Integrated Sensing and Communication Enabled Multiple Beamwidth and Power Allocation for Connected Automated Vehicles

Connected autonomous vehicles(CAVs)are a promising paradigm for implementing intelligent transportation systems.However,in CAVs scenarios,the sensing blind areas cause serious safety hazards.Existing vehicle-to-vehicle(V2V)technology is difficult to break through the sensing blind area and ensure reliable sensing information.To overcome these problems,considering infrastructures as a means to extend the sensing range is feasible based on the integrated sensing and communication(ISAC)technology.The mmWave base station(mmBS)transmits multiple beams consisting of communication beams and sensing beams.The sensing beams are responsible for sensing objects within the CAVs blind area,while the communication beams are responsible for transmitting the sensed information to the CAVs.To reduce the impact of inter-beam interference,a joint multiple beamwidth and power allocation(JMBPA)algorithm is proposed.By maximizing the communication transmission rate under the sensing constraints.The proposed non-convex optimization problem is transformed into a standard difference of two convex functions(D.C.)problem.Finally,the superiority of the lutions.The average transmission rate of communication beams remains over 3.4 Gbps,showcasing a significant improvement compared to other algorithms.Moreover,the satisfaction of sensing services remains steady.

Architecture for Cellular Enabled Integrated Communication and Sensing Services

There is growing interest in the integrated sensing and communication(ISAC)to extend the 5G+/6G network capabilities by introducing sensing capability.While the solutions for mono-static or bi-static ISAC have shown feasibility and benefits based on existing 5G physical layer design,whether and how to coordinate multiple ISAC devices to better exert networking performance are rarely discussed.3 rd Partnership Project(3GPP)has initiated the ISAC use cases study,and the follow-up studies for network architecture could be anticipated.In this article,we focus on gNB-based sensing mode and propose ISAC functional framework with given of highlevel service procedures to enable cellular based ISAC services.In the proposed ISAC framework,three types of network functions for sensing service as Sensing Function(SF),lightweight-Edge Sensing Function(ESF)and full-version-ESF are designed with interaction with network nodes to fulfill the latency requirements of ISAC use cases.Finally,with simulation evaluations and hardware testbed results,we further verify the performance benefit and feasibility to enable ISAC in 5G for the gNB-based sensing mode with new design on SF and related signaling protocols.

Asymptotic Performance Limits of Vehicular Location and Velocity Detection Towards 6G mmWave Integrated Communication and Sensing

In this paper,joint location and velocity estimation(JLVE)of vehicular terminals for 6G integrated communication and sensing(ICAS)is studied.We aim to provide a unified performance analysis framework for ICAS-based JLVE,which is challenging due to random fading,multipath interference,and complexly coupled system models,and thus the impact of channel fading and multipath interference on JLVE performance is not fully understood.To address this challenge,we exploit structured information models of the JLVE problem to render tractable performance quantification.Firstly,an individual closedform Cramer-Rao lower bound for vehicular localization,velocity detection and channel estimation,respectively,is established for gaining insights into performance limits of ICAS-based JLVE.Secondly,the impact of system resource factors and fading environments,e.g.,system bandwidth,the number of subcarriers,carrier frequency,antenna array size,transmission distance,spatial channel correlation,channel covariance,the number of interference paths and noise power,on the JLVE performance is theoretically analyzed.The associated closed-form JLVE performance analysis can not only provide theoretical foundations for ICAS receiver design but also provide a perfor mance benchmark for various JLVE methods。

Integrated sensing and communication based outdoor multi-target detection,tracking,and localization in practical 5G Networks

The 6th generation(6G)wireless networks will likely to support a variety of capabilities beyond communication,such as sensing and localization,through the use of communication networks empowered by advanced technologies.Integrated sensing and communication(ISAC)has been recognized as a critical technology as well as a usage scenario for 6G,as widely agreed by leading global standardization bodies.ISAC utilizes communication infrastructure and devices to provide the capability of sensing the environment with high resolution,as well as tracking and localizing moving objects nearby.Meeting both the requirements for communication and sensing simultaneously,ISAC-based approaches celebrate the advantages of higher spectral and energy efficiency compared to two separate systems to serve two purposes,and potentially lower costs and easy deployment.A key step towards the standardization and commercialization of ISAC is to carry out comprehensive field trials in practical networks,such as the 5th generation(5G)networks,to demonstrate its true capacities in practical scenarios.In this paper,an ISAC-based outdoor multi-target detection,tracking and localization approach is proposed and validated in 5G networks.The proposed system comprises of 5G base stations(BSs)which serve nearby mobile users normally,while accomplishing the task of detecting,tracking,and localizing drones,vehicles,and pedestrians simultaneously.Comprehensive trial results demonstrate the relatively high accuracy of the proposed method in practical outdoor environment when tracking and localizing single targets and multiple targets.

Cognitive J^(2)SAC:Joint Jamming,Sensing,and Communication Under Antagonistic Environment

Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.

Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-Enabled Vehicular Networks

Predictive beamforming design is an essential task in realizing high-mobility integrated sensing and communication(ISAC),which highly depends on the accuracy of the channel prediction(CP),i.e.,predicting the angular parameters of users.However,the performance of CP highly depends on the estimated historical channel stated information(CSI)with estimation errors,resulting in the performance degradation for most traditional CP methods.To further improve the prediction accuracy,in this paper,we focus on the ISAC in vehicle networks and propose a convolutional long-short term memory(CLSTM)recurrent neural network(CLRNet)to predict the angle of vehicles for the design of predictive beamforming.In the developed CLRNet,both the convolutional neural network(CNN)module and the LSTM module are adopted to exploit the spatial features and the temporal dependency from the estimated historical angles of vehicles to facilitate the angle prediction.Finally,numerical results demonstrate that the developed CLRNet-based method is robust to the estimation error and can significantly outperform the state-of-the-art benchmarks,achieving an excellent sum-rate performance for ISAC systems.

An Indoor Environment Sensing and Localization System via mmWave Phased Array

In this paper,an indoor layout sensing and localization system with testbed in the 60-GHz millimeter wave(mmWave)band,named mmReality,is elaborated.The mmReality system consists of one transmitter and one mobile receiver,both with a phased array and a single radio frequency(RF)chain.To reconstruct the room layout,the pilot signal is delivered from the transmitter to the receiver via different pairs of transmission and receiving beams,so that multipath signals in all directions can be captured.Then spatial smoothing and the two-dimensional multiple signal classification(MUSIC)algorithm are applied to detect the angle-of-departures(AoDs)and angle-of-arrivals(AoAs)of propagation paths.Moreover,the technique of multi-carrier ranging is adopted to measure the path lengths.Therefore,with the measurements of the receiver in different locations of the room,the receiver and virtual transmitters can be pinpointed to reconstruct the room layout.Experiments show that the reconstructed room layout can be utilized to localize a mobile device via the AoA spectrum.