We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adapt...We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.展开更多
This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state...This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.展开更多
We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path l...We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction methodology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75%and 103%,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.展开更多
Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) chann...Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) channels. It consists of a line-of-sight(Lo S) and non-line-of-sight(NLo S) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e.the temporal autocorrelation function(ACF) and spatial cross correlation function(CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture.展开更多
This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the ...This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the intensity levels, the open-access R-studio software was used based on the General Extreme Value (GEV) distribution function. Among the four linear parameter models adopted for integrating time as a covariate, the fourth linear model incorporating scale and location with the shape function constant produced the least corrected Akaike Information Criteria (AICc), varying between 306.191 to 101.497 for 15 and 1440 minutes, respectively, selected for calibration of the GEV distribution equation. The non-stationary intensities yielded higher values above those of stationary models, proving that the assumption of stationary IDF models underestimated extreme events. The difference of 13.71 mm/hr (22.71%) to 14.26 mm/hr (17.0%) intensities implies an underestimation of the peak flood from a stationary IDF curve. The statistical difference at a 95% confidence level between stationary and non-stationary models was significant, confirming evidence of climatic change influenced by time-variant parameters. Consequently, emphasis should be on applying shorter-duration storms for design purposes occurring with higher intensities to help reduce the flood risk and resultant infrastructural failures.展开更多
To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important...To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important communication scenarios in a wireless network.In this paper,we consider the effects of the Rician fading channel on the performance of cooperative device-to-device(D2D)communication with URLLC.For better performance,we maximize and examine the system’s minimal rate of D2D communication.Due to the interference in D2D communication,the problem of maximizing the minimum rate becomes non-convex and difficult to solve.To solve this problem,a learning-to-optimize-based algorithm is proposed to find the optimal power allocation.The conventional branch and bound(BB)algorithm are used to learn the optimal pruning policy with supervised learning.Ensemble learning is used to train the multiple classifiers.To address the imbalanced problem,we used the supervised undersampling technique.Comparisons are made with the conventional BB algorithm and the heuristic algorithm.The outcome of the simulation demonstrates a notable performance improvement in power consumption.The proposed algorithm has significantly low computational complexity and runs faster as compared to the conventional BB algorithm and a heuristic algorithm.展开更多
The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity g...The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity gain. The development of an analytical mathematical model of ensuring security in multicasting through fading channels incorporating this benefit of multi-hop relaying is still an open problem. Motivated by this issue, this paper considers a secure wireless multicasting scenario employing multi-hop relaying technique over frequency selective Nakagami-m fading channel and develops an analytical mathematical model to ensure the security against multiple eavesdroppers. This mathematical model has been developed based on the closed-form analytical expressions of the probability of non-zero secrecy multicast capacity (PNSMC) and the secure outage probability for multicasting (SOPM) to ensure the security in the presence of multiple eavesdroppers. Moreover, the effects of the fading parameter of multicast channel, the number of hops and eavesdropper are investigated. The results show that the security in multicasting through Nakagami-m fading channel with multi-hop relaying system is more sensitive to the number of hops and eavesdroppers. The fading of multicast channel helps to improve the secrecy multicast capacity and is not the enemy of security in multicasting.展开更多
同时定位与建图(Simultaneous Localization and Mapping,SLAM)技术使移动机器人在缺乏先验环境信息的条件下,能够在估计自身位姿的同时构建环境地图。然而,在海洋、矿洞等复杂环境中,移动机器人容易受到随机突变噪声的干扰,进而导致SLA...同时定位与建图(Simultaneous Localization and Mapping,SLAM)技术使移动机器人在缺乏先验环境信息的条件下,能够在估计自身位姿的同时构建环境地图。然而,在海洋、矿洞等复杂环境中,移动机器人容易受到随机突变噪声的干扰,进而导致SLAM性能下降。现有的概率假设密度(Probability Hypothesis Density,PHD)SLAM算法未考虑随机突变噪声,受到干扰时在线自适应调整能力较弱。为解决移动机器人因随机突变噪声导致状态估计和建图精度降低的问题,本文结合强跟踪滤波器(Strong Tracking Filter,STF)与PHD滤波器,提出了一种基于强跟踪的自适应PHD-SLAM滤波算法(Strong Tracking Probability Hypothesis Density Simultaneous Localization and Mapping,STPHD-SLAM)。该算法以PHD-SLAM为框架,针对过程噪声协方差和量测噪声协方差随机突变问题,本文通过在特征预测协方差中引入STF中的渐消因子,实现了对特征预测的自适应修正和卡尔曼增益的动态调整,从而增强了算法的自适应能力。其中渐消因子根据量测新息递归更新,确保噪声突变时每个时刻的量测新息保持正交,从而充分利用量测信息,准确并且快速地跟踪突变噪声。针对渐消因子激增导致的滤波器发散问题,本文对渐消因子进行边界约束,提高算法的鲁棒性。仿真结果表明,在量测噪声协方差和过程噪声协方差随机突变的情况下,所提算法相较于PHD-SLAM 1.0和PHD-SLAM 2.0的定位和建图精度都得到了提高,同时保证了计算效率。展开更多
基金supported in part by the National Key R&D Project of China under Grant 2020YFA0712300National Natural Science Foundation of China under Grant NSFC-62231022,12031011supported in part by the NSF of China under Grant 62125108。
文摘We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.
基金supported by the National Natural Science Foundation of China under grant 61941106。
文摘This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.
文摘We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction methodology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75%and 103%,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.
基金supported by the National Natural Science Foundation of China,No.62271250the National Key Scientific Instrument and Equipment Development Project,No.61827801+3 种基金Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry),No.BE2022067,BE2022067-1 and BE2022067-3the Natural Science Foundation of Jiangsu Province,No.BK20211182the open research fund of National Mobile Communications Research Laboratory,Southeast University,No.2022D04the Experimental technology research and development,No.SYJS202304Z。
文摘Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) channels. It consists of a line-of-sight(Lo S) and non-line-of-sight(NLo S) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e.the temporal autocorrelation function(ACF) and spatial cross correlation function(CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture.
文摘This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the intensity levels, the open-access R-studio software was used based on the General Extreme Value (GEV) distribution function. Among the four linear parameter models adopted for integrating time as a covariate, the fourth linear model incorporating scale and location with the shape function constant produced the least corrected Akaike Information Criteria (AICc), varying between 306.191 to 101.497 for 15 and 1440 minutes, respectively, selected for calibration of the GEV distribution equation. The non-stationary intensities yielded higher values above those of stationary models, proving that the assumption of stationary IDF models underestimated extreme events. The difference of 13.71 mm/hr (22.71%) to 14.26 mm/hr (17.0%) intensities implies an underestimation of the peak flood from a stationary IDF curve. The statistical difference at a 95% confidence level between stationary and non-stationary models was significant, confirming evidence of climatic change influenced by time-variant parameters. Consequently, emphasis should be on applying shorter-duration storms for design purposes occurring with higher intensities to help reduce the flood risk and resultant infrastructural failures.
基金supported in part by the National Natural Science Foundation of China under Grant 61771410in part by the Sichuan Science and Technology Program 2023NSFSC1373in part by Postgraduate Innovation Fund Project of SWUST 23zx7101.
文摘To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important communication scenarios in a wireless network.In this paper,we consider the effects of the Rician fading channel on the performance of cooperative device-to-device(D2D)communication with URLLC.For better performance,we maximize and examine the system’s minimal rate of D2D communication.Due to the interference in D2D communication,the problem of maximizing the minimum rate becomes non-convex and difficult to solve.To solve this problem,a learning-to-optimize-based algorithm is proposed to find the optimal power allocation.The conventional branch and bound(BB)algorithm are used to learn the optimal pruning policy with supervised learning.Ensemble learning is used to train the multiple classifiers.To address the imbalanced problem,we used the supervised undersampling technique.Comparisons are made with the conventional BB algorithm and the heuristic algorithm.The outcome of the simulation demonstrates a notable performance improvement in power consumption.The proposed algorithm has significantly low computational complexity and runs faster as compared to the conventional BB algorithm and a heuristic algorithm.
文摘The additional diversity gain provided by the relays improves the secrecy capacity of communications system significantly. The multiple hops in the relaying system is an important technique to improve this diversity gain. The development of an analytical mathematical model of ensuring security in multicasting through fading channels incorporating this benefit of multi-hop relaying is still an open problem. Motivated by this issue, this paper considers a secure wireless multicasting scenario employing multi-hop relaying technique over frequency selective Nakagami-m fading channel and develops an analytical mathematical model to ensure the security against multiple eavesdroppers. This mathematical model has been developed based on the closed-form analytical expressions of the probability of non-zero secrecy multicast capacity (PNSMC) and the secure outage probability for multicasting (SOPM) to ensure the security in the presence of multiple eavesdroppers. Moreover, the effects of the fading parameter of multicast channel, the number of hops and eavesdropper are investigated. The results show that the security in multicasting through Nakagami-m fading channel with multi-hop relaying system is more sensitive to the number of hops and eavesdroppers. The fading of multicast channel helps to improve the secrecy multicast capacity and is not the enemy of security in multicasting.
文摘同时定位与建图(Simultaneous Localization and Mapping,SLAM)技术使移动机器人在缺乏先验环境信息的条件下,能够在估计自身位姿的同时构建环境地图。然而,在海洋、矿洞等复杂环境中,移动机器人容易受到随机突变噪声的干扰,进而导致SLAM性能下降。现有的概率假设密度(Probability Hypothesis Density,PHD)SLAM算法未考虑随机突变噪声,受到干扰时在线自适应调整能力较弱。为解决移动机器人因随机突变噪声导致状态估计和建图精度降低的问题,本文结合强跟踪滤波器(Strong Tracking Filter,STF)与PHD滤波器,提出了一种基于强跟踪的自适应PHD-SLAM滤波算法(Strong Tracking Probability Hypothesis Density Simultaneous Localization and Mapping,STPHD-SLAM)。该算法以PHD-SLAM为框架,针对过程噪声协方差和量测噪声协方差随机突变问题,本文通过在特征预测协方差中引入STF中的渐消因子,实现了对特征预测的自适应修正和卡尔曼增益的动态调整,从而增强了算法的自适应能力。其中渐消因子根据量测新息递归更新,确保噪声突变时每个时刻的量测新息保持正交,从而充分利用量测信息,准确并且快速地跟踪突变噪声。针对渐消因子激增导致的滤波器发散问题,本文对渐消因子进行边界约束,提高算法的鲁棒性。仿真结果表明,在量测噪声协方差和过程噪声协方差随机突变的情况下,所提算法相较于PHD-SLAM 1.0和PHD-SLAM 2.0的定位和建图精度都得到了提高,同时保证了计算效率。