Airborne pulse radar and communication systems are essential for precise detection and collision avoidance,ensuring that aircraft operate safely and efficiently.A major challenge in spectrum sharing is the allocation ...Airborne pulse radar and communication systems are essential for precise detection and collision avoidance,ensuring that aircraft operate safely and efficiently.A major challenge in spectrum sharing is the allocation of resources in both the time and frequency domains,aiming to minimize inter-system interference as the available spectrum fluctuates over time.In this paper,regarding maximization of detection probability and spectrum utilization efficiency as two fundamental objectives,a novel Dynamic Spectrum and Power Allocation based on Genetic Algorithm(GA-DSPA)model is proposed,which dynamically allocates communication channel frequency and power under the constraints of pulse radar detection probability and signal-to-interferenceplus-noise ratio of communication.To solve this bi-objective model,a non-dominated sortingbased multi-objective genetic algorithm is developed.A novel environment perception strategy and offspring sorting technique based on radar echoes are integrated into the optimization framework.Simulation results indicate that by integrating environmental monitoring mechanisms and dynamic adaptation strategies,the proposed method effectively tracks the evolving Paretooptimal Fronts(Po Fs),thereby ensuring optimal performance for both co-located pulse radar and communication systems.Hardware test results confirm that within the GA-DSPA framework,the pulse radar achieves higher detection probabilities under identical conditions,while the communication system realizes increased average throughput.展开更多
Symmetric encryption algorithms learned by the previous proposed end-to-end adversarial network encryption communication systems are deterministic.With the same key and same plaintext,the deterministic algorithm will ...Symmetric encryption algorithms learned by the previous proposed end-to-end adversarial network encryption communication systems are deterministic.With the same key and same plaintext,the deterministic algorithm will lead to the same ciphertext.This means that the key in the deterministic encryption algorithm can only be used once,thus the encryption is not practical.To solve this problem,a nondeterministic symmetric encryption end-to-end communication system based on generative adversarial networks is proposed.We design a nonce-based adversarial neural network model,where a“nonce”standing for“number used only once”is passed to communication participants,and does not need to be secret.Moreover,we optimize the network structure through adding Batch Normalization(BN)to the CNNs(Convolutional Neural Networks),selecting the appropriate activation functions,and setting appropriate CNNs parameters.Results of experiments and analysis show that our system can achieve non-deterministic symmetric encryption,where Alice encrypting the same plaintext with the key twice will generate different ciphertexts,and Bob can decrypt all these different ciphertexts of the same plaintext to the correct plaintext.And our proposed system has fast convergence and the correct rate of decryption when the plaintext length is 256 or even longer.展开更多
Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,th...Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.展开更多
The utilization of unmanned aerial vehicle(UAV) relays in cooperative communication has gained considerable attention in recent years.However,the current research is mostly based on fixed base stations and users,lacki...The utilization of unmanned aerial vehicle(UAV) relays in cooperative communication has gained considerable attention in recent years.However,the current research is mostly based on fixed base stations and users,lacking sufficient exploration of scenarios where communication nodes are in motion.This paper presents a multi-destination vehicle communication system based on decode-and-forward(DF)UAV relays,where source and destination vehicles are moving and an internal eavesdropper intercepts messages from UAV.The closed-form expressions for system outage probability and secrecy outage probability are derived to analyze the reliability and security of the system.Furthermore,the impact of the UAV's position,signal transmission power,and system time allocation ratio on the system's performance are also analyzed.The numerical simulation results validate the accuracy of the derived formulas and confirm the correctness of the analysis.The appropriate time allocation ratio significantly enhances the security performance of system under various environmental conditions.展开更多
High reliability applications in dense access scenarios have become one of the main goals of 6G environments.To solve the access collision of dense Machine Type Communication(MTC)devices in cell-free communication sys...High reliability applications in dense access scenarios have become one of the main goals of 6G environments.To solve the access collision of dense Machine Type Communication(MTC)devices in cell-free communication systems,an intelligent cooperative secure access scheme based on multi-agent reinforcement learning and federated learning is proposed,that is,the Preamble Slice Orderly Queue Access(PSOQA)scheme.In this scheme,the preamble arrangement is combined with the access control.The preamble arrangement is realized by preamble slices which is from the virtual preamble pool.The access devices learn to queue orderly by deep reinforcement learning.The orderly queue weakens the random and avoids collision.A preamble slice is assigned to an orderly access queue at each access time.The orderly queue is determined by interaction information among multiple agents.With the federated reinforcement learning framework,the PSOQA scheme is implemented to guarantee the privacy and security of agents.Finally,the access performance of PSOQA is compared with other random contention schemes in different load scenarios.Simulation results show that PSOQA can not only improve the access success rate but also guarantee low-latency tolerant performances.展开更多
Backscatter communication(BC)is con-sidered a key technology in self-sustainable commu-nications,and the unmanned aerial vehicle(UAV)as a data collector can improve the efficiency of data col-lection.We consider a UAV...Backscatter communication(BC)is con-sidered a key technology in self-sustainable commu-nications,and the unmanned aerial vehicle(UAV)as a data collector can improve the efficiency of data col-lection.We consider a UAV-aided BC system,where the power beacons(PBs)are deployed as dedicated radio frequency(RF)sources to supply power for backscatter devices(BDs).After harvesting enough energy,the BDs transmit data to the UAV.We use stochastic geometry to model the large-scale BC sys-tem.Specifically,the PBs are modeled as a type II Mat´ern hard-core point process(MHCPP II)and the BDs are modeled as a homogeneous Poisson point process(HPPP).Firstly,the BDs’activation proba-bility and average coverage probability are derived.Then,to maximize the energy efficiency(EE),we opti-mize the RF power of the PBs under different PB den-sities.Furthermore,we compare the coverage proba-bility and EE performance of our system with a bench-mark scheme,in which the distribution of PBs is mod-eled as a HPPP.Simulation results show that the PBs modeled as MHCPP II has better performance,and we found that the higher the density of PBs,the smaller the RF power required,and the EE is also higher.展开更多
The performance of traditional regular Intelligent Reflecting Surface(IRS)improves as the number of IRS elements increases,but more reflecting elements lead to higher IRS power consumption and greater overhead of chan...The performance of traditional regular Intelligent Reflecting Surface(IRS)improves as the number of IRS elements increases,but more reflecting elements lead to higher IRS power consumption and greater overhead of channel estimation.The Irregular Intelligent Reflecting Surface(IIRS)can enhance the performance of the IRS as well as boost the system performance when the number of reflecting elements is limited.However,due to the lack of radio frequency chain in IRS,it is challenging for the Base Station(BS)to gather perfect Channel State Information(CSI),especially in the presence of Eavesdroppers(Eves).Therefore,in this paper we investigate the minimum transmit power problem of IIRS-aided Simultaneous Wireless Information and Power Transfer(SWIPT)secure communication system with imperfect CSI of BS-IIRS-Eves links,which is subject to the rate outage probability constraints of the Eves,the minimum rate constraints of the Information Receivers(IRs),the energy harvesting constraints of the Energy Receivers(ERs),and the topology matrix constraints.Afterward,the formulated nonconvex problem can be efficiently tackled by employing joint optimization algorithm combined with successive refinement method and adaptive topology design method.Simulation results demonstrate the effectiveness of the proposed scheme and the superiority of IIRS.展开更多
To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase n...To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.展开更多
Sparse code multiple access(SCMA)is a non-orthogonal multiple access(NOMA)scheme based on joint modulation and spread spectrum coding.It is ideal for future communication networks with a massive number of nodes due to...Sparse code multiple access(SCMA)is a non-orthogonal multiple access(NOMA)scheme based on joint modulation and spread spectrum coding.It is ideal for future communication networks with a massive number of nodes due to its ability to handle user overload.Introducing SCMA into visible light communication(VLC)systems can improve the data transmission capability of the system.However,designing a suitable codebook becomes a challenging problem when addressing the demands of massive connectivity scenarios.Therefore,this paper proposes a low-complexity design method for high-overload codebooks based on the minimum bit error rate(BER)criterion.Firstly,this paper constructs a new codebook with parameters based on the symmetric mother codebook structure by allocating the codeword power so that the power of each user codebook is unbalanced;then,the BER performance in the visible light communication system is optimized to obtain specific parameters;finally,the successive interference cancellation(SIC)detection algorithm is used at the receiver side.Simulation results show that the method proposed in this paper can converge quickly by utilizing a relatively small number of detection iterations.This can simultaneously reduce the complexity of design and detection,outperforming existing design methods for massive SCMA codebooks.展开更多
In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its as...In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.展开更多
Reconfigurable intelligent surfaces(RISs)with the capability of nearly passive beamforming,have recently sparked considerable interests.This paper presents an energy-efficient discrete phase encoding method for RIS-as...Reconfigurable intelligent surfaces(RISs)with the capability of nearly passive beamforming,have recently sparked considerable interests.This paper presents an energy-efficient discrete phase encoding method for RIS-assisted communication systems.Firstly,the beamforming gain,power consumption and energy efficiency models for the RIS-assisted system are illustrated.On this basis,the discrete phase encoding problem is formulated for the purpose of improving the energy efficiency,under the power constraint and the quality-of-service(QoS)requirement.According to the interrelation between the phase encoding and power consumption,a three-step encoding method is proposed with the capability of customizing the beamforming gain,power consumption,and energy efficiency.Simulation results indicate that the proposed method is capable of achieving a more favorable performance in terms of satisfying the QoS demand,reducing the power consumption,and improving the energy efficiency.Furthermore,two field trials at 35 GHz evidence the superiority performance and feasibility characteristics of the proposed method in real environment.This work may provide a reference for future applications of RIS-assisted system with an energy-efficient manner.展开更多
The resource allocation technique is of great significance in achieving frequency spectrum coexistence in Joint Radar-Communication(JRC) systems, by which the problem of radio frequency spectrum congestion can be well...The resource allocation technique is of great significance in achieving frequency spectrum coexistence in Joint Radar-Communication(JRC) systems, by which the problem of radio frequency spectrum congestion can be well alleviated. A Robust Joint Frequency Spectrum and Power Allocation(RJFSPA) strategy is proposed for the Coexisting Radar and Communication(CRC)system. Specifically, we consider the uncertainty of target Radar Cross Section(RCS) and communication channel gain to formulate a bi-objective optimization model. The joint probabilities that the Cramér-Rao Lower Bound(CRLB) of each target satisfying the localization accuracy threshold and the Communication Data Ratio(CDR) of each user satisfying the communication threshold are simultaneously maximized, under the constraint of the total power budget. A Three-Stage Alternating Optimization Method(TSAOM) is proposed to obtain the Best-Known Pareto Subset(BKPS) of this problem, where the frequency spectrum, radar power, and communicator power are allocated using the greedy search and standard convex optimization methods, respectively. Simulation results confirm the effectiveness of the proposed RJFSPA strategy, compared with the resource allocation methods in a uniform manner and that ignores the uncertainties. The efficiency of the TSAOM is also verified by the comparison with the exhaustive search-based method.展开更多
With the rapid development of information technology,5G communication technology has gradually entered real life,among which the application of edge computing is particularly significant in the information and communi...With the rapid development of information technology,5G communication technology has gradually entered real life,among which the application of edge computing is particularly significant in the information and communication system field.This paper focuses on using edge computing based on 5G communication in information and communication systems.First,the study analyzes the importance of combining edge computing technology with 5G communication technology,and its advantages,such as high efficiency and low latency in processing large amounts of data.The study then explores multiple application scenarios of edge computing in information and communication systems,such as integrated use in the Internet of Things,intelligent transportation,telemedicine and Industry 4.0.The research method is mainly based on theoretical analysis and experimental verification,combined with the characteristics of the 5G network to optimize the edge computing model and test the performance of edge computing in different scenarios through experimental simulation.The results show that edge computing significantly improves the data processing capacity and response speed of ICS in a 5G environment.However,there are also a series of challenges in practical application,including data security and privacy protection,the complexity of resource management and allocation,and the guarantee of quality of service(QoS).Through the case analysis and problem analysis,the paper puts forward the corresponding solution strategies,such as strengthening the data security protocol,introducing the intelligent resource scheduling system and establishing a multi-dimensional service quality monitoring mechanism.Finally,this study points out that the deep integration of edge computing and 5G communication will continue to promote the innovative development of information and communication systems,which has a far-reaching impact and important practical significance for promoting the transformation and upgrading in the field of information technology.展开更多
Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be co...Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.展开更多
With the rapid development of artificial intelligence and the widespread use of the Internet of Things, semantic communication, as an emerging communication paradigm, has been attracting great interest. Taking image t...With the rapid development of artificial intelligence and the widespread use of the Internet of Things, semantic communication, as an emerging communication paradigm, has been attracting great interest. Taking image transmission as an example, from the semantic communication's view, not all pixels in the images are equally important for certain receivers. The existing semantic communication systems directly perform semantic encoding and decoding on the whole image, in which the region of interest cannot be identified. In this paper, we propose a novel semantic communication system for image transmission that can distinguish between Regions Of Interest (ROI) and Regions Of Non-Interest (RONI) based on semantic segmentation, where a semantic segmentation algorithm is used to classify each pixel of the image and distinguish ROI and RONI. The system also enables high-quality transmission of ROI with lower communication overheads by transmissions through different semantic communication networks with different bandwidth requirements. An improved metric θPSNR is proposed to evaluate the transmission accuracy of the novel semantic transmission network. Experimental results show that our proposed system achieves a significant performance improvement compared with existing approaches, namely, existing semantic communication approaches and the conventional approach without semantics.展开更多
The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backsca...The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.展开更多
In this paper,the eavesdropping model based on eavesdroppers near legitimate users,and the effect of atmospheric channel correlation on the physical layer security(PLS)of the free-space optical(FSO)link are analyzed.A...In this paper,the eavesdropping model based on eavesdroppers near legitimate users,and the effect of atmospheric channel correlation on the physical layer security(PLS)of the free-space optical(FSO)link are analyzed.According to the joint probability density function(PDF)and cumulative distribution function(CDF)of Gamma-Gamma(G-G)distribution,a new closed-form expression of interception probability is derived.Numerical results show that the interception probability of the FSO system depends on turbulence intensity,channel correlation and radial displacement attenuation of eavesdroppers.展开更多
Performance of non-line-of-sight(NLOS)ultraviolet(UV)communication is closely related with the communication range,system geometry and the atmosphere aerosol properties.In this paper,we investigate the path loss of th...Performance of non-line-of-sight(NLOS)ultraviolet(UV)communication is closely related with the communication range,system geometry and the atmosphere aerosol properties.In this paper,we investigate the path loss of the NLOS UV communication systems in both monodisperse and polydisperse aerosol systems based on the Monte-Carlo method.展开更多
The concept of semantic communication provides a novel approach for applications in scenarios with limited communication resources.In this paper,we propose an end-to-end(E2E)semantic molecular communication system,aim...The concept of semantic communication provides a novel approach for applications in scenarios with limited communication resources.In this paper,we propose an end-to-end(E2E)semantic molecular communication system,aiming to enhance the efficiency of molecular communication systems by reducing the transmitted information.Specifically,following the joint source channel coding paradigm,the network is designed to encode the task-relevant information into the concentration of the information molecules,which is robust to the degradation of the molecular communication channel.Furthermore,we propose a channel network to enable the E2E learning over the non-differentiable molecular channel.Experimental results demonstrate the superior performance of the semantic molecular communication system over the conventional methods in classification tasks.展开更多
Context information is significant for semantic extraction and recovery of messages in semantic communication.However,context information is not fully utilized in the existing semantic communication systems since re-l...Context information is significant for semantic extraction and recovery of messages in semantic communication.However,context information is not fully utilized in the existing semantic communication systems since re-lationships between sentences are often ignored.In this paper,we propose an Extended Context-based Semantic Communication(ECSC)system for text transmission,in which context information within and between sentences is explored for semantic representation and recovery.At the encoder,self-attention and segment-level relative attention are used to extract context information within and between sentences,respectively.In addition,a gate mechanism is adopted at the encoder to incorporate the context information from different ranges.At the decoder,Transformer-XL is introduced to obtain more semantic information from the historical communication processes for semantic recovery.Simulation results show the effectiveness of our proposed model in improving the semantic accuracy between transmitted and recovered messages under various channel conditions.展开更多
基金co-supported by the National Natural Science Foundation of China(No.62293495)the National Key Research and Development Program of China(No.2023YFB3306900)the Academic Excellence Foundation of BUAA for ph.D Students,China。
文摘Airborne pulse radar and communication systems are essential for precise detection and collision avoidance,ensuring that aircraft operate safely and efficiently.A major challenge in spectrum sharing is the allocation of resources in both the time and frequency domains,aiming to minimize inter-system interference as the available spectrum fluctuates over time.In this paper,regarding maximization of detection probability and spectrum utilization efficiency as two fundamental objectives,a novel Dynamic Spectrum and Power Allocation based on Genetic Algorithm(GA-DSPA)model is proposed,which dynamically allocates communication channel frequency and power under the constraints of pulse radar detection probability and signal-to-interferenceplus-noise ratio of communication.To solve this bi-objective model,a non-dominated sortingbased multi-objective genetic algorithm is developed.A novel environment perception strategy and offspring sorting technique based on radar echoes are integrated into the optimization framework.Simulation results indicate that by integrating environmental monitoring mechanisms and dynamic adaptation strategies,the proposed method effectively tracks the evolving Paretooptimal Fronts(Po Fs),thereby ensuring optimal performance for both co-located pulse radar and communication systems.Hardware test results confirm that within the GA-DSPA framework,the pulse radar achieves higher detection probabilities under identical conditions,while the communication system realizes increased average throughput.
基金supported by The National Defense Innovation Project(No.ZZKY20222411)Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-546).
文摘Symmetric encryption algorithms learned by the previous proposed end-to-end adversarial network encryption communication systems are deterministic.With the same key and same plaintext,the deterministic algorithm will lead to the same ciphertext.This means that the key in the deterministic encryption algorithm can only be used once,thus the encryption is not practical.To solve this problem,a nondeterministic symmetric encryption end-to-end communication system based on generative adversarial networks is proposed.We design a nonce-based adversarial neural network model,where a“nonce”standing for“number used only once”is passed to communication participants,and does not need to be secret.Moreover,we optimize the network structure through adding Batch Normalization(BN)to the CNNs(Convolutional Neural Networks),selecting the appropriate activation functions,and setting appropriate CNNs parameters.Results of experiments and analysis show that our system can achieve non-deterministic symmetric encryption,where Alice encrypting the same plaintext with the key twice will generate different ciphertexts,and Bob can decrypt all these different ciphertexts of the same plaintext to the correct plaintext.And our proposed system has fast convergence and the correct rate of decryption when the plaintext length is 256 or even longer.
基金supported by the Science and Technology Project of the State Grid Corporation of China(5400-202255158A-1-1-ZN).
文摘Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.
基金supported by the National Natural Science Foundation of China under Grants 62001359 and 61901201by the Key Science and Technology Research Project of Henan Province under Grants 232102211059the Natural Science Basic Research Program of Shaanxi under Grants 2022JQ-658 and 2022JQ-621。
文摘The utilization of unmanned aerial vehicle(UAV) relays in cooperative communication has gained considerable attention in recent years.However,the current research is mostly based on fixed base stations and users,lacking sufficient exploration of scenarios where communication nodes are in motion.This paper presents a multi-destination vehicle communication system based on decode-and-forward(DF)UAV relays,where source and destination vehicles are moving and an internal eavesdropper intercepts messages from UAV.The closed-form expressions for system outage probability and secrecy outage probability are derived to analyze the reliability and security of the system.Furthermore,the impact of the UAV's position,signal transmission power,and system time allocation ratio on the system's performance are also analyzed.The numerical simulation results validate the accuracy of the derived formulas and confirm the correctness of the analysis.The appropriate time allocation ratio significantly enhances the security performance of system under various environmental conditions.
基金supported in part by the National Natural Science Foundation of China under grants 61771255in part by the Provincial and Ministerial Key Laboratory Open Project under grant 20190904in part by the Key Technologies R&D Program of Jiangsu (Prospective and Key Technologies for Industry)under Grants BE2022067,BE2022067-1 and BE2022067-2。
文摘High reliability applications in dense access scenarios have become one of the main goals of 6G environments.To solve the access collision of dense Machine Type Communication(MTC)devices in cell-free communication systems,an intelligent cooperative secure access scheme based on multi-agent reinforcement learning and federated learning is proposed,that is,the Preamble Slice Orderly Queue Access(PSOQA)scheme.In this scheme,the preamble arrangement is combined with the access control.The preamble arrangement is realized by preamble slices which is from the virtual preamble pool.The access devices learn to queue orderly by deep reinforcement learning.The orderly queue weakens the random and avoids collision.A preamble slice is assigned to an orderly access queue at each access time.The orderly queue is determined by interaction information among multiple agents.With the federated reinforcement learning framework,the PSOQA scheme is implemented to guarantee the privacy and security of agents.Finally,the access performance of PSOQA is compared with other random contention schemes in different load scenarios.Simulation results show that PSOQA can not only improve the access success rate but also guarantee low-latency tolerant performances.
文摘Backscatter communication(BC)is con-sidered a key technology in self-sustainable commu-nications,and the unmanned aerial vehicle(UAV)as a data collector can improve the efficiency of data col-lection.We consider a UAV-aided BC system,where the power beacons(PBs)are deployed as dedicated radio frequency(RF)sources to supply power for backscatter devices(BDs).After harvesting enough energy,the BDs transmit data to the UAV.We use stochastic geometry to model the large-scale BC sys-tem.Specifically,the PBs are modeled as a type II Mat´ern hard-core point process(MHCPP II)and the BDs are modeled as a homogeneous Poisson point process(HPPP).Firstly,the BDs’activation proba-bility and average coverage probability are derived.Then,to maximize the energy efficiency(EE),we opti-mize the RF power of the PBs under different PB den-sities.Furthermore,we compare the coverage proba-bility and EE performance of our system with a bench-mark scheme,in which the distribution of PBs is mod-eled as a HPPP.Simulation results show that the PBs modeled as MHCPP II has better performance,and we found that the higher the density of PBs,the smaller the RF power required,and the EE is also higher.
基金supported in part by the Shenzhen Basic Research Program under Grant JCYJ20220531103008018,and Grants 20231120142345001 and 20231127144045001the Natural Science Foundation of China under Grant U20A20156.
文摘The performance of traditional regular Intelligent Reflecting Surface(IRS)improves as the number of IRS elements increases,but more reflecting elements lead to higher IRS power consumption and greater overhead of channel estimation.The Irregular Intelligent Reflecting Surface(IIRS)can enhance the performance of the IRS as well as boost the system performance when the number of reflecting elements is limited.However,due to the lack of radio frequency chain in IRS,it is challenging for the Base Station(BS)to gather perfect Channel State Information(CSI),especially in the presence of Eavesdroppers(Eves).Therefore,in this paper we investigate the minimum transmit power problem of IIRS-aided Simultaneous Wireless Information and Power Transfer(SWIPT)secure communication system with imperfect CSI of BS-IIRS-Eves links,which is subject to the rate outage probability constraints of the Eves,the minimum rate constraints of the Information Receivers(IRs),the energy harvesting constraints of the Energy Receivers(ERs),and the topology matrix constraints.Afterward,the formulated nonconvex problem can be efficiently tackled by employing joint optimization algorithm combined with successive refinement method and adaptive topology design method.Simulation results demonstrate the effectiveness of the proposed scheme and the superiority of IIRS.
基金supported in part by National Natural Science Foundation of China(No.62271080)in part by Fund of State Key Laboratory of IPOC(BUPT)(No.IPOC2022ZT06)in part by BUPT Excellent Ph.D Students Foundation(No.CX2022102).
文摘To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.
基金supported in part by the National Science Foundation of China(NSFC)under Grant 62161024Jiangxi Provincial Natural Science Foundation under Grant 20224BAB212002+3 种基金Jiangxi Provincial Talent Project for Academic and Technical Leaders of Major Disciplines under Grant 20232BCJ23085,China Postdoctoral Science Foundation under Grant 2021TQ0136 and 2022M711463the State Key Laboratory of Computer Architecture(ICT,CAS)Open Project under Grant CARCHB202019supported in part by the National Natural Science Foundation of China(NSFC)under Grant 62061030supported in part by the National Natural Science Foundation of China(NSFC)under Grant 62161023。
文摘Sparse code multiple access(SCMA)is a non-orthogonal multiple access(NOMA)scheme based on joint modulation and spread spectrum coding.It is ideal for future communication networks with a massive number of nodes due to its ability to handle user overload.Introducing SCMA into visible light communication(VLC)systems can improve the data transmission capability of the system.However,designing a suitable codebook becomes a challenging problem when addressing the demands of massive connectivity scenarios.Therefore,this paper proposes a low-complexity design method for high-overload codebooks based on the minimum bit error rate(BER)criterion.Firstly,this paper constructs a new codebook with parameters based on the symmetric mother codebook structure by allocating the codeword power so that the power of each user codebook is unbalanced;then,the BER performance in the visible light communication system is optimized to obtain specific parameters;finally,the successive interference cancellation(SIC)detection algorithm is used at the receiver side.Simulation results show that the method proposed in this paper can converge quickly by utilizing a relatively small number of detection iterations.This can simultaneously reduce the complexity of design and detection,outperforming existing design methods for massive SCMA codebooks.
基金supported by Beijing Natural Science Fund–Haidian Original Innovation Joint Fund(L232040 and L232045).
文摘In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.
基金supported in part by the National Natural Science Foundation of China under Grants 62231009 and 62261160576in part by the Fundamental Research Funds for the Central Universities under Grant 2242023K5003in part by the Startup Research Fund of Southeast University under Grant RF1028623267。
文摘Reconfigurable intelligent surfaces(RISs)with the capability of nearly passive beamforming,have recently sparked considerable interests.This paper presents an energy-efficient discrete phase encoding method for RIS-assisted communication systems.Firstly,the beamforming gain,power consumption and energy efficiency models for the RIS-assisted system are illustrated.On this basis,the discrete phase encoding problem is formulated for the purpose of improving the energy efficiency,under the power constraint and the quality-of-service(QoS)requirement.According to the interrelation between the phase encoding and power consumption,a three-step encoding method is proposed with the capability of customizing the beamforming gain,power consumption,and energy efficiency.Simulation results indicate that the proposed method is capable of achieving a more favorable performance in terms of satisfying the QoS demand,reducing the power consumption,and improving the energy efficiency.Furthermore,two field trials at 35 GHz evidence the superiority performance and feasibility characteristics of the proposed method in real environment.This work may provide a reference for future applications of RIS-assisted system with an energy-efficient manner.
基金Supported by the National Natural Science Foundation of China(No.62071482)Shaanxi Association of Science and Technology Youth Talent Support Program Project,China(No.20230137)+1 种基金the Innovative Talents Cultivate Program for Technology Innovation Team of ShaanXi Province,China(No.2024RS-CXTD-08)the Youth Talent Lifting Project of the China Association for Science and Technology(No.2021-JCJQ-QT-018).
文摘The resource allocation technique is of great significance in achieving frequency spectrum coexistence in Joint Radar-Communication(JRC) systems, by which the problem of radio frequency spectrum congestion can be well alleviated. A Robust Joint Frequency Spectrum and Power Allocation(RJFSPA) strategy is proposed for the Coexisting Radar and Communication(CRC)system. Specifically, we consider the uncertainty of target Radar Cross Section(RCS) and communication channel gain to formulate a bi-objective optimization model. The joint probabilities that the Cramér-Rao Lower Bound(CRLB) of each target satisfying the localization accuracy threshold and the Communication Data Ratio(CDR) of each user satisfying the communication threshold are simultaneously maximized, under the constraint of the total power budget. A Three-Stage Alternating Optimization Method(TSAOM) is proposed to obtain the Best-Known Pareto Subset(BKPS) of this problem, where the frequency spectrum, radar power, and communicator power are allocated using the greedy search and standard convex optimization methods, respectively. Simulation results confirm the effectiveness of the proposed RJFSPA strategy, compared with the resource allocation methods in a uniform manner and that ignores the uncertainties. The efficiency of the TSAOM is also verified by the comparison with the exhaustive search-based method.
文摘With the rapid development of information technology,5G communication technology has gradually entered real life,among which the application of edge computing is particularly significant in the information and communication system field.This paper focuses on using edge computing based on 5G communication in information and communication systems.First,the study analyzes the importance of combining edge computing technology with 5G communication technology,and its advantages,such as high efficiency and low latency in processing large amounts of data.The study then explores multiple application scenarios of edge computing in information and communication systems,such as integrated use in the Internet of Things,intelligent transportation,telemedicine and Industry 4.0.The research method is mainly based on theoretical analysis and experimental verification,combined with the characteristics of the 5G network to optimize the edge computing model and test the performance of edge computing in different scenarios through experimental simulation.The results show that edge computing significantly improves the data processing capacity and response speed of ICS in a 5G environment.However,there are also a series of challenges in practical application,including data security and privacy protection,the complexity of resource management and allocation,and the guarantee of quality of service(QoS).Through the case analysis and problem analysis,the paper puts forward the corresponding solution strategies,such as strengthening the data security protocol,introducing the intelligent resource scheduling system and establishing a multi-dimensional service quality monitoring mechanism.Finally,this study points out that the deep integration of edge computing and 5G communication will continue to promote the innovative development of information and communication systems,which has a far-reaching impact and important practical significance for promoting the transformation and upgrading in the field of information technology.
基金supported by the National Natural Science Foundation of China(No.62171052 and No.61971054)the Fundamental Research Funds for the Central Universities(No.24820232023YQTD01).
文摘Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.
基金supported in part by collaborative research with Toyota Motor Corporation,in part by ROIS NII Open Collaborative Research under Grant 21S0601,in part by JSPS KAKENHI under Grants 20H00592,21H03424.
文摘With the rapid development of artificial intelligence and the widespread use of the Internet of Things, semantic communication, as an emerging communication paradigm, has been attracting great interest. Taking image transmission as an example, from the semantic communication's view, not all pixels in the images are equally important for certain receivers. The existing semantic communication systems directly perform semantic encoding and decoding on the whole image, in which the region of interest cannot be identified. In this paper, we propose a novel semantic communication system for image transmission that can distinguish between Regions Of Interest (ROI) and Regions Of Non-Interest (RONI) based on semantic segmentation, where a semantic segmentation algorithm is used to classify each pixel of the image and distinguish ROI and RONI. The system also enables high-quality transmission of ROI with lower communication overheads by transmissions through different semantic communication networks with different bandwidth requirements. An improved metric θPSNR is proposed to evaluate the transmission accuracy of the novel semantic transmission network. Experimental results show that our proposed system achieves a significant performance improvement compared with existing approaches, namely, existing semantic communication approaches and the conventional approach without semantics.
文摘The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.
基金supported in part by the Fundamental Research Project of Shenzhen(No.JCYJ20200109105216803)。
文摘In this paper,the eavesdropping model based on eavesdroppers near legitimate users,and the effect of atmospheric channel correlation on the physical layer security(PLS)of the free-space optical(FSO)link are analyzed.According to the joint probability density function(PDF)and cumulative distribution function(CDF)of Gamma-Gamma(G-G)distribution,a new closed-form expression of interception probability is derived.Numerical results show that the interception probability of the FSO system depends on turbulence intensity,channel correlation and radial displacement attenuation of eavesdroppers.
基金supported in part by the National Natural Science Foundation of China(No.U1833111)。
文摘Performance of non-line-of-sight(NLOS)ultraviolet(UV)communication is closely related with the communication range,system geometry and the atmosphere aerosol properties.In this paper,we investigate the path loss of the NLOS UV communication systems in both monodisperse and polydisperse aerosol systems based on the Monte-Carlo method.
基金supported by the Beijing Natural Science Foundation(L211012)the Natural Science Foundation of China(62122012,62221001)the Fundamental Research Funds for the Central Universities(2022JBQY004)。
文摘The concept of semantic communication provides a novel approach for applications in scenarios with limited communication resources.In this paper,we propose an end-to-end(E2E)semantic molecular communication system,aiming to enhance the efficiency of molecular communication systems by reducing the transmitted information.Specifically,following the joint source channel coding paradigm,the network is designed to encode the task-relevant information into the concentration of the information molecules,which is robust to the degradation of the molecular communication channel.Furthermore,we propose a channel network to enable the E2E learning over the non-differentiable molecular channel.Experimental results demonstrate the superior performance of the semantic molecular communication system over the conventional methods in classification tasks.
基金supported in part by the National Natural Science Foundation of China under Grant No.61931020,U19B2024,62171449,,62001483in part by the science and technology innovation Program of Hunan Province under Grant No.2021JJ40690.
文摘Context information is significant for semantic extraction and recovery of messages in semantic communication.However,context information is not fully utilized in the existing semantic communication systems since re-lationships between sentences are often ignored.In this paper,we propose an Extended Context-based Semantic Communication(ECSC)system for text transmission,in which context information within and between sentences is explored for semantic representation and recovery.At the encoder,self-attention and segment-level relative attention are used to extract context information within and between sentences,respectively.In addition,a gate mechanism is adopted at the encoder to incorporate the context information from different ranges.At the decoder,Transformer-XL is introduced to obtain more semantic information from the historical communication processes for semantic recovery.Simulation results show the effectiveness of our proposed model in improving the semantic accuracy between transmitted and recovered messages under various channel conditions.
