scalability.However,several challenges must first be addressed to realize these benefits,as the resource management,network control,network security,spectrum management,and energy usage of satellite networks are more challenging than that of terrestrial networks.Meanwhile,artificial intelligence(AI),including machine learning,deep learning,and reinforcement learning,has been steadily growing as a research field and has shown successful results in diverse applications,including wireless communication.In particular,the application of AI to a wide variety of satellite communication aspects has demonstrated excellent potential,including beam-hopping,anti-jamming,network traffic forecasting,channel modeling,telemetry mining,ionospheric scintillation detecting,interference managing,remote sensing,behavior modeling,space-air-ground integrating,and energy managing.This work thus provides a general overview of AI,its diverse sub-fields,and its state-of-the-art algorithms.Several challenges facing diverse aspects of satellite communication systems are then discussed,and their proposed and potential AI-based solutions are presented.Finally,an outlook of field is drawn,and future steps are suggested.展开更多
Future beyond fifth-generation(B5G)and sixth-generation(6G)mobile communications will shift from facilitating interpersonal communications to supporting internet of everything(IoE),where intelligent communications wit...Future beyond fifth-generation(B5G)and sixth-generation(6G)mobile communications will shift from facilitating interpersonal communications to supporting internet of everything(IoE),where intelligent communications with full integration of big data and artificial intelligence(AI)will play an important role in improving network efficiency and providing high-quality service.As a rapid evolving paradigm,the AI-empowered mobile communications demand large amounts of data acquired from real network environment for systematic test and verification.Hence,we build the world’s first true-data testbed for 5G/B5G intelligent network(TTIN),which comprises 5G/B5G on-site experimental networks,data acquisition&data warehouse,and AI engine&network optimization.In the TTIN,true network data acquisition,storage,standardization,and analysis are available,which enable system-level online verification of B5G/6G-orientated key technologies and support data-driven network optimization through the closed-loop control mechanism.This paper elaborates on the system architecture and module design of TTIN.Detailed technical specifications and some of the established use cases are also showcased.展开更多
To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathem...To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization (ACO) algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm (GA) for dynamic obstacle avoidance in real time.展开更多
文摘面向6G网络的技术发展,综述了世界各国和第三代合作伙伴计划(The 3rd Generation Partnership Project,3GPP)、电气和电子工程师协会(Institute of Electrical and Electronics Engineers,IEEE)、等国际组织在该领域的规划和已开展工作情况,阐述了6G愿景和主要技术指标体系。针对无线接入这一核心技术环节,介绍了6G阶段新型波形、多址接入、信道编码以及无蜂窝大规模MIMO等技术研究和发展情况,重点叙述了全频谱、全覆盖、内生安全、全应用及人工智能等6G新范式的内涵、关键技术以及目前研究重点,最后对6G技术的未来发展进行了展望。
文摘Satellite communication offers the prospect of service continuity over uncovered and under-covered areas,service ubiquity,and service scalability.However,several challenges must first be addressed to realize these benefits,as the resource management,network control,network security,spectrum management,and energy usage of satellite networks are more challenging than that of terrestrial networks.Meanwhile,artificial intelligence(AI),including machine learning,deep learning,and reinforcement learning,has been steadily growing as a research field and has shown successful results in diverse applications,including wireless communication.In particular,the application of AI to a wide variety of satellite communication aspects has demonstrated excellent potential,including beam-hopping,anti-jamming,network traffic forecasting,channel modeling,telemetry mining,ionospheric scintillation detecting,interference managing,remote sensing,behavior modeling,space-air-ground integrating,and energy managing.This work thus provides a general overview of AI,its diverse sub-fields,and its state-of-the-art algorithms.Several challenges facing diverse aspects of satellite communication systems are then discussed,and their proposed and potential AI-based solutions are presented.Finally,an outlook of field is drawn,and future steps are suggested.
基金This work was supported in part by the National Key R&D Program of China(No.2018YFB1800801)the National Natural Science Foundation of China(Nos.61720106003 and 62001103).
文摘Future beyond fifth-generation(B5G)and sixth-generation(6G)mobile communications will shift from facilitating interpersonal communications to supporting internet of everything(IoE),where intelligent communications with full integration of big data and artificial intelligence(AI)will play an important role in improving network efficiency and providing high-quality service.As a rapid evolving paradigm,the AI-empowered mobile communications demand large amounts of data acquired from real network environment for systematic test and verification.Hence,we build the world’s first true-data testbed for 5G/B5G intelligent network(TTIN),which comprises 5G/B5G on-site experimental networks,data acquisition&data warehouse,and AI engine&network optimization.In the TTIN,true network data acquisition,storage,standardization,and analysis are available,which enable system-level online verification of B5G/6G-orientated key technologies and support data-driven network optimization through the closed-loop control mechanism.This paper elaborates on the system architecture and module design of TTIN.Detailed technical specifications and some of the established use cases are also showcased.
基金Project(60475035) supported by the National Natural Science Foundation of China
文摘To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization (ACO) algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm (GA) for dynamic obstacle avoidance in real time.
