Mutual Information Maximization via Joint Power Allocation in Integrated Sensing and Communications System

In this paper, we focus on the power allocation of Integrated Sensing and Communication(ISAC) with orthogonal frequency division multiplexing(OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is,to maximize the mutual information(MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals,as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However,the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization(AO), sequence convex programming(SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.

Adversarial attacks and defenses for digital communication signals identification

As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.

Beam Training and Tracking in mmWave Communication:A Survey

Communicating on millimeter wave(mmWave)bands is ushering in a new epoch of mobile communication which provides the availability of 10 Gbps high data rate transmission.However,mmWave links are easily prone to short transmission range communication because of the serious free space path loss and the blockage by obstacles.To overcome these challenges,highly directional beams are exploited to achieve robust links by hybrid beamforming.Accurately aligning the transmitter and receiver beams,i.e.beam training,is vitally important to high data rate transmission.However,it may cause huge overhead which has negative effects on initial access,handover,and tracking.Besides,the mobility patterns of users are complicated and dynamic,which may cause tracking error and large tracking latency.An efficient beam tracking method has a positive effect on sustaining robust links.This article provides an overview of the beam training and tracking technologies on mmWave bands and reveals the insights for future research in the 6th Generation(6G)mobile network.Especially,some open research problems are proposed to realize fast,accurate,and robust beam training and tracking.We hope that this survey provides guidelines for the researchers in the area of mmWave communications.

A holographic optical communication system based on RSA algorithm and quaternion function

A facile encryption way was successfully applied to the holographic optical encryption system with high speed,multidimensionality,and high capacity,which provided a better security solution for underwater communication.The reconstructed optical security system for information transmission was based on wavelengthλand focal length f that were keys to encryption and decryption.To finish the secure data transmission(λ,f)between sender and receiver,an extended Rivest-Shamir-Adleman(ERSA)algorithm for the encryption was achieved based on three-dimension quaternion function.Therein,the Pollard’s rho method was used for the evaluation and comparison of RSA and ERSA algorithms.The results demonstrate that the message encrypted by the ERSA algorithm has better security than that by RSA algorithm in the face of unpredictability and complexity of information transmission on the unsecure acoustic channel.

Intelligent recognition and information extraction of radar complex jamming based on time-frequency features

In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)situations.In this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging issue.Firstly,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter estimation.Furthermore,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other parameters.Finally,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results.

An Energy Management System with Mobile Energy Station Based Wireless Energy Transfer:System Design and Prototype Implementation

In indoor environments,various batterypowered Internet of Things(IoT)devices,such as remote controllers and electronic tags on high-level shelves,require efficient energy management.However,manually monitoring remaining energy levels and battery replacement is both inadequate and costly.This paper introduces an energy management system for indoor IoT,which includes a mobile energy station(ES)for enabling on-demand wireless energy transfer(WET)in radio frequency(RF),some energy receivers(ERs),and a cloud server.By implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices,we robustly manage their energy storage.The experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.

Potential Transmission Choice for Internet of Things(IoT):Wireless and Batteryless Communications and Open Problems

The 5th generation mobile communications aims at connecting everything and future Internet of Things(IoT)will get everything smartly connected.To realize it,there exist many challenges.One key challenge is the battery problem for small devices,such as sensors or tags.Batteryless backscatter,also referred to as or battery-free backscatter,is a new potential technology to address this problem.One early and typical type of batteryless backscatter is ambient backscatter.Generally,batteryless backscatter utilizes environmental wireless signals to enable battery-free devices to communicate with each other.These devices first harvest energy from ambient wireless signals and then backscatter these signals so as to transmit their own information.This paper reviews the current studies about batteryless backscatter,including various backscatter schemes and theoretical works,and then introduces open problems for future research.

A 20.8-Gbps Dual-Carrier Wireless Communication Link in 220-GHz Band

With the successful demonstration of terahertz(THz)high-speed wireless data transmission,the THz frequencies are now becoming a worth candidate for post-5G wireless communications.On the other hand,to bring THz communications a step closer to real scenario application,solving high data rate realtime transmission is also an important issue.This paper describes a 220-GHz solid-state dual-carrier wireless link whose maximum transmission real-time data rates are 20.8 Gbps(10.4 Gbps per channel).By aggregating two carrier signals in the THz band,the contradiction between high real-time data rate communication and low sampling rate analog-to-digital(ADC)and digital-to-analog converter(DAC)is alleviated.The transmitting and receiving front-ends consist of 220-GHz diplexers,220-GHz sub-harmonic mixers based on anti-parallel Schottky barrier diodes,G-band low-noise amplifiers(LNA),WR-4.3 band high-gain Cassegrain antennas,high data rates dual-DAC and-ADC baseband platform and other components.The low-density parity-check(LDPC)encoding is also realized to improve the bit error rate(BER)of the received signal.Modulated signals are centered at 214.4 GHz and 220.6 GHz with-11.9 dBm and-13.4 dBm output power for channel 1 and 2,respectively.This link is demonstrated to achieve 20.8-Gbps real-time data transmission using 16-QAM modulation over a distance of 1030 m.The measured signal to noise ratio(SNR)is 17.3 dB and 16.5 dB,the corresponding BER is 8.6e-7 and 3.8e-7,respectively.Furthermore,4K video transmission is also carried out which is clear and free of stutter.The successful transmission of aggregated channels in this wireless link shows the great potential of THz communication for future wireless high-rate real-time data transmission applications.

Multi-narrowband signals receiving method based on analog-to-information convertor and block sparsity

The analog-to-information convertor (AIC) is a successful practice of compressive sensing (CS) theory in the analog signal acquisition. This paper presents a multi-narrowband signals sampling and reconstruction model based on AIC and block sparsity. To overcome the practical problems, the block sparsity is divided into uniform block and non-uniform block situations, and the block restricted isometry property and sub-sampling limit in different situations are analyzed respectively in detail. Theoretical analysis proves that using the block sparsity in AIC can reduce the restricted isometric constant, increase the reconstruction probability and reduce the sub -sampling rate. Simulation results show that the proposed model can complete sub -sampling and reconstruction for multi-narrowband signals. This paper extends the application range of AIC from the finite information rate signal to the multi-narrowband signals by using the potential relevance of support sets. The proposed receiving model has low complexity and is easy to implement, which can promote the application of CS theory in the radar receiver to reduce the burden of analog-to digital convertor (ADC) and solve bandwidth limitations of ADC.

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.

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.

Multiple Vandermonde Decomposition Based Channel Estimation for Mm Wave MIMO High-Mobility Communication in 5G and Beyond

Millimeter wave(mmWave)massive massive multiple input multiple output(MIMO)technique has been regarded as the viable solution for vehicular communications in 5G and beyond.To achieve the substantial increase in date rates,it is important to take an effective channel state information(CSI).However,existing channel estimation strategies are unavailable since the users high-mobility.To solve above issues,in this paper,inspired by a specific antenna structure,we propose a novel approach for fast time-varying channel estimation.Specifically,by considering the vehicle scenario with high-mobility,a corresponding mathematical model is firstly established.Then,based on the special structural of the sparse array,the switch network is used to replace the convention phase shifter of mmWave hybrid system,which can effectively reduce the number of radio-frequency(RF)chains and antennas.Furthermore,by solving the semidefinite programming(SDP)duality problem,the Doppler frequency and path parameters are effectively estimated.Simulation results are shown that the computational complexity and estimation accuracy of the proposed algorithm is superior than that of the traditional schemes.

Jitter Enhanced Full Digital RF Transmitter and PWM RFPA for 5G Broadband Communications

RFPA(radio frequency power amplifier)based on PWM(pulse width modulation)can be perfect linear without using complicated DPD(digital pre-distortion)hardware.However,PWM RFPA need ultra-high PWM time resolution(less than 10 ps)for wide-band 5G,which is limited by CMOS technologies(can reach 40 ps).It limits the complexity of modulation so that PWM RFPA cannot be really commercialized so far in wideband radio/mobile technologies.This paper presents our contribution by introducing jitter into PWM.For the first time,we demonstrate that jitter can improve the PWM time resolution equivalently reaching less than 2.6 ps.Hence PWM RFPA can be used in 5G supporting 256QAM OFDM modulation based on currently available digital CMOS technologies.We demonstrate that jitter can refine the inherent resolution of PWM hardware circuit modulation.The jitter makes the MCS(modulation and coding scheme)of the bandwidth OFDM system improved from 16QAM to 256QAM in the band n28 of 3GPP 38.101.We also verified that 5G 256QAM OFDM modulation is achievable in the 3GPP band n20,Softbank band28 and NTT Docomo band28.The RMS EVM(root mean square error vector magnitude)of 256QAM OFDM modulation is about-44 dB.

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.

Bit-Level Composite Signal Design for Simultaneous Ranging and Communication

As the complexity of space exploration missions augments,how to enhance the overall performance of communication,ranging or other functions has become a challengeable problem.Considering the integration of communication and ranging,we present a bit-level composite signal for simultaneous ranging and communication.In this composite method,through a specially designed mapping scheme using low-weight codewords,the information sequence is converted to a sparse sequence which is then superimposed on the ranging code.For ranging,the correlation characteristics of the ranging code component can be maintained to calculate the transmitter-receiver distance.For communications,the sparse sequence can be extracted without interference by eliminating the ranging code component.Simulation results show that the proposed composite signal can support communication and ranging simultaneously with limited sacrifice of ranging performance,and the performance loss of ranging can be controlled and minimized by lowering the density of information sequences using different sparsification encoding methods.

A Brief Introduction on Joint Radar and Communication Systems

Joint radar and communication(JRC)technology is gradually becoming an essential approach to alleviating spectral congestion.Radar and communications systems were designed with common spectral and hardware resources to reduce size,improve performance,reduce cost,and decongest the spectrum.Various approaches have been proposed to achieve the coexistence of radar and communication systems.This paper mainly focuses on the research directions of radar communication coexistence(RCC)and dual-function radar communication systems(DFRC)in JRC technology.We summarize and analyze the existing research problems in the JRC era.According to the characteristics and advantages of JRC technology,we highlight several potentials in military and commercial applications.

RIS Assisted Dual-Function Radar and Secure Communications Based on Frequency-Shifted Chirp Spread Spectrum Index Modulation

Reconfigurable intelligent surface(RIS)assisted dual-function radar communications(DFRC)system is a promising integrated sensing and communication(ISAC)technology for future 6G.In this paper,we propose a scheme of RIS-assisted DFRC system based on frequency shifted chirp spread spectrum index modulation(RDFI)for secure communications.The proposed RDFI achieves the sensing and transmission of target location information in its radar and communication modes,respectively.In both modes,the frequency-shifted chirp spread spectrum index modulation(FSCSS-IM)signal is used as the baseband signal for radar and communications,so that the signal sent by the radar also carries information.This scheme implements the RIS-assisted beamforming in the communication mode through the azimuth information of the target acquired in the radar mode,so that the signal received from the eavesdropper is distorted in amplitude and phase.In addition,this paper analyzes the radar measurement accuracy and communication security of the FSCSS-IM signal using ambiguity function and secrecy rate(SR)analysis,respectively.Simulation results show that RDFI achieves both excellent bit error rate(BER)performance and physical layer security of communications.

Dual-Use Signal Design for Radar and Communication via Joint Orthogonal Signal and Phase Modulation

This paper proposes a new information modulation resorting to orthogonal signal and its phase for dual-function radar communication(DFRC)systems.Focusing on the standardized linear frequency modulation(LFM)signal by additional phase,a bank of signals enjoying satisfactory autocorrelation and cross-correlation characteristics,are generated.Then,these signals map the different information as well as their phases are also modulated to increase the communication bit rate,thus yielding a series of dual-use signals.Finally,the radar detection and communication performance of dual-use signals are also provided through numerical simulation and half-physical platform verification,confirming the effectiveness of the designed signals compared with the existing design strategy.

Performance Analysis of Multiband Impulse Radio UWB Communication System Based on PSWF

To improve the data transmission rate and use spectrum flexibly, a new spectrum allocation method for Multiband Impulse Radio UWB (MB-IR-UWB) is proposed in this paper based on the band-limited and orthogonal characteristics of Prolate Spheroidal Wave Function (PSWF). The system model is built and the bit error rate (BER) formula is deprived by binary time hopping pulse position modulation under additive white Gaussian noise. Moreover, the system performance is analyzed via MATLB simulation. The results indicate that MB-IR-UWB system performance of BER is the same with single-band UWB. However, in the proposed scheme the data can be transmitted in multiple parallel bands, which enjoys much higher transmission rate. In addition, PSWF pulse duration affects the BER performance.

A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational efficiency.As technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process.In this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing accuracy.Initially,features are extracted by the VGG19 convolutional block.Then,after processing through the GAP layer,the extracted features are fed to the SVM classifier for classification.For this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the datasets.The outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS dataset.Similarly,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.