Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
Integrated Sensing and Communication(ISAC)is considered a key technology in 6G networks.An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems.The widely used Ge...Integrated Sensing and Communication(ISAC)is considered a key technology in 6G networks.An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems.The widely used Geometry-Based Stochastic Model(GBSM),typically applied in standardized channel modeling,mainly focuses on the statistical fading characteristics of the channel.However,it fails to capture the characteristics of targets in ISAC systems,such as their positions and velocities,as well as the impact of the targets on the background.To address this issue,this paper proposes an Extended-GBSM(E-GBSM)sensing channel model that incorporates newly discovered channel characteristics into a unified modeling framework.In this framework,the sensing channel is divided into target and background channels.For the target channel,the model introduces a concatenated modeling approach,while for the background channel,a parameter called the power control factor is introduced to assess impact of the target on the background channel,making the modeling framework applicable to both mono-static and bi-static sensing modes.To validate the proposed model’s effectiveness,measurements of target and background channels are conducted across a wide range of indoor and outdoor scenarios,covering various sensing targets such as metal plates,reconfigurable intelligent surfaces,human bodies,unmanned aerial vehicles,and vehicles.The experimental results provide important theoretical support and empirical data for the standardization of ISAC channel modeling.展开更多
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
基金supported in part by the Young Scientists Fund of the National Natural Science Foundation of China(No.62201087)in part by the National Natural Science Foundation of China(No.62525101,62341128)+3 种基金in part by the National Key R&D Program of China(No.2023YFB2904803)in part by the Guangdong Major Project of Basic and Applied Basic Research(No.2023B0303000001)in part by the Beijing Natural Science Foundation(No.L243002)in part by the Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint innovation Center.
文摘Integrated Sensing and Communication(ISAC)is considered a key technology in 6G networks.An accurate sensing channel model is crucial for the design and sensing performance evaluation of ISAC systems.The widely used Geometry-Based Stochastic Model(GBSM),typically applied in standardized channel modeling,mainly focuses on the statistical fading characteristics of the channel.However,it fails to capture the characteristics of targets in ISAC systems,such as their positions and velocities,as well as the impact of the targets on the background.To address this issue,this paper proposes an Extended-GBSM(E-GBSM)sensing channel model that incorporates newly discovered channel characteristics into a unified modeling framework.In this framework,the sensing channel is divided into target and background channels.For the target channel,the model introduces a concatenated modeling approach,while for the background channel,a parameter called the power control factor is introduced to assess impact of the target on the background channel,making the modeling framework applicable to both mono-static and bi-static sensing modes.To validate the proposed model’s effectiveness,measurements of target and background channels are conducted across a wide range of indoor and outdoor scenarios,covering various sensing targets such as metal plates,reconfigurable intelligent surfaces,human bodies,unmanned aerial vehicles,and vehicles.The experimental results provide important theoretical support and empirical data for the standardization of ISAC channel modeling.
