Construction of Software Design and Programming Practice Course in Information and Communication Engineering

Innovation and entrepreneurship education is becoming one of the important goals of higher education in China.According to the requirements of the Ministry of Education to deepen the reform of innovation and entrepreneur-ship education in colleges and universities,we propose a core principle of“from basis to comprehensiveness,and then to innovation”to construct the software design and programming practice course in the information and communication engineering discipline.We have integrated specialized knowledge teaching with innovation and entrepreneurship training,implemented a series of experimental projects that integrate theory with practice,and explored mixed teaching methods and diversified examination methods.In this paper,details about software design and programming practice course construction are shown from aspects of teaching content,teaching methods,and examination methods.These course construction experiences will benefit teachers who engage in innovative practical courses in the information and communication engineering discipline.

Probe into the course teaching reform of ＂communication engineering budget＂

＂Communication project budget＂ is a professional course of the communication engineering specialty. Combined with the requirements of the teaching reform, from three aspects of the theoretical teaching, the experimental teaching, and the engineering practice, the author carries on the reform and practice, to cultivate the active thinking and practical ability of the students, and the effects of the re-form are fully in line with the orientation of cultivating the highly-skillful and applied talents.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.

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.

Energy-Efficient Implementation of BCD to Excess-3 Code Converter for Nano-Communication Using QCA Technology

Code converters are essential in digital nano communication;therefore,a low-complexity optimal QCA layout for a BCD to Excess-3 code converter has been proposed in this paper.A QCA clockphase-based design technique was adopted to investigate integration with other complicated circuits.Using a unique XOR gate,the recommended circuit’s cell complexity has been decreased.The findings produced using the QCADesigner-2.0.3,a reliable simulation tool,prove the effectiveness of the current structure over earlier designs by considering the number of cells deployed,the area occupied,and the latency as design metrics.In addition,the popular tool QCAPro was used to estimate the energy dissipation of the proposed design.The proposed technique reduces the occupied space by∼40%,improves cell complexity by∼20%,and reduces energy dissipation by∼1.8 times(atγ=1.5EK)compared to the current scalable designs.This paper also studied the suggested structure’s energy dissipation and compared it to existing works for a better performance evaluation.

A tensile wearable SHF antenna with efficient communication in defense beacon technology

The study projects a flexible and compact wearable pear-shaped Super High Frequency(SHF)antenna that can provide detailed location recognition and tracking applicable to defense beacon technology.This mini aperture with electrical dimensions of 0.12λ_(0)×0.22λ_(0)×0.01λ_(0)attains a vast bandwidth over 3.1-34.5 GHz Super High Frequency(SHF)frequency band at S_(11)≤-10 dB,peak gain of 7.14 dBi and proportionately homogeneous radiation pattern.The fractional bandwidth(%BW)acquired is 168%that envelopes diversified frequency spectrum inclusive of X band specifically targeted to all kinds of defense and military operations.The proposed antenna can be worn on a soldier's uniform and hence the Specific Absorption Rate simulation is accomplished.The Peak SAR Value over 1 g of tissue is 1.48 W/kg and for 10 g of tissue is 0.27 W/kg well under the safety standards.The flexibility is proven by analyzing the full electromagnetic simulations for various bending conditions.Time response analysis is attained with its Fidelity Factor and Group Delay.Communication excellence is determined using Link Budget Analysis and it is seen that margin at 100 Mbps is 62 m and at 200 Mbps is 59 m.Prototype is fabricated along with experimental validation.All the results show harmony in shaping the antenna to provide critical situational awareness and data sharing capabilities required in defense beacon technology for location identification.

Joint Optimization for on-Demand Deployment of UAVs and Spectrum Allocation in UAVs-Assisted Communication

To improve the efficiency and fairness of the spectrum allocation for ground communication assisted by unmanned aerial vehicles(UAVs),a joint optimization method for on-demand deployment and spectrum allocation of UAVs is proposed,which is modeled as a mixed-integer non-convex optimization problem(MINCOP).An algorithm to estimate the minimum number of required UAVs is firstly proposed based on the pre-estimation and simulated annealing.The MINCOP is then decomposed into three sub-problems based on the block coordinate descent method,including the spectrum allocation of UAVs,the association between UAVs and ground users,and the deployment of UAVs.Specifically,the optimal spectrum allocation is derived based on the interference mitigation and channel reuse.The association between UAVs and ground users is optimized based on local iterated optimization.A particle-based optimization algorithm is proposed to resolve the subproblem of the UAVs deployment.Simulation results show that the proposed method could effectively improve the minimum transmission rate of UAVs as well as user fairness of spectrum allocation.

Covert LEO Satellite Communication Aided by Generative Adversarial Network Based Cooperative UAV Jamming

In this paper,we study the covert performance of the downlink low earth orbit(LEO)satellite communication,where the unmanned aerial vehicle(UAV)is employed as a cooperative jammer.To maximize the covert rate of the LEO satellite transmission,a multi-objective problem is formulated to jointly optimize the UAV’s jamming power and trajectory.For practical consideration,we assume that the UAV can only have partial environmental information,and can’t know the detection threshold and exact location of the eavesdropper on the ground.To solve the multiobjective problem,we propose the data-driven generative adversarial network(DD-GAN)based method to optimize the power and trajectory of the UAV,in which the sample data is collected by using genetic algorithm(GA).Simulation results show that the jamming solution of UAV generated by DD-GAN can achieve an effective trade-off between covert rate and probability of detection errors when only limited prior information is obtained.

A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is paramount.As cyber threats evolve in complexity,traditional cryptographic methods face increasingly sophisticated challenges.This article initiates an exploration into these challenges,focusing on key exchanges(encompassing their variety and subtleties),scalability,and the time metrics associated with various cryptographic processes.We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering.Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity,foundational pillars of information security.Our method employs a phased strategy,beginning with a detailed examination of traditional cryptographic processes,including Elliptic Curve Diffie-Hellman(ECDH)key exchanges.We also delve into encrypt/decrypt paradigms,signature generation modes,and the hashes used for Message Authentication Codes(MACs).Each process is rigorously evaluated for performance and reliability.To gain a comprehensive understanding,a meticulously designed simulation was conducted,revealing the strengths and potential improvement areas of various techniques.Notably,our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs,marking a significant advancement over existing methods.Furthermore,with integrity metrics at 9.35,the protocol’s resilience is further affirmed.These metrics,derived from stringent testing,underscore the protocol’s efficacy in enhancing data security.

Novel Sum-of-Sinusoids Simulation Channel Modeling for 6G Multiple-Input Multiple-Output Vehicle-to-Everything Communications

In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.

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.

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.

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.

AI-Driven Resource and Communication-Aware Virtual Machine Placement Using Multi-Objective Swarm Optimization for Enhanced Efficiency in Cloud-Based Smart Manufacturing

Cloud computing has emerged as a vital platform for processing resource-intensive workloads in smart manu-facturing environments,enabling scalable and flexible access to remote data centers over the internet.In these environments,Virtual Machines(VMs)are employed to manage workloads,with their optimal placement on Physical Machines(PMs)being crucial for maximizing resource utilization.However,achieving high resource utilization in cloud data centers remains a challenge due to multiple conflicting objectives,particularly in scenarios involving inter-VM communication dependencies,which are common in smart manufacturing applications.This manuscript presents an AI-driven approach utilizing a modified Multi-Objective Particle Swarm Optimization(MOPSO)algorithm,enhanced with improved mutation and crossover operators,to efficiently place VMs.This approach aims to minimize the impact on networking devices during inter-VM communication while enhancing resource utilization.The proposed algorithm is benchmarked against other multi-objective algorithms,such as Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),demonstrating its superiority in optimizing resource allocation in cloud-based environments for smart manufacturing.

Age of Information for Short-Packet Covert Communication with Time Modulated Retrodirective Array

In this paper,the covert age of information(CAoI),which characterizes the timeliness and covertness performance of communication,is first investigated in the short-packet covert communication with time modulated retrodirective array(TMRDA).Specifically,the TMRDA is designed to maximize the antenna gain in the target direction while the side lobe is sufficiently suppressed.On this basis,the covertness constraint and CAoI are derived in closed form.To facilitate the covert transmission design,the transmit power and block-length are jointly optimized to minimize the CAoI,which demonstrates the trade-off between covertness and timelessness.Our results illustrate that there exists an optimal block-length that yields the minimum CAoI,and the presented optimization results can achieve enhanced performance compared with the fixed block-length case.Additionally,we observe that smaller beam pointing error at Bob leads to improvements in CAoI.

Variational Neural Inference Enhanced Text Semantic Communication System

Recently,deep learning-based semantic communication has garnered widespread attention,with numerous systems designed for transmitting diverse data sources,including text,image,and speech,etc.While efforts have been directed toward improving system performance,many studies have concentrated on enhancing the structure of the encoder and decoder.However,this often overlooks the resulting increase in model complexity,imposing additional storage and computational burdens on smart devices.Furthermore,existing work tends to prioritize explicit semantics,neglecting the potential of implicit semantics.This paper aims to easily and effectively enhance the receiver's decoding capability without modifying the encoder and decoder structures.We propose a novel semantic communication system with variational neural inference for text transmission.Specifically,we introduce a simple but effective variational neural inferer at the receiver to infer the latent semantic information within the received text.This information is then utilized to assist in the decoding process.The simulation results show a significant enhancement in system performance and improved robustness.

High performance receiving and processing technology in satellite beam hopping communication

Beam-hopping technology has become one of the major research hotspots for satellite communication in order to enhance their communication capacity and flexibility.However,beam hopping causes the traditional continuous time-division multiplexing signal in the forward downlink to become a burst signal,satellite terminal receivers need to solve multiple key issues such as burst signal rapid synchronization and high-per-formance reception.Firstly,this paper analyzes the key issues of burst communication for traffic signals in beam hopping sys-tems,and then compares and studies typical carrier synchro-nization algorithms for burst signals.Secondly,combining the requirements of beam-hopping communication systems for effi-cient burst and low signal-to-noise ratio reception of downlink signals in forward links,a decoding assisted bidirectional vari-able parameter iterative carrier synchronization technique is pro-posed,which introduces the idea of iterative processing into car-rier synchronization.Aiming at the technical characteristics of communication signal carrier synchronization,a new technical approach of bidirectional variable parameter iteration is adopted,breaking through the traditional understanding that loop struc-tures cannot adapt to low signal-to-noise ratio burst demodula-tion.Finally,combining the DVB-S2X standard physical layer frame format used in high throughput satellite communication systems,the research and performance simulation are con-ducted.The results show that the new technology proposed in this paper can significantly shorten the carrier synchronization time of burst signals,achieve fast synchronization of low signal-to-noise ratio burst signals,and have the unique advantage of flexible and adjustable parameters.

A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

The efficient transmission of images,which plays a large role inwireless communication systems,poses a significant challenge in the growth of multimedia technology.High-quality images require well-tuned communication standards.The Single Carrier Frequency Division Multiple Access(SC-FDMA)is adopted for broadband wireless communications,because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio(PAPR).Data transmission through open-channel networks requires much concentration on security,reliability,and integrity.The data need a space away fromunauthorized access,modification,or deletion.These requirements are to be fulfilled by digital image watermarking and encryption.This paper ismainly concerned with secure image communication over the wireless SC-FDMA systemas an adopted communication standard.It introduces a robust image communication framework over SC-FDMA that comprises digital image watermarking and encryption to improve image security,while maintaining a high-quality reconstruction of images at the receiver side.The proposed framework allows image watermarking based on the Discrete Cosine Transform(DCT)merged with the Singular Value Decomposition(SVD)in the so-called DCT-SVD watermarking.In addition,image encryption is implemented based on chaos and DNA encoding.The encrypted watermarked images are then transmitted through the wireless SC-FDMA system.The linearMinimumMean Square Error(MMSE)equalizer is investigated in this paper to mitigate the effect of channel fading and noise on the transmitted images.Two subcarrier mapping schemes,namely localized and interleaved schemes,are compared in this paper.The study depends on different channelmodels,namely PedestrianAandVehicularA,with a modulation technique namedQuadratureAmplitude Modulation(QAM).Extensive simulation experiments are conducted and introduced in this paper for efficient transmission of encrypted watermarked images.In addition,different variants of SC-FDMA based on the Discrete Wavelet Transform(DWT),Discrete Cosine Transform(DCT),and Fast Fourier Transform(FFT)are considered and compared for the image communication task.The simulation results and comparison demonstrate clearly that DWT-SC-FDMAis better suited to the transmission of the digital images in the case of PedestrianAchannels,while the DCT-SC-FDMA is better suited to the transmission of the digital images in the case of Vehicular A channels.