In this paper, we propose a parameter allocation scheme in a parallel array bistable stochastic resonance-based communication system(P-BSR-CS) to improve the performance of weak binary pulse amplitude modulated(BPAM) ...In this paper, we propose a parameter allocation scheme in a parallel array bistable stochastic resonance-based communication system(P-BSR-CS) to improve the performance of weak binary pulse amplitude modulated(BPAM) signal transmissions. The optimal parameter allocation policy of the P-BSR-CS is provided to minimize the bit error rate(BER)and maximize the channel capacity(CC) under the adiabatic approximation condition. On this basis, we further derive the best parameter selection theorem in realistic communication scenarios via variable transformation. Specifically, the P-BSR structure design not only brings the robustness of parameter selection optimization, where the optimal parameter pair is not fixed but variable in quite a wide range, but also produces outstanding system performance. Theoretical analysis and simulation results indicate that in the P-BSR-CS the proposed parameter allocation scheme yields considerable performance improvement, particularly in very low signal-to-noise ratio(SNR) environments.展开更多
Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the...Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the research and applications of natural language processing across different modalities,our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos.Specifically,we propose a deep learning-basedMulti-ModalMutual Enhancement Video Semantic Communication system,called M3E-VSC.Built upon a VectorQuantized Generative AdversarialNetwork(VQGAN),our systemaims to leverage mutual enhancement among different modalities by using text as the main carrier of transmission.With it,the semantic information can be extracted fromkey-frame images and audio of the video and performdifferential value to ensure that the extracted text conveys accurate semantic information with fewer bits,thus improving the capacity of the system.Furthermore,a multi-frame semantic detection module is designed to facilitate semantic transitions during video generation.Simulation results demonstrate that our proposed model maintains high robustness in complex noise environments,particularly in low signal-to-noise ratio conditions,significantly improving the accuracy and speed of semantic transmission in video communication by approximately 50 percent.展开更多
The initial cell search plays an important role during the process of downlink synchronization establishment between the User Equipment(UE) and the base station. In particular, the uncertainty of the synchronization s...The initial cell search plays an important role during the process of downlink synchronization establishment between the User Equipment(UE) and the base station. In particular, the uncertainty of the synchronization signals on the frequency domain and the flexibility of frame structure configuration have brought great challenges to the initial cell search for the fifth-generation(5G) new radio(NR). To solve this problem, firstly, we analyze the physical layer frame structure of 5G NR systems. Then, by focusing on the knowledge of synchronization signals, the 5G NR cell search process is designed, and the primary synchronization signal(PSS) timing synchronization algorithm is proposed, including a 5G-based coarse synchronization algorithm and conjugate symmetry-based fine synchronization algorithm. Finally, the performance of the proposed cell search algorithm in 5G NR systems is verified through the combination of Digital Signal Processing(DSP) and personal computer(PC). And the MATLAB simulation proves that the proposed algorithm has better performance than the conventional cross-correlation algorithm when a certain frequency offset exists.展开更多
Based on the three-dimensional Liu chaotic system, this paper appends a feedback variable to construct a novel hyperchaotic Liu system. Then, a control signal is further added to construct a novel nonautonomous hyperc...Based on the three-dimensional Liu chaotic system, this paper appends a feedback variable to construct a novel hyperchaotic Liu system. Then, a control signal is further added to construct a novel nonautonomous hyperchaotic Liu system. Through adjusting the frequency of the control signal, the chaotic property of the system can be controlled to show some different dynamic behaviors such as periodic, quasi-periodic, chaotic and hyperchaotic dynamic behaviours. By numerical simulations, the Lyapunov exponent spectrums, bifurcation diagrams and phase diagrams of the two new systems are studied, respectively. Furthermore, the synchronizing circuits of the nonautonomous hyperchaotic Liu system are designed via the synchronization control method of single variable coupling feedback. Finally, the hardware circuits are implemented, and the corresponding waves of chaos are observed by an oscillograph.展开更多
Spatially-coupled low-density parity-check(SC-LDPC)codes are prominent candidates for fu-ture communication standards due to their‘threshold saturation’properties.However,when facing burst erasures,the decoding proc...Spatially-coupled low-density parity-check(SC-LDPC)codes are prominent candidates for fu-ture communication standards due to their‘threshold saturation’properties.However,when facing burst erasures,the decoding process will stop and the decoding performances will dramatically de-grade.To improve the ability of burst erasure corrections,this paper proposes a two-dimensional SC-LDPC(2D-SC-LDPC)codes constructed by parallelly connecting two asymmetric SC-LDPC coupled chains for resistance to burst erasures.Density evolution algorithm is presented to evaluate the as-ymptotic performances against burst erasures,by which the maximum correctable burst erasure length can be computed.The analysis results show that the maximum correctable burst erasure lengths of the proposed 2D-SC-LDPC codes are much larger than the SC-LDPC codes and the asym-metric SC-LDPC codes.Finite-length performance simulation results of the 2D-SC-LDPC codes over the burst erasure channel confirm the excellent asymptotic performances.展开更多
How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is pro...How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.展开更多
This paper proposed a method of generating two attractors in a novel grid multi-scroll chaotic system. Based on a newly generated three-dimensional system, a two-attractor grid multi-scroll attractor system can be gen...This paper proposed a method of generating two attractors in a novel grid multi-scroll chaotic system. Based on a newly generated three-dimensional system, a two-attractor grid multi-scroll attractor system can be generated by adding two triangular waves and a sign function. Some basic dynamical properties, such as equilibrium points, bifurcations, and phase diagrams, were studied. Furthermore, the system was experimentally confirmed by an electronic circuit. The circuit simulation results and numerical simulation results verified the feasibility of this method.展开更多
In order to improve the broadcast reception rates of beacon messages in vehicle ad-hoc networks,a conclusion that the relationship between collision probability and minimum contention window size and the relationship ...In order to improve the broadcast reception rates of beacon messages in vehicle ad-hoc networks,a conclusion that the relationship between collision probability and minimum contention window size and the relationship between expiration probability and minimum window size was reached by building a Markov model. According to this conclusion, a back-off algorithm based on adjusting the size of minimum contention window called CEB is proposed, and this algorithm is on the basis of the differential size between the number of expiration beacons and preset threshold. Simulations were done to compare the performance of CEB with that of RBEB and BEB, and the results show that the performance of the new proposed algorithm is better than that of RBEB and BEB.展开更多
For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed...For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed to model the time-varying channel,which converts the channel estimation into the estimation of the basis coefficient.Specifically,the initial basis coefficients are firstly used to train the neural network in an offline manner,and then the high-precision channel estimation can be obtained by small number of inputs.Moreover,the linear minimum mean square error(LMMSE) estimated channel is considered for the loss function in training phase,which makes the proposed method more practical.Simulation results show that the proposed method has a better performance and lower computational complexity compared with the available schemes,and it is robust to the fast time-varying channel in the high-speed mobile scenarios.展开更多
In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper...In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes.展开更多
Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One ...Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.展开更多
Intelligent Reflecting Surface (IRS) can offer unprecedented channel capacity gains since it can reconfigure the signal propagation environment. We decide to maximize the channel capacity by jointly optimizing the tra...Intelligent Reflecting Surface (IRS) can offer unprecedented channel capacity gains since it can reconfigure the signal propagation environment. We decide to maximize the channel capacity by jointly optimizing the transmit-power-constrained precoding matrix at the base station and the unit-modulus-constrained phase shift vector at the IRS in IRS-assisted multi-user downlink communication. We first convert the resulting non-convex problem into an equivalent problem, then use the alternate optimization algorithm. While fixing the phase shift vector, we can obtain the optimal precoding matrix directly by adopting standard optimization packages. While fixing the precoding matrix, we propose the Riemannian Trust-Region (RTR) algorithm to solve this optimization problem. And the key of the RTR algorithm is the solution of the trust-region sub-problem. We first adopt the accurate solution based on Newton's (ASNT) method to solve this sub-problem, which can obtain the global solution but cannot guarantee that the solution is optimal since the initial iteration point is difficult to choose. Then, we propose the Improved-Polyline (IPL) method, which can avoid the difficulty of the ASNT method and improve convergence speed and calculation efficiency. The numerical results show that the RTR algorithm has more significant performance gains and faster convergence speed compared with the existing approaches.展开更多
Based on the three-dimensional Liu system with a nonlinear term of square, this paper appends a state variable to the system, and further adds a driving signal of the sine signal to construct a novel 4-demensional non...Based on the three-dimensional Liu system with a nonlinear term of square, this paper appends a state variable to the system, and further adds a driving signal of the sine signal to construct a novel 4-demensional nonautonomous hyperchaotic Liu system. The appended variable is formed by the product of the nonlinear quadratic term of the original state variables and the driving signal. Through adjusting the frequency of the driving signal, the system can be controlled to show some different dynamic behaviors. By numerical simulations, the Lyapunov exponent spectrums, bifurcation diagrams and phase diagrams of the novel systems are analyzed. Furthermore, the corresponding hardware circuits are implemented. Both the experimental results and the simulation results confirm that the method is feasible. The method, which adjusts the frequency of the input sine signal to control the system to show different dynamic behaviors, can make the dynamic property of the system become more complex, but easier to be controlled accurately as well.展开更多
In the fifth-generation new radio(5G-NR) high-speed railway(HSR) downlink,a deep learning(DL) based Doppler frequency offset(DFO) estimation scheme is proposed by using the back propagation neural network(BPNN).The pr...In the fifth-generation new radio(5G-NR) high-speed railway(HSR) downlink,a deep learning(DL) based Doppler frequency offset(DFO) estimation scheme is proposed by using the back propagation neural network(BPNN).The proposed method mainly includes pre-training,training,and estimation phases,where the pre-training and training belong to the off-line stage,and the estimation is the online stage.To reduce the performance loss caused by the random initialization,the pre-training method is employed to acquire a desirable initialization,which is used as the initial parameters of the training phase.Moreover,the initial DFO estimation is used as input along with the received pilots to further improve the estimation accuracy.Different from the training phase,the initial DFO estimation in pre-training phase is obtained by the data and pilot symbols.Simulation results show that the mean squared error(MSE) performance of the proposed method is better than those of the available algorithms,and it has acceptable computational complexity.展开更多
An adaptive object tracking algorithm based on particle filtering and a modified Gradient Vector Flow (GVF) Snake is proposed for tracking moving and deforming objects. The original contours of objects are obtained by...An adaptive object tracking algorithm based on particle filtering and a modified Gradient Vector Flow (GVF) Snake is proposed for tracking moving and deforming objects. The original contours of objects are obtained by using the background differencing method,and the true contours of objects can be converged by means of the powerful searching ability of a modified GVF-Snake. Finally,an Energetic Particle Filtering (EPF) algorithm is obtained by combining particle filtering and a modified GVF-Snake,and by using K-means and the EPF algorithm,multiple objects can be tracked. The proposed tracking tactic for partially occluded objects can effectively improve its anti-occlusion ability. Experiments show that this algorithm can obtain better tracking effect even though the tracked object is occluded.展开更多
In order to better assess the performance of wireless communication systems,it is desirable to produce multiple Rayleigh fading envelopes with specified correlations.In this paper,we analyze theoretically a procedure ...In order to better assess the performance of wireless communication systems,it is desirable to produce multiple Rayleigh fading envelopes with specified correlations.In this paper,we analyze theoretically a procedure which generates correlated Gaussian random variables from independent Gaussian random variables and give a physical explanation for the limitation of this procedure.Then,based on some uncorrelated Rayleigh fading envelopes,a simple but efficient procedure for generating an arbitrary number of cross-correlated Rayleigh fading envelopes is proposed.Simulation results and computational complexity analysis are presented,which show that the proposed method has some advantages,such as high accuracy,low computational complexity and easy implementation,over the conventional simulation method.展开更多
According to the analysis of the problem of contract management, financial settlement and placement of coal trucks in coal business, a study is made on the coal management system. This system combines B/S and C/S toge...According to the analysis of the problem of contract management, financial settlement and placement of coal trucks in coal business, a study is made on the coal management system. This system combines B/S and C/S together, and it also uses three-tire application of ASP.NET which sets up a business subsystem based on functional module management in vehicle. Additionally, MFC solves the problems in weighing management systems. This system goes with unit testing, integration testing, and system testing, and the whole process realizes an effective monitoring from coal trucks applying for delivery, checking in, and weighing to checking out. Besides, it also secures precise and accurate weighing data, and deals with the new coming coal contract in a faster way. The real project indicates this system wins a very good reputation and it is worthy of spreading in a broader context.展开更多
In response to the challenge posed by the complexity of the system and the difficulty in obtaining accurate channel state information(CSI)for millimeter wave communication assisted by intelligent reflecting surfaces(I...In response to the challenge posed by the complexity of the system and the difficulty in obtaining accurate channel state information(CSI)for millimeter wave communication assisted by intelligent reflecting surfaces(IRS),we propose a deep learning-based channel estimation scheme.The proposed scheme employs a hybrid active/passive IRS architecture,wherein the least square(LS)algorithm is initially utilized to acquire the channel estimate from the active elements.Subsequently,this estimation is interpolated to obtain a preliminary channel estimation and ultimately refined into an accurate estimate of the channel using the channel super-resolution convolutional neural network(Chan-SRCNN)deep learning network.The simulation results demonstrate that the proposed scheme surpasses LS,orthogonal matching pursuit(OMP),synchronous OMP(SOMP),and deep neural network(DNN)channel estimation algorithms in terms of normalized mean squared error(NMSE)performance,thereby validating the feasibility of the proposed approach.展开更多
Modified largest weighted delay first （M-LWDF） is a typical packet scheduling algorithm for supporting hybrid real-time services over wireless networks. However, so far, there is little literature available regardin...Modified largest weighted delay first （M-LWDF） is a typical packet scheduling algorithm for supporting hybrid real-time services over wireless networks. However, so far, there is little literature available regarding the theoretic analysis of M-LWDF fairness. This paper gives a theoretic analysis of M-LWDF fairness, which shows that M-LWDF fairness is related to channel condition, packet＇s arrival process and the ratio of quality of service （QoS） requirements of different service queues. Given service QoS requirements and other parameters related to channel model and packet＇s arrival process, the fairness is merely related to the ratio of the number of users in the service queues. Based on the analysis, an enhanced M-LWDF algorithm （EM-LWDF） is proposed and demonstrated in this paper. EM-LWDF is strictly designed in light of the fairness criteria of QoS requirements, so its fairness is almost not related to the ratio of the number of users in the service queues, and the theoretical value of fairness index is equal to 1. Simulation results validate the theoretic analysis and show the effectiveness of EM-LWDF in improving fairness.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.61179027)the Qinglan Project of Jiangsu Province of China(Grant No.QL06212006)the University Postgraduate Research and Innovation Project of Jiangsu Province(Grant Nos.KYLX15_0829,KYLX15_0831)
文摘In this paper, we propose a parameter allocation scheme in a parallel array bistable stochastic resonance-based communication system(P-BSR-CS) to improve the performance of weak binary pulse amplitude modulated(BPAM) signal transmissions. The optimal parameter allocation policy of the P-BSR-CS is provided to minimize the bit error rate(BER)and maximize the channel capacity(CC) under the adiabatic approximation condition. On this basis, we further derive the best parameter selection theorem in realistic communication scenarios via variable transformation. Specifically, the P-BSR structure design not only brings the robustness of parameter selection optimization, where the optimal parameter pair is not fixed but variable in quite a wide range, but also produces outstanding system performance. Theoretical analysis and simulation results indicate that in the P-BSR-CS the proposed parameter allocation scheme yields considerable performance improvement, particularly in very low signal-to-noise ratio(SNR) environments.
基金supported by the National Key Research and Development Project under Grant 2020YFB1807602Key Program of Marine Economy Development Special Foundation of Department of Natural Resources of Guangdong Province(GDNRC[2023]24)the National Natural Science Foundation of China under Grant 62271267.
文摘Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the research and applications of natural language processing across different modalities,our goal is to accurately extract frame-level semantic information from videos and ultimately transmit high-quality videos.Specifically,we propose a deep learning-basedMulti-ModalMutual Enhancement Video Semantic Communication system,called M3E-VSC.Built upon a VectorQuantized Generative AdversarialNetwork(VQGAN),our systemaims to leverage mutual enhancement among different modalities by using text as the main carrier of transmission.With it,the semantic information can be extracted fromkey-frame images and audio of the video and performdifferential value to ensure that the extracted text conveys accurate semantic information with fewer bits,thus improving the capacity of the system.Furthermore,a multi-frame semantic detection module is designed to facilitate semantic transitions during video generation.Simulation results demonstrate that our proposed model maintains high robustness in complex noise environments,particularly in low signal-to-noise ratio conditions,significantly improving the accuracy and speed of semantic transmission in video communication by approximately 50 percent.
基金partially the Chongqing Municipality’s Major Theme Project “R & D and Application of 5G terminal simulation equipment” (Grant No. Cstc2017zdcy-zdzx0030)
文摘The initial cell search plays an important role during the process of downlink synchronization establishment between the User Equipment(UE) and the base station. In particular, the uncertainty of the synchronization signals on the frequency domain and the flexibility of frame structure configuration have brought great challenges to the initial cell search for the fifth-generation(5G) new radio(NR). To solve this problem, firstly, we analyze the physical layer frame structure of 5G NR systems. Then, by focusing on the knowledge of synchronization signals, the 5G NR cell search process is designed, and the primary synchronization signal(PSS) timing synchronization algorithm is proposed, including a 5G-based coarse synchronization algorithm and conjugate symmetry-based fine synchronization algorithm. Finally, the performance of the proposed cell search algorithm in 5G NR systems is verified through the combination of Digital Signal Processing(DSP) and personal computer(PC). And the MATLAB simulation proves that the proposed algorithm has better performance than the conventional cross-correlation algorithm when a certain frequency offset exists.
基金Project supported by the National Natural Science Foundation of China (Grant No 60572089)the Natural Science Foundation of Chongqing (Grant No CSTC,2008BB2087)
文摘Based on the three-dimensional Liu chaotic system, this paper appends a feedback variable to construct a novel hyperchaotic Liu system. Then, a control signal is further added to construct a novel nonautonomous hyperchaotic Liu system. Through adjusting the frequency of the control signal, the chaotic property of the system can be controlled to show some different dynamic behaviors such as periodic, quasi-periodic, chaotic and hyperchaotic dynamic behaviours. By numerical simulations, the Lyapunov exponent spectrums, bifurcation diagrams and phase diagrams of the two new systems are studied, respectively. Furthermore, the synchronizing circuits of the nonautonomous hyperchaotic Liu system are designed via the synchronization control method of single variable coupling feedback. Finally, the hardware circuits are implemented, and the corresponding waves of chaos are observed by an oscillograph.
基金Supported by the National Natural Science Foundation of China(No.U19B2015,62271386,61801371).
文摘Spatially-coupled low-density parity-check(SC-LDPC)codes are prominent candidates for fu-ture communication standards due to their‘threshold saturation’properties.However,when facing burst erasures,the decoding process will stop and the decoding performances will dramatically de-grade.To improve the ability of burst erasure corrections,this paper proposes a two-dimensional SC-LDPC(2D-SC-LDPC)codes constructed by parallelly connecting two asymmetric SC-LDPC coupled chains for resistance to burst erasures.Density evolution algorithm is presented to evaluate the as-ymptotic performances against burst erasures,by which the maximum correctable burst erasure length can be computed.The analysis results show that the maximum correctable burst erasure lengths of the proposed 2D-SC-LDPC codes are much larger than the SC-LDPC codes and the asym-metric SC-LDPC codes.Finite-length performance simulation results of the 2D-SC-LDPC codes over the burst erasure channel confirm the excellent asymptotic performances.
文摘How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.
基金Project supported by the National Natural Science Foundation of China (Grant No. 60972069)the Science and Technology Foundation of the Education Department of Chongqing (Grant No. KJ090513)
文摘This paper proposed a method of generating two attractors in a novel grid multi-scroll chaotic system. Based on a newly generated three-dimensional system, a two-attractor grid multi-scroll attractor system can be generated by adding two triangular waves and a sign function. Some basic dynamical properties, such as equilibrium points, bifurcations, and phase diagrams, were studied. Furthermore, the system was experimentally confirmed by an electronic circuit. The circuit simulation results and numerical simulation results verified the feasibility of this method.
基金supported by National Basic Research Program of China (2013CB329005)National Natural Science Foundation of China (61302100, 61201162, 61471203)+1 种基金Basic Research Program of Jiangsu Province (BK2011027)Specialized Research Fund for the Doctoral Program of Higher Education (20133223120002)
文摘In order to improve the broadcast reception rates of beacon messages in vehicle ad-hoc networks,a conclusion that the relationship between collision probability and minimum contention window size and the relationship between expiration probability and minimum window size was reached by building a Markov model. According to this conclusion, a back-off algorithm based on adjusting the size of minimum contention window called CEB is proposed, and this algorithm is on the basis of the differential size between the number of expiration beacons and preset threshold. Simulations were done to compare the performance of CEB with that of RBEB and BEB, and the results show that the performance of the new proposed algorithm is better than that of RBEB and BEB.
基金Supported by the National Science Foundation Program of Jiangsu Province (No.BK20191378)the National Science Research Project of Jiangsu Higher Education Institutions (No.18KJB510034)+2 种基金China Postdoctoral Science Fund Special Funding Project (No.2018T110530)the Key Technologies R&D Program of Jiangsu Province (No.BE2022067,BE2022067-2)Major Research Program Key Project(No.92067201)。
文摘For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed to model the time-varying channel,which converts the channel estimation into the estimation of the basis coefficient.Specifically,the initial basis coefficients are firstly used to train the neural network in an offline manner,and then the high-precision channel estimation can be obtained by small number of inputs.Moreover,the linear minimum mean square error(LMMSE) estimated channel is considered for the loss function in training phase,which makes the proposed method more practical.Simulation results show that the proposed method has a better performance and lower computational complexity compared with the available schemes,and it is robust to the fast time-varying channel in the high-speed mobile scenarios.
基金supported by the National Natural Science Foundation of China under Grants No.60972038,No.61001077,No.61101105 the Scientific Research Foundation for Nanjing University of Posts and Telecommunications under Grant No.NY211007+2 种基金 the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2011D05 Specialized Research Fund for the Doctoral Program of Higher Education under Grant No.20113223120002 University Natural Science Research Project of Jiangsu Province under Grant No.11KJB510016
文摘In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes.
基金supported by the National Basic Research Program of China (973 Program) under Grant 2013CB329104the National Natural Science Foundation of China under Grant 61372124 and 61427801the Key Projects of Natural Science Foundation of Jiangsu University under Grant 11KJA510001
文摘Network virtualization(NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks(VNs) with different protocols to coexist on a shared substrate network(SN). One main challenge in NV is virtual network embedding(VNE). VNE is a NPhard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in smallscaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT(Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNERSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNERSOT, a simulation against typical and stateof-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request(VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.
基金supported by the General Program of Natural Science Foudation of Chongqing Province of China(cstc2021jcyj-msxmX0454)
文摘Intelligent Reflecting Surface (IRS) can offer unprecedented channel capacity gains since it can reconfigure the signal propagation environment. We decide to maximize the channel capacity by jointly optimizing the transmit-power-constrained precoding matrix at the base station and the unit-modulus-constrained phase shift vector at the IRS in IRS-assisted multi-user downlink communication. We first convert the resulting non-convex problem into an equivalent problem, then use the alternate optimization algorithm. While fixing the phase shift vector, we can obtain the optimal precoding matrix directly by adopting standard optimization packages. While fixing the precoding matrix, we propose the Riemannian Trust-Region (RTR) algorithm to solve this optimization problem. And the key of the RTR algorithm is the solution of the trust-region sub-problem. We first adopt the accurate solution based on Newton's (ASNT) method to solve this sub-problem, which can obtain the global solution but cannot guarantee that the solution is optimal since the initial iteration point is difficult to choose. Then, we propose the Improved-Polyline (IPL) method, which can avoid the difficulty of the ASNT method and improve convergence speed and calculation efficiency. The numerical results show that the RTR algorithm has more significant performance gains and faster convergence speed compared with the existing approaches.
基金supported by the National Natural Science Foundation of China (Grant No 60572089)the Natural Science Foundation of Chongqing (Grant No CSTC,2008BB2087)
文摘Based on the three-dimensional Liu system with a nonlinear term of square, this paper appends a state variable to the system, and further adds a driving signal of the sine signal to construct a novel 4-demensional nonautonomous hyperchaotic Liu system. The appended variable is formed by the product of the nonlinear quadratic term of the original state variables and the driving signal. Through adjusting the frequency of the driving signal, the system can be controlled to show some different dynamic behaviors. By numerical simulations, the Lyapunov exponent spectrums, bifurcation diagrams and phase diagrams of the novel systems are analyzed. Furthermore, the corresponding hardware circuits are implemented. Both the experimental results and the simulation results confirm that the method is feasible. The method, which adjusts the frequency of the input sine signal to control the system to show different dynamic behaviors, can make the dynamic property of the system become more complex, but easier to be controlled accurately as well.
基金Supported by the National Science Foundation Program of Jiangsu Province(No.BK20191378)the National Science Research Project of Jiangsu Higher Education Institutions(No.18KJB510034)+1 种基金the 11th Batch of China Postdoctoral Science Fund Special Funding Project(No.2018T110530)the National Natural Science Foundation of China(No.61771255)。
文摘In the fifth-generation new radio(5G-NR) high-speed railway(HSR) downlink,a deep learning(DL) based Doppler frequency offset(DFO) estimation scheme is proposed by using the back propagation neural network(BPNN).The proposed method mainly includes pre-training,training,and estimation phases,where the pre-training and training belong to the off-line stage,and the estimation is the online stage.To reduce the performance loss caused by the random initialization,the pre-training method is employed to acquire a desirable initialization,which is used as the initial parameters of the training phase.Moreover,the initial DFO estimation is used as input along with the received pilots to further improve the estimation accuracy.Different from the training phase,the initial DFO estimation in pre-training phase is obtained by the data and pilot symbols.Simulation results show that the mean squared error(MSE) performance of the proposed method is better than those of the available algorithms,and it has acceptable computational complexity.
基金Supported by the Significant Term of Science and Technology Research in Ministry of Education (No. 205060)Open Research Fund of National Mobile Communications Research Laboratory,Southeast University (N200911)+2 种基金Significant Basic Research of Jiangsu Province Colleges and Universities Natural Science Projects (07 KJA51006)Research Fund of Nanjing College of Traffic Vocational Technology (JY0903)Huawei Science and Technology Fund
文摘An adaptive object tracking algorithm based on particle filtering and a modified Gradient Vector Flow (GVF) Snake is proposed for tracking moving and deforming objects. The original contours of objects are obtained by using the background differencing method,and the true contours of objects can be converged by means of the powerful searching ability of a modified GVF-Snake. Finally,an Energetic Particle Filtering (EPF) algorithm is obtained by combining particle filtering and a modified GVF-Snake,and by using K-means and the EPF algorithm,multiple objects can be tracked. The proposed tracking tactic for partially occluded objects can effectively improve its anti-occlusion ability. Experiments show that this algorithm can obtain better tracking effect even though the tracked object is occluded.
基金the National Natural Science Foundation of China (No.60572130)Jiangsu Provincial Natural Science Foundation (BK2006235)
文摘In order to better assess the performance of wireless communication systems,it is desirable to produce multiple Rayleigh fading envelopes with specified correlations.In this paper,we analyze theoretically a procedure which generates correlated Gaussian random variables from independent Gaussian random variables and give a physical explanation for the limitation of this procedure.Then,based on some uncorrelated Rayleigh fading envelopes,a simple but efficient procedure for generating an arbitrary number of cross-correlated Rayleigh fading envelopes is proposed.Simulation results and computational complexity analysis are presented,which show that the proposed method has some advantages,such as high accuracy,low computational complexity and easy implementation,over the conventional simulation method.
文摘According to the analysis of the problem of contract management, financial settlement and placement of coal trucks in coal business, a study is made on the coal management system. This system combines B/S and C/S together, and it also uses three-tire application of ASP.NET which sets up a business subsystem based on functional module management in vehicle. Additionally, MFC solves the problems in weighing management systems. This system goes with unit testing, integration testing, and system testing, and the whole process realizes an effective monitoring from coal trucks applying for delivery, checking in, and weighing to checking out. Besides, it also secures precise and accurate weighing data, and deals with the new coming coal contract in a faster way. The real project indicates this system wins a very good reputation and it is worthy of spreading in a broader context.
文摘In response to the challenge posed by the complexity of the system and the difficulty in obtaining accurate channel state information(CSI)for millimeter wave communication assisted by intelligent reflecting surfaces(IRS),we propose a deep learning-based channel estimation scheme.The proposed scheme employs a hybrid active/passive IRS architecture,wherein the least square(LS)algorithm is initially utilized to acquire the channel estimate from the active elements.Subsequently,this estimation is interpolated to obtain a preliminary channel estimation and ultimately refined into an accurate estimate of the channel using the channel super-resolution convolutional neural network(Chan-SRCNN)deep learning network.The simulation results demonstrate that the proposed scheme surpasses LS,orthogonal matching pursuit(OMP),synchronous OMP(SOMP),and deep neural network(DNN)channel estimation algorithms in terms of normalized mean squared error(NMSE)performance,thereby validating the feasibility of the proposed approach.
基金supported by the National Natural Science Foundation of China (60972068)the Basic Application Research Program of Chongqing Education Committee of China (KJ090502,KJ100517)+1 种基金the Graduate Innovation Program of Chongqing University of China (200904B1A0010306)the Youth Program Foundation of Chongqing University of Posts and Telecommunications of China (A2008-28)
文摘Modified largest weighted delay first （M-LWDF） is a typical packet scheduling algorithm for supporting hybrid real-time services over wireless networks. However, so far, there is little literature available regarding the theoretic analysis of M-LWDF fairness. This paper gives a theoretic analysis of M-LWDF fairness, which shows that M-LWDF fairness is related to channel condition, packet＇s arrival process and the ratio of quality of service （QoS） requirements of different service queues. Given service QoS requirements and other parameters related to channel model and packet＇s arrival process, the fairness is merely related to the ratio of the number of users in the service queues. Based on the analysis, an enhanced M-LWDF algorithm （EM-LWDF） is proposed and demonstrated in this paper. EM-LWDF is strictly designed in light of the fairness criteria of QoS requirements, so its fairness is almost not related to the ratio of the number of users in the service queues, and the theoretical value of fairness index is equal to 1. Simulation results validate the theoretic analysis and show the effectiveness of EM-LWDF in improving fairness.
