A robust radio map is essential in implementing a fingerprint-based indoor positioning system(IPS).However,the offline site survey to manually construct the radio map is time-consuming and labour-intensive.Various int...A robust radio map is essential in implementing a fingerprint-based indoor positioning system(IPS).However,the offline site survey to manually construct the radio map is time-consuming and labour-intensive.Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys.This paper presents a novel fingerprint interpolator using a multi-path loss model(MPLM)to create the virtual fingerprints from the collected sample data based on different signal paths from different access points(APs).Based on the historical signal data,the poor signal paths are identified using their standard deviations.The proposed method reduces the positioning errors by smoothing out the wireless signal fluctuations and stabilizing the signals for those poor signal paths.By consideringmultipath signal propagations from different APs,the inherent noise from these signal paths can be alleviated.Firstly,locations of the signal data with standard deviations higher than the threshold are identified.The new fingerprints are then generated at these locations based on the proposed M-PLM interpolation function to replace the old fingerprints.The proposed technique interpolates virtual fingerprints based on good signal paths with more stable signals to improve the positioning performance.Experimental results show that the proposed scheme enhances the positioning accuracy by up to 44%compared to the conventional interpolation techniques such as the Inverse DistanceWeighting,Kriging,and single Path LossModel.As a result,we can overcome the site survey problems for IPS by building an accurate radio map with more reliable signals to improve indoor positioning performance.展开更多
This paper proposes modifications to the tradional Ceiling Bounce Model and uses it to characterize diffuse indoor optical wireless channel by analyzing the effect of transceiver position on signal propagation propert...This paper proposes modifications to the tradional Ceiling Bounce Model and uses it to characterize diffuse indoor optical wireless channel by analyzing the effect of transceiver position on signal propagation properties. The modified approach uses a combination of the tradional ceiling bounce method and a statistical approach. The effects of different transmitter-receiver separations and height of the ceiling on path loss and delay spread are studied in detail.展开更多
When there are bigger obstacles in the indoor environment such as elevator, the radio waves basically can not penetrate it. The contribution of received signal strength by transmission and reflection will be greatly r...When there are bigger obstacles in the indoor environment such as elevator, the radio waves basically can not penetrate it. The contribution of received signal strength by transmission and reflection will be greatly reduced, and most of the time, the radio waves will reach the user by bypass diffraction. Therefore, the traditional path loss model is no longer applicable, and the improved model should be proposed. In this paper, we firstly proposed an indoor radio propagation model based on dominant path in which the received signal strength has nothing to do with the direct distance between user and access point, but is related to the length of dominant path. Then on the basis of dominant path model, the NLOS influence is considered in order to further improve the accuracy of dominant path model. Experimental results demonstrated that the proposed dominant path model can improve the accuracy of traditional path loss model remarkably.展开更多
In 5G era,it is expected to achieve wireless network coverage including offshore areas.Modeling of marine wireless channels is the basis of constructing a marine communication system.In this paper,a communication scen...In 5G era,it is expected to achieve wireless network coverage including offshore areas.Modeling of marine wireless channels is the basis of constructing a marine communication system.In this paper,a communication scene between an unmanned aerial vehicle(UAV)and a boat is simulated to study the marine wireless channel.Firstly,an improved spatial partitioning ray tracing algorithm is proposed to track the propagation path of electromagnetic waves at sea surface.Secondly,a mobile channel is simulated and modeled based on the track results.Finally,a loss measurement is carried out in the coastal waters based on the simple wireless channel loss measuring platform,and a path loss propagation model is built.Then we compare the actual measurement data with the simulation results and find that the two are have good consistency,which further verifies the reliability of the simulation.展开更多
In recent years,high-speed railways(HSRs)have developed rapidly with a high transportation capacity and high comfort level.A tunnel is a complex high-speed rail terrain environment.It is very important to establish an...In recent years,high-speed railways(HSRs)have developed rapidly with a high transportation capacity and high comfort level.A tunnel is a complex high-speed rail terrain environment.It is very important to establish an accurate channel propagation model for a railway tunnel environment to improve the safety of HSR operation.In this paper,a method for finite-state Markov chain(FSMC)channel modeling with least squares fitting based on non-uniform interval division is proposed.First,a path loss model is obtained according to measured data.The communication distance between the transmitter and receiver in the tunnel is non-uniformly divided into several large non-overlapping intervals based on the path loss model.Then,the Lloyd-Max quantization method is used to determine the threshold of the signal-to-noise ratio(SNR)and the channel state quantization value and obtain the FSMC state transition probability matrix.Simulation experiments show that the proposed wireless channel model has a low mean square error(MSE)and can accurately predict the received signal power in a railway tunnel environment.展开更多
针对煤矿井下复杂环境中第五代移动通信技术(5th-Generation Mobile Communication Technology,5G)网络覆盖性能优化的问题,提出一种基于深度强化学习的矿井5G优化方案。面向10 km主运巷道场景,综合考虑巷道截面尺寸、壁面粗糙度、设备...针对煤矿井下复杂环境中第五代移动通信技术(5th-Generation Mobile Communication Technology,5G)网络覆盖性能优化的问题,提出一种基于深度强化学习的矿井5G优化方案。面向10 km主运巷道场景,综合考虑巷道截面尺寸、壁面粗糙度、设备遮挡等多重传输损耗因素,建立融合视距/非视距路径损耗模型与粗糙度衰减因子的信号传播数学模型。将深度Q网络作为价值函数近似器的强化学习智能体,并通过基站部署与发射功率将在线优化转化为多目标决策问题,以最小基站数量实现覆盖率最大化。采用动态功率调整机制,以实时优化基站发射功率,从而适应局部信号衰减的突发变化。实验结果表明,该方案可以实现95%以上的覆盖率,相较于传统静态方案减少了28%基站部署,显著提升了井下5G网络覆盖性能,并能够降低部署成本与运行功耗。展开更多
针对传统信号传播路径损耗模型接收的信号强度指示(received signal strength indication,RSSI)测距误差较大,提出了基于反向传播(back propagation,BP)神经网络模型的RSSI测距方法.首先,研究分析传统信号传播路径损耗模型及测距误差;其...针对传统信号传播路径损耗模型接收的信号强度指示(received signal strength indication,RSSI)测距误差较大,提出了基于反向传播(back propagation,BP)神经网络模型的RSSI测距方法.首先,研究分析传统信号传播路径损耗模型及测距误差;其次,利用BP神经网络构建新的路径损耗模型,并将该模型应用到RSSI测距中,对基于BP神经网络模型的RSSI测距方法进行研究;最后,通过实验和MATLAB仿真对测距方法进行验证.仿真结果表明:BP神经网络模型的RSSI测距误差比传统信号传播路径损耗模型的RSSI测距误差要小.展开更多
基金funded by the Ministry of Higher EducationMalaysia under the Fundamental Research Grant Scheme(FRGS)with grant number FRGS/1/2019/ICT02/MMU/02/1.
文摘A robust radio map is essential in implementing a fingerprint-based indoor positioning system(IPS).However,the offline site survey to manually construct the radio map is time-consuming and labour-intensive.Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys.This paper presents a novel fingerprint interpolator using a multi-path loss model(MPLM)to create the virtual fingerprints from the collected sample data based on different signal paths from different access points(APs).Based on the historical signal data,the poor signal paths are identified using their standard deviations.The proposed method reduces the positioning errors by smoothing out the wireless signal fluctuations and stabilizing the signals for those poor signal paths.By consideringmultipath signal propagations from different APs,the inherent noise from these signal paths can be alleviated.Firstly,locations of the signal data with standard deviations higher than the threshold are identified.The new fingerprints are then generated at these locations based on the proposed M-PLM interpolation function to replace the old fingerprints.The proposed technique interpolates virtual fingerprints based on good signal paths with more stable signals to improve the positioning performance.Experimental results show that the proposed scheme enhances the positioning accuracy by up to 44%compared to the conventional interpolation techniques such as the Inverse DistanceWeighting,Kriging,and single Path LossModel.As a result,we can overcome the site survey problems for IPS by building an accurate radio map with more reliable signals to improve indoor positioning performance.
文摘This paper proposes modifications to the tradional Ceiling Bounce Model and uses it to characterize diffuse indoor optical wireless channel by analyzing the effect of transceiver position on signal propagation properties. The modified approach uses a combination of the tradional ceiling bounce method and a statistical approach. The effects of different transmitter-receiver separations and height of the ceiling on path loss and delay spread are studied in detail.
文摘When there are bigger obstacles in the indoor environment such as elevator, the radio waves basically can not penetrate it. The contribution of received signal strength by transmission and reflection will be greatly reduced, and most of the time, the radio waves will reach the user by bypass diffraction. Therefore, the traditional path loss model is no longer applicable, and the improved model should be proposed. In this paper, we firstly proposed an indoor radio propagation model based on dominant path in which the received signal strength has nothing to do with the direct distance between user and access point, but is related to the length of dominant path. Then on the basis of dominant path model, the NLOS influence is considered in order to further improve the accuracy of dominant path model. Experimental results demonstrated that the proposed dominant path model can improve the accuracy of traditional path loss model remarkably.
基金National Natural Science Foundation of China(Grant number 61971365)National Natural Science Foundation of China(Grant number 61871339)+1 种基金National Natural Science Foundation of China(Grant number 61901403)Xiamen Science and Technology Plan Project(No.3502Z20183008).
文摘In 5G era,it is expected to achieve wireless network coverage including offshore areas.Modeling of marine wireless channels is the basis of constructing a marine communication system.In this paper,a communication scene between an unmanned aerial vehicle(UAV)and a boat is simulated to study the marine wireless channel.Firstly,an improved spatial partitioning ray tracing algorithm is proposed to track the propagation path of electromagnetic waves at sea surface.Secondly,a mobile channel is simulated and modeled based on the track results.Finally,a loss measurement is carried out in the coastal waters based on the simple wireless channel loss measuring platform,and a path loss propagation model is built.Then we compare the actual measurement data with the simulation results and find that the two are have good consistency,which further verifies the reliability of the simulation.
基金partially supported by Nation Science Foundation of China (61661025, 61661026)Foundation of A hundred Youth Talents Training Program of Lanzhou Jiaotong University (152022)
文摘In recent years,high-speed railways(HSRs)have developed rapidly with a high transportation capacity and high comfort level.A tunnel is a complex high-speed rail terrain environment.It is very important to establish an accurate channel propagation model for a railway tunnel environment to improve the safety of HSR operation.In this paper,a method for finite-state Markov chain(FSMC)channel modeling with least squares fitting based on non-uniform interval division is proposed.First,a path loss model is obtained according to measured data.The communication distance between the transmitter and receiver in the tunnel is non-uniformly divided into several large non-overlapping intervals based on the path loss model.Then,the Lloyd-Max quantization method is used to determine the threshold of the signal-to-noise ratio(SNR)and the channel state quantization value and obtain the FSMC state transition probability matrix.Simulation experiments show that the proposed wireless channel model has a low mean square error(MSE)and can accurately predict the received signal power in a railway tunnel environment.
文摘针对煤矿井下复杂环境中第五代移动通信技术(5th-Generation Mobile Communication Technology,5G)网络覆盖性能优化的问题,提出一种基于深度强化学习的矿井5G优化方案。面向10 km主运巷道场景,综合考虑巷道截面尺寸、壁面粗糙度、设备遮挡等多重传输损耗因素,建立融合视距/非视距路径损耗模型与粗糙度衰减因子的信号传播数学模型。将深度Q网络作为价值函数近似器的强化学习智能体,并通过基站部署与发射功率将在线优化转化为多目标决策问题,以最小基站数量实现覆盖率最大化。采用动态功率调整机制,以实时优化基站发射功率,从而适应局部信号衰减的突发变化。实验结果表明,该方案可以实现95%以上的覆盖率,相较于传统静态方案减少了28%基站部署,显著提升了井下5G网络覆盖性能,并能够降低部署成本与运行功耗。
文摘针对传统信号传播路径损耗模型接收的信号强度指示(received signal strength indication,RSSI)测距误差较大,提出了基于反向传播(back propagation,BP)神经网络模型的RSSI测距方法.首先,研究分析传统信号传播路径损耗模型及测距误差;其次,利用BP神经网络构建新的路径损耗模型,并将该模型应用到RSSI测距中,对基于BP神经网络模型的RSSI测距方法进行研究;最后,通过实验和MATLAB仿真对测距方法进行验证.仿真结果表明:BP神经网络模型的RSSI测距误差比传统信号传播路径损耗模型的RSSI测距误差要小.
