Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity comm...Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.展开更多
The evolution of global mobile data over the past decades in broadcasting, Internet of Things (IoT), education, healthcare, commerce, and energy has put strong pressure on 3G/4G mobile networks to improve their servic...The evolution of global mobile data over the past decades in broadcasting, Internet of Things (IoT), education, healthcare, commerce, and energy has put strong pressure on 3G/4G mobile networks to improve their service offerings. These generations of mobile networks were initially invented to meet the requirements of the above-mentioned applications. However, as the requirements in these applications continue to increase, new mobile technologies such as 5G (fifth generation), 5G and beyond (B5G, beyond fifth generation), and 6G (sixth generation) are still progressing and being experimented. These networks are very heterogeneous generations of mobile networks that will have to offer very high throughput per user, good energy efficiency, better traffic capacity per area, improved spectral efficiency, very low latency, and high mobility. To meet these requirements, the radio interface of future mobile networks will have to be flexible and rationalized the available frequency resources. Therefore, new modulation methods, access techniques and waveforms capable of supporting these technological changes are proposed. This review presents brief descriptions of the types of 5G, B5G, and 6G waveforms. The 5G consists of OFDM including its transmission techniques: generalized frequency division multiplexing (GFDM), filter bank based multi-carrier (FBMC), universal filtered multi-carrier (UFMC), and index modulation (IM). Meanwhile, the 6G covers orthogonal time frequency space (OTFS), orthogonal chirp division multiplexing (OCDM) and orthogonal time sequence multiplexing (OTSM). The networks’ potentialities, advantages, disadvantages, and future directions are outlined.展开更多
The rapid growth of mobile and Internet of Things(IoT)applications in dense urban environments places stringent demands on future Beyond 5G(B5G)or Beyond 6G(B6G)networks,which must ensure high Quality of Service(QoS)w...The rapid growth of mobile and Internet of Things(IoT)applications in dense urban environments places stringent demands on future Beyond 5G(B5G)or Beyond 6G(B6G)networks,which must ensure high Quality of Service(QoS)while maintaining cost-efficiency and sustainable deployment.Traditional strategies struggle with complex 3D propagation,building penetration loss,and the balance between coverage and infrastructure cost.To address this challenge,this study presents the first application of a Global-best Guided Quantum-inspired Tabu Search with Quantum-Not Gate(GQTS-QNG)framework for 3D base-station deployment optimization.The problem is formulated as a multi-objective model that simultaneously maximizes coverage and minimizes deployment cost.A binary-to-decimal encodingmechanism is designed to represent discrete placement coordinates and base station types,leveraging a quantum-inspired method to efficiently search and refine solutions within challenging combinatorial environments.Global-best guidance and tabu memory are integrated to strengthen convergence stability and avoid revisiting previously explored solutions.Simulation results across user densities ranging from 1000 to 10,000 show that GQTS-QNG consistently finds deployment configurations achieving full coverage while reducing deployment cost compared with the state-of-the-art algorithms under equal iteration times.Additionally,our method generates welldistributed and structured Pareto fronts,offering diverse planning options that allow operators to flexibly balance cost and performance requirements.These findings demonstrate that GQTS-QNG is a scalable and efficient algorithm for sustainable 3D cellular network deployment in B5G/6G urban scenarios.展开更多
How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the ...How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.展开更多
现有蜂窝5G/B5G高可靠低时延通信(ultra-reliable and low latency communications,URLLC)标准3GPP Release 17-18采用经典正交频分复用(OFDM)多载波波形传输,因其工作在授权频带,较少考虑URLLCOFDM多载波传输抗干扰策略。未来工业物联...现有蜂窝5G/B5G高可靠低时延通信(ultra-reliable and low latency communications,URLLC)标准3GPP Release 17-18采用经典正交频分复用(OFDM)多载波波形传输,因其工作在授权频带,较少考虑URLLCOFDM多载波传输抗干扰策略。未来工业物联网异构多服务质量(quality of service,QoS)业务大部分部署于非授权频带,其无线通信链路变得复杂,现有URLLC-OFDM波形无法完全为工业物联网信息传输提供高可靠性、低时延的苛刻要求。首先,基于子载波可配置的OFDMA,将鲁棒性更高的子载波跳频(subcarrier frequency hopping,Sub-FH)技术应用于OFDMA中(即Sub-FH/OFDMA),以提高信号传输可靠性。然后,设计将Sub-FH/OFDMA波形融合到以微时隙为基本单位的调度策略中。该调度策略采用Hamming编码+微时隙结合的混合自动重传请求(HARQ)机制,有效降低端到端传输的重传次数,旨在提升节点传输的实时性。并推导了信息误码(块)率与重传次数的折中理论关系。仿真结果表明,在面对外部电磁干扰和内部多用户干扰时,该方案能够保障物联网节点的稳定传输质量,并在目标误块率为10-5时实现毫秒级短数据包的传输时延。通过波形设计和MAC时隙调度的跨层级设计,为未来B5G/6G通信在复杂工业物联网场景中的实际应用提供了可行解决方案。展开更多
车联网借助新一代信息通信技术,实现人、车、路、云等的互联互通.未来beyond 5G(B5G)和6G将赋予下一代车联网更极致的通信与感知性能,有效支撑智能驾驶与智慧交通等创新应用.然而,车辆高速移动带来的高多普勒效应,极大地增加了现有正交...车联网借助新一代信息通信技术,实现人、车、路、云等的互联互通.未来beyond 5G(B5G)和6G将赋予下一代车联网更极致的通信与感知性能,有效支撑智能驾驶与智慧交通等创新应用.然而,车辆高速移动带来的高多普勒效应,极大地增加了现有正交频分复用(Orthogonal frequency division multiplexing,OFDM)系统的载波间干扰和导频开销,尤其是B5G/6G时代毫米波、太赫兹等高频段的广泛应用将进一步加剧这一问题.近年来,正交时频空间(Orthogonal time frequency space, OTFS)技术由于在抗时频双域选择性衰落方面的显著优势受到了业界的广泛关注.基于OTFS实现通信与感知一体化成为了车联网领域的研究热点.本文旨在研究基于OTFS的车联网通感一体化的系统原理、关键技术、应用模式及技术挑战.首先,在现有OTFS通信系统的基础上,探讨OTFS通感一体化的系统架构、实现原理以及通信和感知性能.然后,介绍OTFS技术的国内外研究现状,并进一步从物理层帧结构、导频机制等方面讨论OTFS通感一体化的难点与关键技术.最后,结合实际场景,分析OTFS在车联网通感一体化中的应用及面临的主要挑战.展开更多
文摘Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.
文摘The evolution of global mobile data over the past decades in broadcasting, Internet of Things (IoT), education, healthcare, commerce, and energy has put strong pressure on 3G/4G mobile networks to improve their service offerings. These generations of mobile networks were initially invented to meet the requirements of the above-mentioned applications. However, as the requirements in these applications continue to increase, new mobile technologies such as 5G (fifth generation), 5G and beyond (B5G, beyond fifth generation), and 6G (sixth generation) are still progressing and being experimented. These networks are very heterogeneous generations of mobile networks that will have to offer very high throughput per user, good energy efficiency, better traffic capacity per area, improved spectral efficiency, very low latency, and high mobility. To meet these requirements, the radio interface of future mobile networks will have to be flexible and rationalized the available frequency resources. Therefore, new modulation methods, access techniques and waveforms capable of supporting these technological changes are proposed. This review presents brief descriptions of the types of 5G, B5G, and 6G waveforms. The 5G consists of OFDM including its transmission techniques: generalized frequency division multiplexing (GFDM), filter bank based multi-carrier (FBMC), universal filtered multi-carrier (UFMC), and index modulation (IM). Meanwhile, the 6G covers orthogonal time frequency space (OTFS), orthogonal chirp division multiplexing (OCDM) and orthogonal time sequence multiplexing (OTSM). The networks’ potentialities, advantages, disadvantages, and future directions are outlined.
基金supported by the National Science and Technology Council,Taiwan,under Grants 113-2221-E-260-014-MY2 and 114-2119-M-033-001.
文摘The rapid growth of mobile and Internet of Things(IoT)applications in dense urban environments places stringent demands on future Beyond 5G(B5G)or Beyond 6G(B6G)networks,which must ensure high Quality of Service(QoS)while maintaining cost-efficiency and sustainable deployment.Traditional strategies struggle with complex 3D propagation,building penetration loss,and the balance between coverage and infrastructure cost.To address this challenge,this study presents the first application of a Global-best Guided Quantum-inspired Tabu Search with Quantum-Not Gate(GQTS-QNG)framework for 3D base-station deployment optimization.The problem is formulated as a multi-objective model that simultaneously maximizes coverage and minimizes deployment cost.A binary-to-decimal encodingmechanism is designed to represent discrete placement coordinates and base station types,leveraging a quantum-inspired method to efficiently search and refine solutions within challenging combinatorial environments.Global-best guidance and tabu memory are integrated to strengthen convergence stability and avoid revisiting previously explored solutions.Simulation results across user densities ranging from 1000 to 10,000 show that GQTS-QNG consistently finds deployment configurations achieving full coverage while reducing deployment cost compared with the state-of-the-art algorithms under equal iteration times.Additionally,our method generates welldistributed and structured Pareto fronts,offering diverse planning options that allow operators to flexibly balance cost and performance requirements.These findings demonstrate that GQTS-QNG is a scalable and efficient algorithm for sustainable 3D cellular network deployment in B5G/6G urban scenarios.
文摘How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.
文摘现有蜂窝5G/B5G高可靠低时延通信(ultra-reliable and low latency communications,URLLC)标准3GPP Release 17-18采用经典正交频分复用(OFDM)多载波波形传输,因其工作在授权频带,较少考虑URLLCOFDM多载波传输抗干扰策略。未来工业物联网异构多服务质量(quality of service,QoS)业务大部分部署于非授权频带,其无线通信链路变得复杂,现有URLLC-OFDM波形无法完全为工业物联网信息传输提供高可靠性、低时延的苛刻要求。首先,基于子载波可配置的OFDMA,将鲁棒性更高的子载波跳频(subcarrier frequency hopping,Sub-FH)技术应用于OFDMA中(即Sub-FH/OFDMA),以提高信号传输可靠性。然后,设计将Sub-FH/OFDMA波形融合到以微时隙为基本单位的调度策略中。该调度策略采用Hamming编码+微时隙结合的混合自动重传请求(HARQ)机制,有效降低端到端传输的重传次数,旨在提升节点传输的实时性。并推导了信息误码(块)率与重传次数的折中理论关系。仿真结果表明,在面对外部电磁干扰和内部多用户干扰时,该方案能够保障物联网节点的稳定传输质量,并在目标误块率为10-5时实现毫秒级短数据包的传输时延。通过波形设计和MAC时隙调度的跨层级设计,为未来B5G/6G通信在复杂工业物联网场景中的实际应用提供了可行解决方案。
文摘车联网借助新一代信息通信技术,实现人、车、路、云等的互联互通.未来beyond 5G(B5G)和6G将赋予下一代车联网更极致的通信与感知性能,有效支撑智能驾驶与智慧交通等创新应用.然而,车辆高速移动带来的高多普勒效应,极大地增加了现有正交频分复用(Orthogonal frequency division multiplexing,OFDM)系统的载波间干扰和导频开销,尤其是B5G/6G时代毫米波、太赫兹等高频段的广泛应用将进一步加剧这一问题.近年来,正交时频空间(Orthogonal time frequency space, OTFS)技术由于在抗时频双域选择性衰落方面的显著优势受到了业界的广泛关注.基于OTFS实现通信与感知一体化成为了车联网领域的研究热点.本文旨在研究基于OTFS的车联网通感一体化的系统原理、关键技术、应用模式及技术挑战.首先,在现有OTFS通信系统的基础上,探讨OTFS通感一体化的系统架构、实现原理以及通信和感知性能.然后,介绍OTFS技术的国内外研究现状,并进一步从物理层帧结构、导频机制等方面讨论OTFS通感一体化的难点与关键技术.最后,结合实际场景,分析OTFS在车联网通感一体化中的应用及面临的主要挑战.
