Design of integrated radar and communication system based on MIMO-OFDM waveform

Orthogonal frequency division multiplexing (OFDM) waveform enables radar and communication functions simultaneously, which encounters low angle resolution and poor data rate for traditional single input single output (SISO) systems. To solve these problems, an integrated radar and communication system (IRCS) with multiple input multiple output (MIMO) OFDM waveform is proposed. The different limitations of radar and communication in designing such a system are investigated. Then, an optimization problem is devised to obtain suitable system parameters, including the number of subcarriers, subcarrier spacing, number of symbols, pulse repetition frequency (PRF) and length of cyclic prefix (CP). Finally, to satisfy the requirements of both radar and communication, the IRCS parameters are derived in three typical cases. Several numerical results are presented to illustrate the demands of radar and communication, inconsistent or consistent, for the IRCS parameters and the superiority of the proposed system.

The Spread Spectrum GFDM Schemes for Integrated Satellite-Terrestrial Communication System

Recently, integrated Satellite-Terrestrial(S-T) communication system, especially the integration of satellite communication with 5G/6G, is regarded as a research hotpot. Future integrated S-T communication systems are demanding a more compatible and robust physical layer waveform. Considering physical layer access waveform design, this paper proposed a novel Spread Spectrum Generalized Frequency Division Multiplexing(SS-GFDM) scheme for integrated S-T communication system. Traditional GFDM has many advantages such as excellent adaptability and low out-ofband(OOB) radiation. However, because of intrinsic inter carrier interference(ICI) and low signal-to-noise ratio(SNR), the multiple access performance is degraded. In this paper, we introduced CDMA technology into GFDM. Two different spread spectrum modes, Cyclic Code Shift Keying(CCSK) soft spread spectrum and Direct Sequence Spread Spectrum(DSSS), are considered and compared in this paper to illustrate the benefits of GFDM-CDMA in low SNR scenario. Moreover, this scheme integrates the slot-ALOHA protocol with GFDM-CDMA, which extends access freedom in frequency, time and code domain. The simulation and analysis results show that the proposed GFDM-CDMA scheme reduces the performance degradation caused by interference. It is effective in typical satellite channel with low complexity. Meanwhile, the peak-average-power-ratio(PAPR) and access performance has been enhanced significantly.

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。

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.

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.

Create Your Own Data and Energy Integrated Communication Network:A Brief Tutorial and a Prototype System

In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.

Performance Trade-off for Integrated Communication and Data-Assisted Positioning in MIMO-OFDM System

Communication and positioning,the two pillars of mobile communication systems,are currently being integrated together.The development of communication technologies is the driving force of the positioning progress.In turn,the location information provided by positioning improves the communication performance in various ways.However,the competition of these two functions in terms of resource allocation is a critical issue hindering their integration.In this article,we investigate the trade-off for the integrated communication and data-assisted positioning in multiple-input multiple-output orthogonal frequency division multiplexing systems.A data-assisted positioning method is designed first,which uses both positioning reference signals(PRSs)and data signals for positioning.The positioning and communication performance are theoretically evaluated respectively,then combined to obtain an integrated performance metric.The trade-off is analyzed and the integrated performance is optimized considering the priority of different functions.Numerical simulations show that the data-assisted positioning can not only improve the positioning accuracy,but also reduce the PRS overhead.And the established integrated performance metric can identify the optimal performance and the corresponding resource allocation schemes.

Demonstration of radar-aided flexible communication in a photonics-based W-band distributed integrated sensing and communication system for 6G

This paper experimentally demonstrates a distributed photonics-based W-band integrated sensing and communication(ISAC) system, in which radar sensing can aid the communication links in alignment and data rate estimation. As a proof-of-concept, the ISAC system locates the users, guides the alignment, and sets a communication link with the estimated highest data rate. A peak net data rate of 68.6 Gbit/s and a target sensing with a less-than-1-cm error and a sub-2-cm resolution have been tested over a 10-km fiber and a 1.15-m free space transmission in the photonics-based W-band ISAC system. The achievable net data rates of the users at different locations estimated by sensing are experimentally verified.

A polarisation coding scheme based on an integrated sensing and communication system

Integrated sensing and communication(ISAC)technology enhances the spectrum utilization of the system by interchanging the spectrum between communication and sensing,which has gained popularity in scenarios such as vehicle-to-everything(V2X).With the aim of providing more dependable services for vehicles in high-speed mobile scenarios,we propose a scheme based on sense-assisted polarisation coding.Specifically,the base station acquires the vehicle's positional information and channel strength parameters through the forward time slot echo information.This information informs the creation of the coding architecture for the following time slot.This approach not only optimizes resource consumption but also enhances system dependability.Our simulation results confirm that the introduced scheme displays a notable improvement in the bit error rate(BER)when compared to traditional communication frameworks,maintaining this advantage across both unimpeded and compromised channel conditions.

Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control

In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)technologies.In this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use cases.Next,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration approach.We review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration approaches.We also highlight the need for intelligence in resources integration.Then,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various classes.Finally,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.

Tasks-Oriented Joint Resource Allocation Scheme for the Internet of Vehicles with Sensing, Communication and Computing Integration

With the development of artificial intelligence(AI)and 5G technology,the integration of sensing,communication and computing in the Internet of Vehicles(Io V)is becoming a trend.However,the large amount of data transmission and the computing requirements of intelligent tasks lead to the complex resource management problems.In view of the above challenges,this paper proposes a tasks-oriented joint resource allocation scheme(TOJRAS)in the scenario of Io V.First,this paper proposes a system model with sensing,communication,and computing integration for multiple intelligent tasks with different requirements in the Io V.Secondly,joint resource allocation problems for real-time tasks and delay-tolerant tasks in the Io V are constructed respectively,including communication,computing and caching resources.Thirdly,a distributed deep Q-network(DDQN)based algorithm is proposed to solve the optimization problems,and the convergence and complexity of the algorithm are discussed.Finally,the experimental results based on real data sets verify the performance advantages of the proposed resource allocation scheme,compared to the existing ones.The exploration efficiency of our proposed DDQN-based algorithm is improved by at least about 5%,and our proposed resource allocation scheme improves the m AP performance by about 0.15 under resource constraints.

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.

Joint Design of ISAC Waveform Under PAPR Constraints

In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication multi-user interference(MUI)and the gap between dual-use waveform and ideal radar waveform is minimized with peak-toaverage power ratio(PAPR)constraints.We propose an efficient algorithm based on alternating direction method of multipliers(ADMM),which is able to decouple multiple variables and provide a closed-form solution for each subproblem.In addition,to improve the sensing performance in both spatial and temporal domains,we propose a new criteria to design the ideal radar waveform,in which the beam pattern is made similar to the ideal one and the integrated sidelobe level of the ambiguity function in each target direction is minimized in the region of interest.The limited memory Broyden-Fletcher-Goldfarb-Shanno(LBFGS)algorithm is applied to the design of the ideal radar waveform which works as a reference in the design of the dual-function waveform.Numerical results indicate that the designed dual-function waveform is capable of offering good communication quality of service(QoS)and sensing performance.

Sensing-Assisted Accurate and Fast Beam Management for Cellular-Connected mmWave UAV Network

Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high delay and low accuracy of beam alignment,since they only enable the receiver to passively“hear”the information of the transmitter from the radio domain.This paper presents a novel sensing-assisted beam management approach,the first solution that fully utilizes the information from the visual domain to improve communication performance.We employ both integrated sensing and communication and computer vision techniques and design an extended Kalman filtering method for beam tracking and prediction.Besides,we also propose a novel dual identity association solution to distinguish multiple UAVs in dynamic environments.Real-world experiments and numerical results show that the proposed solution outperforms the conventional methods in IA delay,association accuracy,tracking error,and communication performance.

Target parameter estimation for OTFS-integrated radar and communications based on sparse reconstruction preprocessing

Orthogonal time-frequency space(OTFS)is a new modulation technique proposed in recent years for high Doppler wireless scenes.To solve the parameter estimation problem of the OTFS-integrated radar and communications system,we propose a parameter estimation method based on sparse reconstruction preprocessing to reduce the computational effort of the traditional weighted subspace fitting(WSF)algorithm.First,an OTFS-integrated echo signal model is constructed.Then,the echo signal is transformed to the time domain to separate the target angle from the range,and the range and angle of the detected target are coarsely estimated by using the sparse reconstruction algorithm.Finally,the WSF algorithm is used to refine the search with the coarse estimate at the center to obtain an accurate estimate.The simulations demonstrate the effectiveness and superiority of the proposed parameterestimation algorithm.

High-Precision Doppler Frequency Estimation Based Positioning Using OTFS Modulations by Red and Blue Frequency Shift Discriminator

Orthogonal Time Frequency and Space(OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio(SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator(RBFSD) based on the pseudo-noise(PN) sequence.The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than -15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.

Structural knowledge-driven meta-learning for task offloading in vehicular networks with integrated communications,sensing and computing

Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources.However,the overwhelming upload traffic may lead to unacceptable uploading time.To tackle this issue,for tasks taking environmental data as input,the data perceived by roadside units(RSU)equipped with several sensors can be directly exploited for computation,resulting in a novel task offloading paradigm with integrated communications,sensing and computing(I-CSC).With this paradigm,vehicles can select to upload their sensed data to RSUs or transmit computing instructions to RSUs during the offloading.By optimizing the computation mode and network resources,in this paper,we investigate an I-CSC-based task offloading problem to reduce the cost caused by resource consumption while guaranteeing the latency of each task.Although this nonconvex problem can be handled by the alternating minimization(AM)algorithm that alternatively minimizes the divided four sub-problems,it leads to high computational complexity and local optimal solution.To tackle this challenge,we propose a creative structural knowledge-driven meta-learning(SKDML)method,involving both the model-based AM algorithm and neural networks.Specifically,borrowing the iterative structure of the AM algorithm,also referred to as structural knowledge,the proposed SKDML adopts long short-term memory(LSTM)networkbased meta-learning to learn an adaptive optimizer for updating variables in each sub-problem,instead of the handcrafted counterpart in the AM algorithm.Furthermore,to pull out the solution from the local optimum,our proposed SKDML updates parameters in LSTM with the global loss function.Simulation results demonstrate that our method outperforms both the AM algorithm and the meta-learning without structural knowledge in terms of both the online processing time and the network performance.

An Exploratory Study on the Electronic Word of Mouth Communication in Promoting Brands in the Online Platforms

This study discusses on the communication method followed by most of the brands called. “Electronic Word of Mouth” in a short form is called as eWOM in order to reach the customers effectively in a short span. Social media having become a new hybrid component of integrated marketing communication allows the brands to establish strong relationship with the customers. With the establishment of customer relationship online, the brands create a platform for the customers to discuss about the product features, quality, price and write a review about the product online. This research analyses about the social media and its impact in spreading the messages about the brands to the end customers and the impact of gender, age groups, income, designation and the demographic details of the customers in trusting the information that is spread through electronic media and the level at which the eWOM helps the customers to select the brand.

Integrated communication and localization in millimeter-wave systems

As the fifth-generation(5G)mobile communication system is being commercialized,extensive studies on the evolution of 5G and sixth-generation(6G)mobile communication systems have been conducted.Future mobile communication systems are evidently evolving toward a more intelligent and software-reconfigurable functionality paradigm that can provide ubiquitous communication,as well as sense,control,and optimize wireless environments.Thus,integrating communication and localization using the highly directional transmission characteristics of millimeter waves(mmWaves)is a promising route.This approach not only expands the localization capabilities of a communication system but also provides new concepts and opportunities to enhance communication.In this paper,we explain the integrated communication and localization in mmWave systems,in which these processes share the same set of hardware architecture and algorithms.We also provide an overview of the key enabling technologies and the basic knowledge on localization.Then,we provide two promising directions for studies on localization with an extremely large antenna array and model-based(or model-driven)neural networks.We also discuss a comprehensive guidance for location-assisted mmWave communications in terms of channel estimation,channel state information feedback,beam tracking,synchronization,interference control,resource allocation,and user selection.Finally,we outline the future trends on the mutual assistance and enhancement of communication and localization in integrated systems.

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.