With the rapid development of commercial communications,the research on Radar-Communication Coexistence(RCC)systems is becoming a hot spot.The resource allocation techniques play a crucial role in the RCC systems.A pe...With the rapid development of commercial communications,the research on Radar-Communication Coexistence(RCC)systems is becoming a hot spot.The resource allocation techniques play a crucial role in the RCC systems.A performance-driven Joint Radar-target and Communication-user Assignment,along with Power and Subchannel Allocation(JRCAPSA)strategy,is proposed for an RCC network.The optimization model aims to minimize the sum of weighted Bayesian Cramer-Rao Lower Bounds(BCRLBs)of target state estimates for radar purpose.This is subject to constraints such as the Communication Data Rate(CDR)for communication purpose,the total power budget in each RCC system,assignment relationships,and the number of available subchannels.Considering that such a problem falls into the realm of Mixed Integer Programming(MIP),a Three-stage Iteratively Augment-based Optimization Method(TIAOM)is developed.The Communication-User Assignment(CUA),Communication Subchannel Allocation(SCA),and Radar-Target Assignment(RTA)feasible solution domains are iteratively expanded based on their importance,leading to the efficient acquisition of a suboptimal solution.Simulation results show the outperformance of the proposed JRCAPSA strategy,compared to the other benchmarks and the OPTI toolbox.The results also imply that the Bayesian Cramer-Rao Lower Bound(BCRLB)is a more stringent optimization metric for the achieved Mean Square Error(MSE),compared to Mutual Information(MI)and Signal-to-Interference-Noise Ratio(SINR).展开更多
In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network n...In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.展开更多
The analysis is based on the error rate and the secure communication rate as functions of distance for three quantum-key-distribution （QKD） protocols： the Bennett-Brassard 1984, the Bennett Brassard Mermin 1992, an...The analysis is based on the error rate and the secure communication rate as functions of distance for three quantum-key-distribution （QKD） protocols： the Bennett-Brassard 1984, the Bennett Brassard Mermin 1992, and the coherent differential-phase-shift keying （DPSK） protocols. We consider the secure communication rate of the DPSK protocol against an arbitrary individual attack, including the most commonly considered intercept-resend and photonnumber splitting attacks, and concluded that the simple and efficient differential-phase-shift-keying protocol allows for more than 200 km of secure communication distance with high communication rates.展开更多
This paper addresses the leader-following consensus problem in multi-agent systems(MASs)with limited communication rates,while also considering sensor and actuator false data injection(FDI)attacks.A distributed event-...This paper addresses the leader-following consensus problem in multi-agent systems(MASs)with limited communication rates,while also considering sensor and actuator false data injection(FDI)attacks.A distributed event-triggered adaptive control protocol is developed to achieve cooperative uniform ultimate boundedness(UUB)in consensus tracking for compromised networked MASs.To implement this protocol,a distributed estimator is first designed to allow followers to estimate the leader's state.Then,adaptive internal controllers are constructed for each follower to mitigate the impact of FDI attack signals.Additionally,an event-triggered transmission logic is introduced to handle the constraints imposed by finite communication rates.Simulation results demonstrate the effectiveness of the proposed approach.展开更多
At medium or long distance （〉 10 kin） underwater acoustic speech communication, information transfer rate is constrained by the complicated, time varying channel and limited bandwidth. The bit rate of speech coding...At medium or long distance （〉 10 kin） underwater acoustic speech communication, information transfer rate is constrained by the complicated, time varying channel and limited bandwidth. The bit rate of speech coding is required to be as low as possible. The time delay of underwater acoustic wave propagation can be used for low bit rate speech coding. After investigating the Mixed Excitation Linear Prediction （MELP） standard and taking account of the auditory perceptual features, a variable and adjustable bit rate speech codec algorithm has been proposed, whose average bit rate is about 600 bps. The average Perceptual Evaluation of Speech Quality Mean Opinion Score （PESQ MOS） of synthesized speeches is about 2.8. It has been proved by the computer simulation and sea trial that the performance of the proposed algorithm is well and robust when bit error rate is no more than 10-3. The synthesized speech is vivid and intelligible, and keeps main individual characteristics of speaker.展开更多
Michiko Harayama*and Noboru Miyagawa Abstract:In view of the successful application of deep learning,mainly in the field of image recognition,deep learning applications are now being explored in the fields of communic...Michiko Harayama*and Noboru Miyagawa Abstract:In view of the successful application of deep learning,mainly in the field of image recognition,deep learning applications are now being explored in the fields of communication and computer networks.In these fields,systems have been developed by use of proper theoretical calculations and procedures.However,due to the large amount of data to be processed,proper processing takes time and deviations from the theory sometimes occur due to the inclusion of uncertain disturbances.Therefore,deep learning or nonlinear approximation by neural networks may be useful in some cases.We have studied a user datagram protocol(UDP)based rate-control communication system called the simultaneous multipath communication system(SMPC),which measures throughput by a group of packets at the destination node and feeds it back to the source node continuously.By comparing the throughput with the recorded transmission rate,the source node detects congestion on the transmission route and adjusts the packet transmission interval.However,the throughput fluctuates as packets pass through the route,and if it is fed back directly,the transmission rate fluctuates greatly,causing the fluctuation of the throughput to become even larger.In addition,the average throughput becomes even lower.In this study,we tried to stabilize the transmission rate by incorporating prediction and learning performed by a neural network.The prediction is performed using the throughput measured by the destination node,and the result is learned so as to generate a stabilizer.A simple moving average method and a stabilizer using three types of neural networks,namely multilayer perceptrons,recurrent neural networks,and long short-term memory,were built into the transmission controller of the SMPC.The results showed that not only fluctuation reduced but also the average throughput improved.Together,the results demonstrated that deep learning can be used to predict and output stable values from data with complicated time fluctuations that are difficultly analyzed.展开更多
The advent of quantum computers has significantly challenged the security of traditional cryptographic systems,prompting a surge in research on quantum key distribution(QKD).Among various QKD approaches,continuousvari...The advent of quantum computers has significantly challenged the security of traditional cryptographic systems,prompting a surge in research on quantum key distribution(QKD).Among various QKD approaches,continuousvariable QKD(CVQKD)offers superior resilience against background noise.However,the local local oscillator(LLO)CVQKD scheme faces substantial physical limitations in scenarios with high channel attenuation,and the large attenuation CVQKD remains unrealized.Bottleneck challenges include ensuring stable low-noise transmission and accurately estimating parameters under fluctuating channel conditions.We propose a continuousmode theoretical framework that provides an analytical method for time-varying quantum systems within a freespace channel.This framework can achieve high-fidelity LLO-CVQKD in free space without the need for complex,real-time frequency locking and transmittance calibration equipment.It can also enable free-space QKD under large attenuation and high repetition frequency.Through experimental validation,we first demonstrate high-rate secure quantum key distribution over high-loss free-space channels.Specifically,we achieve asymptotic key rates of 76.366 kbps and 403.896 kbps in 25 dB attenuation free-space channels without turbulence and 21.5 dB average attenuation free-space channels with turbulence,respectively.Additionally,we confirm the feasibility of experiments on mildly turbulent atmospheric channels spanning at least 10.5 km using current equipment.Our scheme provides direct insight into constructing an integrated air-ground quantum communication network.展开更多
This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO)...This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO) system, and the agent's full state is assumed to be unavailable. To deal with this challenge, a state observer is constructed to estimate the agent's full state. A dynamic output-feedback based protocol that is based on the estimated state is proposed. To mitigate the effect of communication noise, noise-attenuation gains are also introduced into the proposed protocol. In this study, each agent is allowed to have its own noise-attenuation gain. It is shown that the proposed protocol can solve the mean square leader-following consensus problem of a linear MIMO MAS. Moreover, if all noise-attenuation gains are of Q(t-β), where b∈(0,1), the convergence rate of the MAS can be quantitatively analyzed. It turns out that all followers' states converge to the leader's state in the mean square sense at a rate of O(t-β).展开更多
基金supported by the National Natural Science Foundation of China(Nos.62071482,62471485,62471348)Shaanxi Association of Science and Technology Youth Talent Support Program Project,China(No.20230137)+1 种基金Innovative Talents Cultivate Program for Technology Innovation Team of ShaanXi Province,China(No.2024RS-CXTD-08)Youth Talent Lifting Project of the China Association for Science and Technology(No.2021-JCJQ-QT-018)。
文摘With the rapid development of commercial communications,the research on Radar-Communication Coexistence(RCC)systems is becoming a hot spot.The resource allocation techniques play a crucial role in the RCC systems.A performance-driven Joint Radar-target and Communication-user Assignment,along with Power and Subchannel Allocation(JRCAPSA)strategy,is proposed for an RCC network.The optimization model aims to minimize the sum of weighted Bayesian Cramer-Rao Lower Bounds(BCRLBs)of target state estimates for radar purpose.This is subject to constraints such as the Communication Data Rate(CDR)for communication purpose,the total power budget in each RCC system,assignment relationships,and the number of available subchannels.Considering that such a problem falls into the realm of Mixed Integer Programming(MIP),a Three-stage Iteratively Augment-based Optimization Method(TIAOM)is developed.The Communication-User Assignment(CUA),Communication Subchannel Allocation(SCA),and Radar-Target Assignment(RTA)feasible solution domains are iteratively expanded based on their importance,leading to the efficient acquisition of a suboptimal solution.Simulation results show the outperformance of the proposed JRCAPSA strategy,compared to the other benchmarks and the OPTI toolbox.The results also imply that the Bayesian Cramer-Rao Lower Bound(BCRLB)is a more stringent optimization metric for the achieved Mean Square Error(MSE),compared to Mutual Information(MI)and Signal-to-Interference-Noise Ratio(SINR).
基金supported by the National Science Foundation of China under Grant 62001517in part by the Research Project of Space Engineering University under Grants 2020XXAQ01 and 2019XXAQ05,and in part by the Science and Technology Innovation Cultivation Fund of Space Engineering University.
文摘In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.
基金supported by the Natural Science Foundation of Beijing,China (Grant No XK100130837)
文摘The analysis is based on the error rate and the secure communication rate as functions of distance for three quantum-key-distribution （QKD） protocols： the Bennett-Brassard 1984, the Bennett Brassard Mermin 1992, and the coherent differential-phase-shift keying （DPSK） protocols. We consider the secure communication rate of the DPSK protocol against an arbitrary individual attack, including the most commonly considered intercept-resend and photonnumber splitting attacks, and concluded that the simple and efficient differential-phase-shift-keying protocol allows for more than 200 km of secure communication distance with high communication rates.
文摘This paper addresses the leader-following consensus problem in multi-agent systems(MASs)with limited communication rates,while also considering sensor and actuator false data injection(FDI)attacks.A distributed event-triggered adaptive control protocol is developed to achieve cooperative uniform ultimate boundedness(UUB)in consensus tracking for compromised networked MASs.To implement this protocol,a distributed estimator is first designed to allow followers to estimate the leader's state.Then,adaptive internal controllers are constructed for each follower to mitigate the impact of FDI attack signals.Additionally,an event-triggered transmission logic is introduced to handle the constraints imposed by finite communication rates.Simulation results demonstrate the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China(61102152)
文摘At medium or long distance （〉 10 kin） underwater acoustic speech communication, information transfer rate is constrained by the complicated, time varying channel and limited bandwidth. The bit rate of speech coding is required to be as low as possible. The time delay of underwater acoustic wave propagation can be used for low bit rate speech coding. After investigating the Mixed Excitation Linear Prediction （MELP） standard and taking account of the auditory perceptual features, a variable and adjustable bit rate speech codec algorithm has been proposed, whose average bit rate is about 600 bps. The average Perceptual Evaluation of Speech Quality Mean Opinion Score （PESQ MOS） of synthesized speeches is about 2.8. It has been proved by the computer simulation and sea trial that the performance of the proposed algorithm is well and robust when bit error rate is no more than 10-3. The synthesized speech is vivid and intelligible, and keeps main individual characteristics of speaker.
文摘Michiko Harayama*and Noboru Miyagawa Abstract:In view of the successful application of deep learning,mainly in the field of image recognition,deep learning applications are now being explored in the fields of communication and computer networks.In these fields,systems have been developed by use of proper theoretical calculations and procedures.However,due to the large amount of data to be processed,proper processing takes time and deviations from the theory sometimes occur due to the inclusion of uncertain disturbances.Therefore,deep learning or nonlinear approximation by neural networks may be useful in some cases.We have studied a user datagram protocol(UDP)based rate-control communication system called the simultaneous multipath communication system(SMPC),which measures throughput by a group of packets at the destination node and feeds it back to the source node continuously.By comparing the throughput with the recorded transmission rate,the source node detects congestion on the transmission route and adjusts the packet transmission interval.However,the throughput fluctuates as packets pass through the route,and if it is fed back directly,the transmission rate fluctuates greatly,causing the fluctuation of the throughput to become even larger.In addition,the average throughput becomes even lower.In this study,we tried to stabilize the transmission rate by incorporating prediction and learning performed by a neural network.The prediction is performed using the throughput measured by the destination node,and the result is learned so as to generate a stabilizer.A simple moving average method and a stabilizer using three types of neural networks,namely multilayer perceptrons,recurrent neural networks,and long short-term memory,were built into the transmission controller of the SMPC.The results showed that not only fluctuation reduced but also the average throughput improved.Together,the results demonstrated that deep learning can be used to predict and output stable values from data with complicated time fluctuations that are difficultly analyzed.
基金Innovation Program for Quantum Science and Technology(2021ZD0300703)Shanghai Municipal Science and Technology Major Project(2019SHZDZX01)+1 种基金Key R&D Program of Guangdong Province(2020B0303040002)National Natural Science Foundation of China(62101320)。
文摘The advent of quantum computers has significantly challenged the security of traditional cryptographic systems,prompting a surge in research on quantum key distribution(QKD).Among various QKD approaches,continuousvariable QKD(CVQKD)offers superior resilience against background noise.However,the local local oscillator(LLO)CVQKD scheme faces substantial physical limitations in scenarios with high channel attenuation,and the large attenuation CVQKD remains unrealized.Bottleneck challenges include ensuring stable low-noise transmission and accurately estimating parameters under fluctuating channel conditions.We propose a continuousmode theoretical framework that provides an analytical method for time-varying quantum systems within a freespace channel.This framework can achieve high-fidelity LLO-CVQKD in free space without the need for complex,real-time frequency locking and transmittance calibration equipment.It can also enable free-space QKD under large attenuation and high repetition frequency.Through experimental validation,we first demonstrate high-rate secure quantum key distribution over high-loss free-space channels.Specifically,we achieve asymptotic key rates of 76.366 kbps and 403.896 kbps in 25 dB attenuation free-space channels without turbulence and 21.5 dB average attenuation free-space channels with turbulence,respectively.Additionally,we confirm the feasibility of experiments on mildly turbulent atmospheric channels spanning at least 10.5 km using current equipment.Our scheme provides direct insight into constructing an integrated air-ground quantum communication network.
基金supported by the National Natural Science Foundation of China(Grant Nos.6142231061370032+2 种基金61225017&61421004)Beijing Nova Program(Grant No.Z121101002512066)Guangdong Provincial Natural Science Foundation(Grant No.2014A030313266)
文摘This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO) system, and the agent's full state is assumed to be unavailable. To deal with this challenge, a state observer is constructed to estimate the agent's full state. A dynamic output-feedback based protocol that is based on the estimated state is proposed. To mitigate the effect of communication noise, noise-attenuation gains are also introduced into the proposed protocol. In this study, each agent is allowed to have its own noise-attenuation gain. It is shown that the proposed protocol can solve the mean square leader-following consensus problem of a linear MIMO MAS. Moreover, if all noise-attenuation gains are of Q(t-β), where b∈(0,1), the convergence rate of the MAS can be quantitatively analyzed. It turns out that all followers' states converge to the leader's state in the mean square sense at a rate of O(t-β).
