In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating c...In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)technologies.In this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use cases.Next,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration approach.We review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration approaches.We also highlight the need for intelligence in resources integration.Then,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various classes.Finally,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.展开更多
Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions...Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions of a photonic spiking neural network(PSNN).However,they are separately implemented with different photonic materials and devices,hindering the large-scale integration of PSNN.Here,we propose,fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spike activation based on a distributed feedback(DFB)laser with a saturable absorber(DFB-SA).A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation.Furthermore,a fourchannel DFB-SA laser array is fabricated for realizing matrix convolution of a spiking convolutional neural network,achieving a recognition accuracy of 87%for the MNIST dataset.The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip.展开更多
The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the sat...The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.展开更多
We construct a circuit based on PBS and CNOT gates, which can be used to determine whether the input pulse is empty or not according to the detection result of the auxiliary state, while the input state will not be ch...We construct a circuit based on PBS and CNOT gates, which can be used to determine whether the input pulse is empty or not according to the detection result of the auxiliary state, while the input state will not be changed. The circuit can be treated as a pre-detection device. Equipping the pre-detection device in the front of the receiver of the quantum key distribution (QKD) can reduce the influence of the dark count of the detector, hence increasing the secure communication distance significantly. Simulation results show that the secure communication distance can reach 516 km and 479 km for QKD with perfect single photon source and decoy-state QKD with weak coherent photon source, respectively.展开更多
Passive detection of moving target is an important part of intelligent surveillance. Satellite has the potential to play a key role in many applications of space-air-ground integrated networks(SAGIN). In this paper, w...Passive detection of moving target is an important part of intelligent surveillance. Satellite has the potential to play a key role in many applications of space-air-ground integrated networks(SAGIN). In this paper, we propose a novel intelligent passive detection method for aerial target based on reservoir computing networks. Specifically, delayed feedback networks are utilized to refine the direct signals from the satellite in the reference channels. In addition, the satellite direct wave interference in the monitoring channels adopts adaptive interference suppression using the minimum mean square error filter. Furthermore, we employ decoupling echo state networks to predict the clutter interference in the monitoring channels and construct the detection statistics accordingly. Finally, a multilayer perceptron is adopted to detect the echo signal after interference suppression. Extensive simulations is conducted to evaluate the performance of our proposed method. Results show that the detection probability is almost 100% when the signal-to-interference ratio of echo signal is-36 dB, which demonstrates that our proposed method achieves efficient passive detection for aerial targets in typical SAGIN scenarios.展开更多
To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlin...To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.展开更多
This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID ...This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.展开更多
The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance th...The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction.Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS.According to their distance to the UAV,the users are divided into the close users and remote users.The UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received power.We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement.However,the problem is non-convex.Therefore,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,respectively.We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.展开更多
Efficient optical network management poses significant importance in backhaul and access network communicationfor preventing service disruptions and ensuring Quality of Service(QoS)satisfaction.The emerging faultsin o...Efficient optical network management poses significant importance in backhaul and access network communicationfor preventing service disruptions and ensuring Quality of Service(QoS)satisfaction.The emerging faultsin optical networks introduce challenges that can jeopardize the network with a variety of faults.The existingliterature witnessed various partial or inadequate solutions.On the other hand,Machine Learning(ML)hasrevolutionized as a promising technique for fault detection and prevention.Unlike traditional fault managementsystems,this research has three-fold contributions.First,this research leverages the ML and Deep Learning(DL)multi-classification system and evaluates their accuracy in detecting six distinct fault types,including fiber cut,fibereavesdropping,splicing,bad connector,bending,and PC connector.Secondly,this paper assesses the classificationdelay of each classification algorithm.Finally,this work proposes a fiber optics fault prevention algorithm thatdetermines to mitigate the faults accordingly.This work utilized a publicly available fiber optics dataset namedOTDR_Data and applied different ML classifiers,such as Gaussian Naive Bayes(GNB),Logistic Regression(LR),Support Vector Machine(SVM),K-Nearest Neighbor(KNN),Random Forest(RF),and Decision Tree(DT).Moreover,Ensemble Learning(EL)techniques are applied to evaluate the accuracy of various classifiers.In addition,this work evaluated the performance of DL-based Convolutional Neural Network and Long-Short Term Memory(CNN-LSTM)hybrid classifier.The findings reveal that the CNN-LSTM hybrid technique achieved the highestaccuracy of 99%with a delay of 360 s.On the other hand,EL techniques improved the accuracy in detecting fiberoptic faults.Thus,this research comprehensively assesses accuracy and delay metrics for various classifiers andproposes the most efficient attack detection system in fiber optics.展开更多
Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV ...Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell.To fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent cells.To tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV position.Then,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation schemes.We further propose an iterative power allocation algorithm based on the sequential convex approximation theory.The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.展开更多
Given imperfect channel state information(CSI)and considering the interference from the primary transmitter,an underlay cognitive multisource multidestination relay network is proposed.A closed-form exact outage proba...Given imperfect channel state information(CSI)and considering the interference from the primary transmitter,an underlay cognitive multisource multidestination relay network is proposed.A closed-form exact outage probability and asymptotic outage probability are derived for the secondary system of the network.The results show that the outage probability is influenced by the source and destination number,the CSI imperfection as well as the interference from the primary transmitter,while the diversity order is independent of the CSI imperfection and the interference from the primary transmitter,yet it is equal to the minimum of the source and destination number.Moreover,extensive simulations are conducted with different system parameters to verify the theoretical analysis.展开更多
Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference manage...Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive Het Net with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.展开更多
In this paper,an energy harvesting enabled cooperative non-orthogonal multiple access(NOMA)system for a multi-cell network is investigated.Particularly,during the direct transmission phase,base stations send their sup...In this paper,an energy harvesting enabled cooperative non-orthogonal multiple access(NOMA)system for a multi-cell network is investigated.Particularly,during the direct transmission phase,base stations send their superposed messages to the near users and far users simultaneously according to a NOMA principle,while the near users act as energy harvesting enabled relays employing a power splitting protocol.During the cooperative phase,the near users transmit their decoded messages to the corresponding far users using harvested energy.Using tools from stochastic geometry,we firstly calculate the signal to interference ratios of the users in each NOMA group including one near user and one far user.Then,the closed-form expressions of the coverage probability,ergodic rate,and energy efficiency are derived respectively.Numerical results validate the derived expressions and show that the energy harvesting enabled cooperative NOMA system in a multi-cell network can improve the coverage probability,ergodic rate,and energy efficiency compared to its counterpart OMA system.展开更多
To improve the recognition rate of signal modulation recognition methods based on the clustering algorithm under the low SNR, a modulation recognition method is proposed. The characteristic parameter of the signal is ...To improve the recognition rate of signal modulation recognition methods based on the clustering algorithm under the low SNR, a modulation recognition method is proposed. The characteristic parameter of the signal is extracted by using a clustering algorithm, the neural network is trained by using the algorithm of variable gradient correction (Polak-Ribiere) so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram. Simulation results show that the recognition rate based on this algorithm is enhanced over 30% compared with the methods that adopt clustering algorithm or neural network based on the back propagation algorithm alone under the low SNR. The recognition rate can reach 90% when the SNR is 4 dB, and the method is easy to be achieved so that it has a broad application prospect in the modulating recognition.展开更多
In cognitive radio networks(CRNs), through recruiting secondary user(SU) as friendly jammer, the secrecy rate obtained by primary user(PU) can be improved. Previous work only considered a simple scenario with a single...In cognitive radio networks(CRNs), through recruiting secondary user(SU) as friendly jammer, the secrecy rate obtained by primary user(PU) can be improved. Previous work only considered a simple scenario with a single PU in their frameworks. In this paper, we will consider a more complicated scenario with multiple PUs and try to investigate the cooperative jamming between multiple PUs and a single SU. When there are multiple PUs in CRN, in order to obtain more spectrum for data transmission, SU will cooperate with multiple PUs at the same time. Considering that both PU and SU are rational and selfish individuals, the interaction between PUs and SU is formulated as a multi-leaders and single-follower Stackelberg game, wherein PU is the leader and SU is the follower. And the Stackelberg Equilibrium(SE) is considered as the final decisions accepted by all PUs and SU. Furthermore, we also prove that when a specific condition is satisfied, the existence of SE can be guaranteed. And a Gauss-Jacobi iterative algorithm is proposed to compute a SE. Finally, simulation results are given to verify the performance and demonstrate that both of the PUs' secrecy rate and the SU's transmission rate can be improved through cooperation.展开更多
The cloud radio access network(C-RAN) and the fog computing have been recently proposed to tackle the dramatically increasing traffic demands and to provide better quality of service(QoS) to user equipment(UE).Conside...The cloud radio access network(C-RAN) and the fog computing have been recently proposed to tackle the dramatically increasing traffic demands and to provide better quality of service(QoS) to user equipment(UE).Considering the better computation capability of the cloud RAN(10 times larger than that of the fog RAN) and the lower transmission delay of the fog computing,we propose a joint resource allocation and coordinated computation offloading algorithm for the fog RAN(F-RAN),which takes the advantage of C-RAN and fog computing.Specifically,the F-RAN splits a computation task into the fog computing part and the cloud computing part.Based on the constraints of maximum transmission delay tolerance,fronthaul and backhaul capacity limits,we minimize the energy cost and obtain optimal computational resource allocation for multiple UE,transmission power allocation of each UE and the event splitting factor.Numerical results have been proposed with the comparison of existing methods.展开更多
Recent research results indicate that individual awareness can play an important influence on epidemic spreading in networks. By local stability analysis, a significant conclusion is that the embedded awareness in an ...Recent research results indicate that individual awareness can play an important influence on epidemic spreading in networks. By local stability analysis, a significant conclusion is that the embedded awareness in an epidemic network can increase its epidemic threshold. In this paper, by using limit theory and dynamical system theory, we further give global stability analysis of a susceptible-infected-susceptible (SIS) epidemic model on networks with awareness. Results show that the obtained epidemic threshold is also a global stability condition for its endemic equilibrium, which implies the embedded awareness can enhance the epidemic threshold globally. Some numerical examples are presented to verify the theoretical results.展开更多
This article investigates channel allocation for cognitive networks, which is difficult to obtain the optimal allocation distribution. We first study interferences between nodes in cognitive networks and establish the...This article investigates channel allocation for cognitive networks, which is difficult to obtain the optimal allocation distribution. We first study interferences between nodes in cognitive networks and establish the channel allocation model with interference constraints. Then we focus on the use of evolutionary algorithms to solve the optimal allocation distribution. We further consider that the search time can be reduced by means of parallel computing, and then a parallel algorithm based APO is proposed. In contrast with the existing algorithms, we decompose the allocation vector into a number of sub-vectors and search for optimal allocation distribution of sub-vector in parallel. In order to speed up converged rate and improve converged value, some typical operations of evolutionary algorithms are modified by two novel operators. Finally, simulation results show that the proposed algorithm drastically outperform other optimal solutions in term of the network utilization.展开更多
Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wi...Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wireless network subject to diverse Qo E is very difficult, which leads to many new challenges regarding Qo E guarantees in wireless networks. In this paper, we formulate the Qo E guarantees model for cellular wireless networks. Based on the model, we convert the effective capacity maximization problem into the equivalent convex optimization problem. Then, we develop the optimal Qo E-driven power allocation scheme, which can maximize the effective capacity. The obtained simulation results verified our proposed power allocation scheme, showing that the effective capacity can be significantly increased compared with that of traditional Qo E guarantees based schemes.展开更多
In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellula...In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellular networks recently. These IFW cells are multi-mode capable(i.e., both licensed bands via cellular interface and unlicensed bands via WiFi interface). Therefore how to offload data effectively has become one of the most significant discussions in 5G Multi-Radio Heterogeneous Network. So far, most researches mainly focus on the generality of UEs, few attention has been paid to UEs' individual requirements. Considering UE's preference vary from individual to individual, in this paper, we present an UE preference-aware network selection scheme for mobile data offloading. It intelligently supports the distribution of heterogeneous classes of services, considers different types of UEs and delay-tolerant flows, and handles the mobility of UEs. The simulation results show the superiority of the proposed algorithm in user fairness, enhanced capacity and energy saving maximization.展开更多
基金supported in part by National Key R&D Program of China(2019YFE0196400)Key Research and Development Program of Shaanxi(2022KWZ09)+4 种基金National Natural Science Foundation of China(61771358,61901317,62071352)Fundamental Research Funds for the Central Universities(JB190104)Joint Education Project between China and Central-Eastern European Countries(202005)the 111 Project(B08038)。
文摘In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)technologies.In this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use cases.Next,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration approach.We review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration approaches.We also highlight the need for intelligence in resources integration.Then,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various classes.Finally,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.
基金financial supports from National Key Research and Development Program of China (2021YFB2801900,2021YFB2801901,2021YFB2801902,2021YFB2801904)National Natural Science Foundation of China (No.61974177)+1 种基金National Outstanding Youth Science Fund Project of National Natural Science Foundation of China (62022062)The Fundamental Research Funds for the Central Universities (QTZX23041).
文摘Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture.Linear weighting and nonlinear spike activation are two fundamental functions of a photonic spiking neural network(PSNN).However,they are separately implemented with different photonic materials and devices,hindering the large-scale integration of PSNN.Here,we propose,fabricate and experimentally demonstrate a photonic neuro-synaptic chip enabling the simultaneous implementation of linear weighting and nonlinear spike activation based on a distributed feedback(DFB)laser with a saturable absorber(DFB-SA).A prototypical system is experimentally constructed to demonstrate the parallel weighted function and nonlinear spike activation.Furthermore,a fourchannel DFB-SA laser array is fabricated for realizing matrix convolution of a spiking convolutional neural network,achieving a recognition accuracy of 87%for the MNIST dataset.The fabricated neuro-synaptic chip offers a fundamental building block to construct the large-scale integrated PSNN chip.
基金supported by the Natural Science Foundation of China under Grants U19B2025,62121001,and 62001347in part by Key Research and Development Program of Shaanxi(ProgramNo.2022ZDLGY05-02)in part by Young Talent Support Program of Xi’an Association for Science and Technology(No.095920221337).
文摘The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.
基金supported by the National Natural Science Foundation of China(Grant No.61372076)the Programme of Introducing Talents of Discipline to Universities,China(Grant No.B08038)the Fundamental Research Funds for the Central Universities,China(Grant No.K5051201021)
文摘We construct a circuit based on PBS and CNOT gates, which can be used to determine whether the input pulse is empty or not according to the detection result of the auxiliary state, while the input state will not be changed. The circuit can be treated as a pre-detection device. Equipping the pre-detection device in the front of the receiver of the quantum key distribution (QKD) can reduce the influence of the dark count of the detector, hence increasing the secure communication distance significantly. Simulation results show that the secure communication distance can reach 516 km and 479 km for QKD with perfect single photon source and decoy-state QKD with weak coherent photon source, respectively.
基金supported by the National Natural Science Foundation of China under Grant 62071364in part by the Aeronautical Science Foundation of China under Grant 2020Z073081001+2 种基金in part by the Fundamental Research Funds for the Central Universities under Grant JB210104in part by the Shaanxi Provincial Key Research and Development Program under Grant 2019GY-043in part by the 111 Project under Grant B08038。
文摘Passive detection of moving target is an important part of intelligent surveillance. Satellite has the potential to play a key role in many applications of space-air-ground integrated networks(SAGIN). In this paper, we propose a novel intelligent passive detection method for aerial target based on reservoir computing networks. Specifically, delayed feedback networks are utilized to refine the direct signals from the satellite in the reference channels. In addition, the satellite direct wave interference in the monitoring channels adopts adaptive interference suppression using the minimum mean square error filter. Furthermore, we employ decoupling echo state networks to predict the clutter interference in the monitoring channels and construct the detection statistics accordingly. Finally, a multilayer perceptron is adopted to detect the echo signal after interference suppression. Extensive simulations is conducted to evaluate the performance of our proposed method. Results show that the detection probability is almost 100% when the signal-to-interference ratio of echo signal is-36 dB, which demonstrates that our proposed method achieves efficient passive detection for aerial targets in typical SAGIN scenarios.
基金supported by the National Natural Science Foundation of China(No.62071354)the Key Research and Development Program of Shaanxi(No.2022ZDLGY05-08)supported by the ISN State Key Laboratory。
文摘To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.
基金supported in part by the NSF of China under Grant 62322106,62071131the Guangdong Basic and Applied Basic Research Foundation under Grant 2022B1515020086+2 种基金the International Collaborative Research Program of Guangdong Science and Technology Department under Grant 2022A0505050070in part by the Open Research Fund of the State Key Laboratory of Integrated Services Networks under Grant ISN22-23the National Research Foundation,Singapore University of Technology Design under its Future Communications Research&Development Programme“Advanced Error Control Coding for 6G URLLC and mMTC”Grant No.FCP-NTU-RG-2022-020.
文摘This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 62271099。
文摘The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground users.Intelligent reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction.Motivated by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS.According to their distance to the UAV,the users are divided into the close users and remote users.The UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received power.We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement.However,the problem is non-convex.Therefore,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,respectively.We propose an iterative algorithm to solve the two sub-problems alternatively.Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.
基金in part by the National Natural Science Foundation of China under Grants 62271079,61875239,62127802in part by the Fundamental Research Funds for the Central Universities under Grant 2023PY01+1 种基金in part by the National Key Research and Development Program of China under Grant 2018YFB2200903in part by the Beijing Nova Program with Grant Number Z211100002121138.
文摘Efficient optical network management poses significant importance in backhaul and access network communicationfor preventing service disruptions and ensuring Quality of Service(QoS)satisfaction.The emerging faultsin optical networks introduce challenges that can jeopardize the network with a variety of faults.The existingliterature witnessed various partial or inadequate solutions.On the other hand,Machine Learning(ML)hasrevolutionized as a promising technique for fault detection and prevention.Unlike traditional fault managementsystems,this research has three-fold contributions.First,this research leverages the ML and Deep Learning(DL)multi-classification system and evaluates their accuracy in detecting six distinct fault types,including fiber cut,fibereavesdropping,splicing,bad connector,bending,and PC connector.Secondly,this paper assesses the classificationdelay of each classification algorithm.Finally,this work proposes a fiber optics fault prevention algorithm thatdetermines to mitigate the faults accordingly.This work utilized a publicly available fiber optics dataset namedOTDR_Data and applied different ML classifiers,such as Gaussian Naive Bayes(GNB),Logistic Regression(LR),Support Vector Machine(SVM),K-Nearest Neighbor(KNN),Random Forest(RF),and Decision Tree(DT).Moreover,Ensemble Learning(EL)techniques are applied to evaluate the accuracy of various classifiers.In addition,this work evaluated the performance of DL-based Convolutional Neural Network and Long-Short Term Memory(CNN-LSTM)hybrid classifier.The findings reveal that the CNN-LSTM hybrid technique achieved the highestaccuracy of 99%with a delay of 360 s.On the other hand,EL techniques improved the accuracy in detecting fiberoptic faults.Thus,this research comprehensively assesses accuracy and delay metrics for various classifiers andproposes the most efficient attack detection system in fiber optics.
基金supported in part by the National Key Research and Development Program of China under Grant 2020YFB1807003in part by the National Natural Science Foundation of China under Grants 61901381,62171385,and 61901378+3 种基金in part by the Aeronautical Science Foundation of China under Grant 2020z073053004in part by the Foundation of the State Key Laboratory of Integrated Services Networks of Xidian University under Grant ISN21-06in part by the Key Research Program and Industrial Innovation Chain Project of Shaanxi Province under Grant 2019ZDLGY07-10in part by the Natural Science Fundamental Research Program of Shaanxi Province under Grant 2021JM-069.
文摘Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell.To fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent cells.To tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV position.Then,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation schemes.We further propose an iterative power allocation algorithm based on the sequential convex approximation theory.The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.
基金Supported by the National Natural Science Foundation of China(No.61301170,61571340)the Fundamental Research Funds for the Central Universities(No.JB150109)the 111 Project(No.B08038)
文摘Given imperfect channel state information(CSI)and considering the interference from the primary transmitter,an underlay cognitive multisource multidestination relay network is proposed.A closed-form exact outage probability and asymptotic outage probability are derived for the secondary system of the network.The results show that the outage probability is influenced by the source and destination number,the CSI imperfection as well as the interference from the primary transmitter,while the diversity order is independent of the CSI imperfection and the interference from the primary transmitter,yet it is equal to the minimum of the source and destination number.Moreover,extensive simulations are conducted with different system parameters to verify the theoretical analysis.
基金supported by the National Natural Science Foundation of China (Grant No.61601071)the Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant No.KJ16004012)+2 种基金the Municipal Natural Science Foundation of Chongqing (Grant No.CSTC2016JCYJA2197)the Seventeenth Open Foundation of State Key Lab of Integrated Services Networks of Xidian University (Grant No.ISN17-01)the Dr. Startup Founds of Chongqing University of Posts and Telecommunications (Grant No.A2016-12)
文摘Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive Het Net with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.
基金supported in part by National Natural Science Foundation of China (61771358)Intergovernmental International Cooperation on Science and Technology Innovation (2016YFE0123200)+2 种基金China Postdoctoral Science Foundation (2017M613074)Fundamental Research Funds for the Central Universities (JB170102)the 111 Project (B08038)
文摘In this paper,an energy harvesting enabled cooperative non-orthogonal multiple access(NOMA)system for a multi-cell network is investigated.Particularly,during the direct transmission phase,base stations send their superposed messages to the near users and far users simultaneously according to a NOMA principle,while the near users act as energy harvesting enabled relays employing a power splitting protocol.During the cooperative phase,the near users transmit their decoded messages to the corresponding far users using harvested energy.Using tools from stochastic geometry,we firstly calculate the signal to interference ratios of the users in each NOMA group including one near user and one far user.Then,the closed-form expressions of the coverage probability,ergodic rate,and energy efficiency are derived respectively.Numerical results validate the derived expressions and show that the energy harvesting enabled cooperative NOMA system in a multi-cell network can improve the coverage probability,ergodic rate,and energy efficiency compared to its counterpart OMA system.
基金supported by the National Natural Science Foundation of China(6107207061301179)the National Science and Technology Major Project(2010ZX03006-002-04)
文摘To improve the recognition rate of signal modulation recognition methods based on the clustering algorithm under the low SNR, a modulation recognition method is proposed. The characteristic parameter of the signal is extracted by using a clustering algorithm, the neural network is trained by using the algorithm of variable gradient correction (Polak-Ribiere) so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram. Simulation results show that the recognition rate based on this algorithm is enhanced over 30% compared with the methods that adopt clustering algorithm or neural network based on the back propagation algorithm alone under the low SNR. The recognition rate can reach 90% when the SNR is 4 dB, and the method is easy to be achieved so that it has a broad application prospect in the modulating recognition.
基金supported in part by the National Key Research and Development Program of China under Grant 2016QY01W0204in part by Key Industrial Innovation Chain in Industrial Domain under Grant 2016KTZDGY-02in part by National High-Level TalentsSpecial Support Program of China under Grant CS31117200001
文摘In cognitive radio networks(CRNs), through recruiting secondary user(SU) as friendly jammer, the secrecy rate obtained by primary user(PU) can be improved. Previous work only considered a simple scenario with a single PU in their frameworks. In this paper, we will consider a more complicated scenario with multiple PUs and try to investigate the cooperative jamming between multiple PUs and a single SU. When there are multiple PUs in CRN, in order to obtain more spectrum for data transmission, SU will cooperate with multiple PUs at the same time. Considering that both PU and SU are rational and selfish individuals, the interaction between PUs and SU is formulated as a multi-leaders and single-follower Stackelberg game, wherein PU is the leader and SU is the follower. And the Stackelberg Equilibrium(SE) is considered as the final decisions accepted by all PUs and SU. Furthermore, we also prove that when a specific condition is satisfied, the existence of SE can be guaranteed. And a Gauss-Jacobi iterative algorithm is proposed to compute a SE. Finally, simulation results are given to verify the performance and demonstrate that both of the PUs' secrecy rate and the SU's transmission rate can be improved through cooperation.
基金supported in part by National Natural Science Foundation of China(No. 61372070)Natural Science Basic Research Plan in Shaanxi Province of China(No. 2015JM6324)+3 种基金Ningbo Natural Science Foundation(2015A610117)Hong Kong, Macao and Taiwan Science & Technology Cooperation Program of China(No. 2015DFT10160)EU FP7 Project MONICA (No.PIRSES-GA-2011-295222)the 111 Project(No.B08038)
文摘The cloud radio access network(C-RAN) and the fog computing have been recently proposed to tackle the dramatically increasing traffic demands and to provide better quality of service(QoS) to user equipment(UE).Considering the better computation capability of the cloud RAN(10 times larger than that of the fog RAN) and the lower transmission delay of the fog computing,we propose a joint resource allocation and coordinated computation offloading algorithm for the fog RAN(F-RAN),which takes the advantage of C-RAN and fog computing.Specifically,the F-RAN splits a computation task into the fog computing part and the cloud computing part.Based on the constraints of maximum transmission delay tolerance,fronthaul and backhaul capacity limits,we minimize the energy cost and obtain optimal computational resource allocation for multiple UE,transmission power allocation of each UE and the event splitting factor.Numerical results have been proposed with the comparison of existing methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.61004101,11161013,and 61164020)the Natural Science Foundation of Guangxi Province,China(Grant Nos.2011GXNSFB018059 and 2013GXNSFAA019006)+2 种基金the 2012 Open Grant of Guangxi Key Lab of Wireless Wideband Communication and Signal Processing,Chinathe 2012 Open Grant of the State Key Laboratory of Integrated Services Networks of Xidian University,Chinathe Graduate Education Innovation Project of Guilin University of Electronic Technology,China(Grant No.GDYCSZ201472)
文摘Recent research results indicate that individual awareness can play an important influence on epidemic spreading in networks. By local stability analysis, a significant conclusion is that the embedded awareness in an epidemic network can increase its epidemic threshold. In this paper, by using limit theory and dynamical system theory, we further give global stability analysis of a susceptible-infected-susceptible (SIS) epidemic model on networks with awareness. Results show that the obtained epidemic threshold is also a global stability condition for its endemic equilibrium, which implies the embedded awareness can enhance the epidemic threshold globally. Some numerical examples are presented to verify the theoretical results.
基金supported in part by the National Natural Science Foundation under Grant No.61072069National Science and Technology Major Project of the Ministry of Science and Technology of China under Grant No.2012ZX03003012
文摘This article investigates channel allocation for cognitive networks, which is difficult to obtain the optimal allocation distribution. We first study interferences between nodes in cognitive networks and establish the channel allocation model with interference constraints. Then we focus on the use of evolutionary algorithms to solve the optimal allocation distribution. We further consider that the search time can be reduced by means of parallel computing, and then a parallel algorithm based APO is proposed. In contrast with the existing algorithms, we decompose the allocation vector into a number of sub-vectors and search for optimal allocation distribution of sub-vector in parallel. In order to speed up converged rate and improve converged value, some typical operations of evolutionary algorithms are modified by two novel operators. Finally, simulation results show that the proposed algorithm drastically outperform other optimal solutions in term of the network utilization.
基金supported in part by the National Natural Science Foundation of China(Nos.61771368 and 61671347)Young Elite Scientists Sponsorship Program by CAST(2016QNRC001)
文摘Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wireless network subject to diverse Qo E is very difficult, which leads to many new challenges regarding Qo E guarantees in wireless networks. In this paper, we formulate the Qo E guarantees model for cellular wireless networks. Based on the model, we convert the effective capacity maximization problem into the equivalent convex optimization problem. Then, we develop the optimal Qo E-driven power allocation scheme, which can maximize the effective capacity. The obtained simulation results verified our proposed power allocation scheme, showing that the effective capacity can be significantly increased compared with that of traditional Qo E guarantees based schemes.
文摘In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellular networks recently. These IFW cells are multi-mode capable(i.e., both licensed bands via cellular interface and unlicensed bands via WiFi interface). Therefore how to offload data effectively has become one of the most significant discussions in 5G Multi-Radio Heterogeneous Network. So far, most researches mainly focus on the generality of UEs, few attention has been paid to UEs' individual requirements. Considering UE's preference vary from individual to individual, in this paper, we present an UE preference-aware network selection scheme for mobile data offloading. It intelligently supports the distribution of heterogeneous classes of services, considers different types of UEs and delay-tolerant flows, and handles the mobility of UEs. The simulation results show the superiority of the proposed algorithm in user fairness, enhanced capacity and energy saving maximization.