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Improving the Performance of OFDM Channel Estimation through Subspace Projecting and Tracking

Dong Liang,Cao Xiuying,Bi Guangguo

Strategic Study of CAE 2006, Volume 8, Issue 11,   Pages 86-93

Abstract:

The LS channel estimation of OFDM systems can be viewed as a noisy observation of the true channel frequency response, so the noise component can be compressed through subspace projecting. In this paper, the substance of the improvement of LS channel estimation is analyzed when subspace projecting is enforced, and the general framework to perform subspace projecting in the context of OFDM channel estimation is given, based on which this method is exterded to non-LS channel estimation. When signal subspace varies with time, subspace tracking should be performed to maintain a good estimation of signal subspace. At the end of this paper, a subspace tracking based parametric channel estimator is presented, and computer simulation shows that this channel estimator outperforms its nonparametric counterparts.

Keywords： OFDM     subspace     projecting     tracking     channel estimation    

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Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond Research Articles

Zhao Yi, Weixia Zou, Xuebin Sun,yz17tx@bupt.edu.cn,zwx0218@bupt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6,   Pages 777-789 doi: 10.1631/FITEE.2000515

Abstract: (mmWave) has been claimed as the viable solution for high-bandwidth s in 5G and beyond. To realize applications in future s, it is important to take a robust mmWave vehicular network into consideration. However, one challenge in such a network is that mmWave should provide an ultra-fast and high-rate data exchange among vehicles or vehicle-to-infrastructure (V2I). Moreover, traditional real-time strategies are unavailable because vehicle mobility leads to a fast variation mmWave channel. To overcome these issues, a approach for mmWave V2I communications is proposed in this paper. Specifically, by considering a fast-moving vehicle secnario, a corresponding mathematical model for a fast channel is first established. Then, the temporal variation rule between the base station and each mobile user and the determined direction-of-arrival are used to predict the channel prior information (PI). Finally, by exploiting the PI and the characteristics of the channel, the channel is estimated. The simulation results show that the scheme in this paper outperforms traditional ones in both normalized mean square error and sum-rate performance in the mmWave vehicular system.

Keywords： 大规模多入多出；毫米波；信道估计；车辆通信；时变    

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Compressed sensing-based structured joint channel estimation in a multi-user massive MIMO system Article

Ruo-yu ZHANG, Hong-lin ZHAO, Shao-bo JIA

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 12,   Pages 2082-2100 doi: 10.1631/FITEE.1601635

Abstract: Acquisition of accurate channel state information (CSI) at transmitters results in a huge pilot overhead in massive multiple input multiple output (MIMO) systems due to the large number of antennas in the base station (BS). To reduce the overwhelming pilot overhead in such systems, a structured joint channel estimation scheme employing compressed sensing (CS) theory is proposed. Specifically, the channel sparsity in the angular domain due to the practical scattering environment is analyzed, where common sparsity and individual sparsity structures among geographically neighboring users exist in multi-user massive MIMO systems. Then, by equipping each user with multiple antennas, the pilot overhead can be alleviated in the framework of CS and the channel estimation quality can be improved. Moreover, a structured joint matching pursuit (SJMP) algorithm at the BS is proposed to jointly estimate the channel of users with reduced pilot overhead. Furthermore, the probability upper bound of common support recovery and the upper bound of channel estimation quality using the proposed SJMP algorithm are derived. Simulation results demonstrate that the proposed SJMP algorithm can achieve a higher system performance than those of existing algorithms in terms of pilot overhead and achievable rate.

Keywords： Compressed sensing     Multi-user massive multiple input multiple output (MIMO)     Frequency-division duplexing     Structured joint channel estimation     Pilot overhead reduction    

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On detecting primary user emulation attack using channel impulse response in the cognitive radio network Article

Qiao-mu JIANG, Hui-fang CHEN, Lei XIE, Kuang WANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1665-1676 doi: 10.1631/FITEE.1700203

Abstract: Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service (DoS) attack, named the ‘primary user emulation attack (PUEA)’, exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response (CIR) between the secondary user (SU) and the signal source is used to determine whether the received signal is transmitted by the primary user (PU) or the primary user emulator (PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.

Keywords： Cognitive radio network     Primary user emulation attack     Subspace-based blind channel estimation     Channel impulse response    

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Joint DOA and channel estimation with data detection based on 2D unitary ESPRITin massive MIMO systems Article

Jing-ming KUANG, Yuan ZHOU, Ze-song FEI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 6,   Pages 841-849 doi: 10.1631/FITEE.1700025

Abstract: We propose a novel method for joint two-dimensional (2D) direction-of-arrival (DOA) and channel estimation with data detection for uniform rectangular arrays (URAs) for the massive multiple-input multiple-output (MIMO) systems. The conventional DOA estimation algorithms usually assume that the channel impulse responses are known exactly. However, the large number of antennas in a massive MIMO system can lead to a challenge in estimating accurate corresponding channel impulse responses. In contrast, a joint DOA and channel estimation scheme is proposed, which first estimates the channel impulse responses for the links between the transmitters and antenna elements using training sequences. After that, the DOAs of the waves are estimated based on a unitary ESPRIT algorithm using previous channel impulse response estimates instead of accurate channel impulse responses and then, the enhanced channel impulse response estimates can be obtained. The proposed estimator enjoys closedform expressions, and thus it bypasses the search and pairing processes. In addition, a low-complexity approach toward data detection is presented by reducing the dimension of the inversion matrix in massive MIMO systems. Different cases for the proposed method are analyzed by changing the number of antennas. Experimental results demonstrate the validity of the proposed method.

Keywords： Two-dimensional (2D) direction-of-arrival (DOA) estimation     Channel impulse response estimation     Data detection     Uniform rectangular array (URA)     Massive multiple-input multiple-output (MIMO)    

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Gaze Estimation via a Differential Eyes’ Appearances Network with a Reference Grid Article

Song Gu, Lihui Wang, Long He, Xianding He, Jian Wang

Engineering 2021, Volume 7, Issue 6,   Pages 777-786 doi: 10.1016/j.eng.2020.08.027

Abstract:

A person’s eye gaze can effectively express that person’s intentions. Thus, gaze estimation is an important approach in intelligent manufacturing to analyze a person’s intentions. Many gaze estimation methods regress the direction of the gaze by analyzing images of the eyes, also known as eye patches. However, it is very difficult to construct a person-independent model that can estimate an accurate gaze direction for every person due to individual differences. In this paper, we hypothesize that the difference in the appearance of each of a person’s eyes is related to the difference in the corresponding gaze directions. Based on this hypothesis, a differential eyes’ appearances network (DEANet) is trained on public datasets to predict the gaze differences of pairwise eye patches belonging to the same individual. Our proposed DEANet is based on a Siamese neural network (SNNet) framework which has two identical branches. A multi-stream architecture is fed into each branch of the SNNet. Both branches of the DEANet that share the same weights extract the features of the patches; then the features are concatenated to obtain the difference of the gaze directions. Once the differential gaze model is trained, a new person’s gaze direction can be estimated when a few calibrated eye patches for that person are provided. Because personspecific calibrated eye patches are involved in the testing stage, the estimation accuracy is improved. Furthermore, the problem of requiring a large amount of data when training a person-specific model is effectively avoided. A reference grid strategy is also proposed in order to select a few references as some of the DEANet’s inputs directly based on the estimation values, further thereby improving the estimation accuracy. Experiments on public datasets show that our proposed approach outperforms the state-of-theart methods.

Keywords： Gaze estimation     Differential gaze     Siamese neural network     Cross-person evaluations     Human–robot collaboration    

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Non-ideal space division multiple access and its application None

Ji-ying XIANG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 3,   Pages 357-366 doi: 10.1631/FITEE.1700827

Abstract: We study the performance of space division multiple access (SDMA) under a non-ideal engineering situation. When the SDMA channel is of high inter-layer correlation and the condition number is large, the multiple user multiple input and multiple output user equipment (MUMIMOUE) grouping should be optimized, and in some cases further dimension-reduction should be applied. As the channel measuring is always non-ideal, we use two methods, feedback mode and non-feedback mode, in terms of performance and overhead. It is proposed that the non-feedback mode is preferable even for some non-reciprocal channels. Principle analysis and test results are given.

Keywords： Fifth generation (5G)     Condition number     Channel reciprocity     Feedback mode     Non-feedback mode    

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An Estimate Method of Parametric in Reliability Engineering

Han Ming

Strategic Study of CAE 2003, Volume 5, Issue 3,   Pages 51-56

Abstract:

In this paper, the Bayesian method, an estimate method for parameter in reliability engineering is put forward. The author gives definition of the new Bayesian estimate for failure probability and failure rate, and shows the estimate of the failure probability and the failure rate by new Bayesian method. Finally, calculations are performed regarding to practical problems, which show that the new Bayesian method is feasible, easy to operate, and convenient to use for engineers and technicians in fieldwork.

Keywords： reliability engineering     parameter estimate     new Bayesian estimate     failure probability    

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Ergodic secrecy capacity ofMRC/SC in single-inputmultiple-output wiretap systems with imperfect channel state information Article

Hui ZHAO, You-yu TAN, Gao-feng PAN, Yun-fei CHEN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4,   Pages 578-590 doi: 10.1631/FITEE.1500430

Abstract: This paper investigates the secrecy performance of maximal ratio combining (MRC) and selection combining (SC) with imperfect channel state information (CSI) in the physical layer. In a single-input multipleoutput (SIMO) wiretap channel, a source transmits confidential messages to the destination equipped with antennas using the MRC/SC scheme to process the received multiple signals. An eavesdropper equipped with antennas also adopts the MRC/SC scheme to promote successful eavesdropping. We derive the exact and asymptotic closed-form expressions for the ergodic secrecy capacity (ESC) in two cases: (1) MRC with weighting errors, and (2) SC with outdated CSI. Moreover, two important indicators, namely high signal-to-noise ratio (SNR) slope and high SNR power offset, which govern ESC at the high SNR region, are derived. Finally, simulations are conducted to validate the accuracy of our proposed analytical models. Results indicate that ESC rises with the increase of the number of antennas and the received SNR at the destination, and fades with the increase of those at the eavesdropper. Another finding is that the high SNR slope is constant, while the high SNR power offset is correlated with the number of antennas at both the destination and the eavesdropper.

Keywords： Ergodic secrecy capacity (ESC)     Maximal ratio combining (MRC)     Weighting errors     Physical layer security     Selection combining (SC)     Single-input multiple-output (SIMO)    

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Cooperative channel assignment for VANETs based on multiagent reinforcement learning Research Articles

Yun-peng Wang, Kun-xian Zheng, Da-xin Tian, Xu-ting Duan, Jian-shan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 1047-1058 doi: 10.1631/FITEE.1900308

Abstract: (DCA) plays a key role in extending vehicular ad-hoc network capacity and mitigating congestion. However, channel assignment under vehicular direct communication scenarios faces mutual influence of large-scale nodes, the lack of centralized coordination, unknown global state information, and other challenges. To solve this problem, a multiagent (RL) based cooperative DCA (RL-CDCA) mechanism is proposed. Specifically, each vehicular node can successfully learn the proper strategies of channel selection and backoff adaptation from the real-time channel state information (CSI) using two cooperative RL models. In addition, neural networks are constructed as nonlinear Q-function approximators, which facilitates the mapping of the continuously sensed input to the mixed policy output. Nodes are driven to locally share and incorporate their individual rewards such that they can optimize their policies in a distributed collaborative manner. Simulation results show that the proposed multiagent RL-CDCA can better reduce the one-hop packet delay by no less than 73.73%, improve the packet delivery ratio by no less than 12.66% on average in a highly dense situation, and improve the fairness of the global network resource allocation.

Keywords： Vehicular ad-hoc networks     Reinforcement learning     Dynamic channel assignment     Multichannel    

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A data-driven method for estimating the target position of low-frequency sound sources in shallow seas Research Articles

Xianbin Sun, Xinming Jia, Yi Zheng, Zhen Wang,robin_sun@qut.edu.cn,jiaxinming_123@163.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 7,   Pages 1020-1030 doi: 10.1631/FITEE.2000181

Abstract: Estimating the target position of low-frequency sound sources in a environment is difficult due to the high cost of hydrophone placement and the complexity of the propagation model. We propose a compressed (C-RNN) model that compresses the signal received by a into a dynamic sound intensity signal and compresses the target position of the sound source into a GeoHash code. Two types of data are used to carry out prior training on the , and the trained network is subsequently used to estimate the target position of the sound source. Compared with traditional mathematical models, the C-RNN model functions independently under the complex sound field environment and terrain conditions, and allows for real-time positioning of the sound source under low-parameter operating conditions. Experimental results show that the average error of the model is 56 m for estimating the target position of a low-frequency sound source in a environment.

Keywords： 矢量水听器；浅海；低频；位置估计；循环神经网络    

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A study of uplink and downlink channel spatial characteristics in an urban micro scenario at 28 GHz

Tao Jiang, Jianhua Zhang, Pan Tang, Lei Tian,jet@bupt.edu.cn,jhzhang@bupt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 4,   Pages 488-502 doi: 10.1631/FITEE.2000443

Abstract: This paper presents an empirical study of the and (AoA) in an urban micro (UMi) scenario at 28 GHz. At present, most UMi measurements are conducted in the and then the situation is inferred assuming channel reciprocity. Although the channel correlation coefficient of the and can be as high as 0.8, this does not mean that they are the same. Only a real measurement can accurately describe its channel conditions, and this is what this study does. A receiver equipped with a rotatable horn antenna is mounted at the base station and the user terminal, respectively, in simulating the and . To improve the angular resolution, we extract the multipath components (MPCs) using the space-alternating generalized expectation-maximization algorithm. Also, a spatial lobe approach is used to cluster the MPCs in the power angular spectrum. By matching MPCs with objects in the environment, we find that direct propagation and first-order reflections are dominant in line-of-sight and non-line-of-sight cases. By comparing our measurement with those in standard channel models, we verify that the AoA of clusters follows a Gaussian distribution in the and . In addition, a two-dimensional Gaussian distribution for ray AoA and power is established to reflect their correlation.

Keywords： 信道测量；毫米波；上行链路；下行链路；水平到达角    

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Channelmeasurements and models for 6G: current status and future outlook Review Articles

Jian-hua ZHANG, Pan TANG, Li YU, Tao JIANG, Lei TIAN

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 1,   Pages 39-61 doi: 10.1631/FITEE.1900450

Abstract: With the commercialization of fifth generation networks worldwide, research into sixth generation (6G) networks has been launched to meet the demands for high data rates and low latency for future services. A wireless propagation channel is the transmission medium to transfer information between the transmitter and the receiver. Moreover, channel properties determine the ultimate performance limit of wireless communication systems. Thus, conducting channel research is a prerequisite to designing 6G wireless communication systems. In this paper, we first introduce several emerging technologies and applications for 6G, such as terahertz communication, industrial Internet of Things, space-air-ground integrated network, and machine learning, and point out the developing trends of 6G channel models. Then, we give a review of channel measurements and models for the technologies and applications. Finally, the outlook for 6G channel measurements and models is discussed.

Keywords： Channel measurements     Channel models     Sixth generation     Terahertz     Industrial Internet of Things     Space-air-ground integrated network     Machine learning    

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Spatial fading channel emulation for over-the-air testing of millimeter-wave radios: concepts and experimental validations

Wei Fan, Lassi Hentilä, Pekka Kyösti,wfa@es.aau.dk

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 4,   Pages 548-559 doi: 10.1631/FITEE.2000484

Abstract: Millimeter-wave (mmWave) communication is regarded as the key enabling component for fifth-generation (5G) cellular systems due to the large available spectrum bandwidth. To make mmWave new radio (NR) a reality, tremendous efforts have been exerted from the industry and academia. Performance evaluation of mmWave NR is a mandatory step and the key to ensuring the success of mmWave 5G deployment. Over-the-air (OTA) radiated method of testing mmWave NR in laboratory conditions is highly attractive, since it facilitates virtual field testing of mmWave devices in realistic propagation conditions. In this paper, we first discuss the need for and challenges in OTA measurement of mmWave 5G NR under fading channel conditions. After that, two promising candidate solutions, i.e., wireless cable and multi-probe anechoic chamber (MPAC), are detailed. Their principles, applicability for mmWave NR, and main challenges are discussed. Furthermore, preliminary experimental validation results in a frequency range 2 anechoic chamber are demonstrated for the wireless cable and MPAC methods at 28 GHz.

Keywords： 空间信道模型；空口测试；无线线缆；多探头电波暗室；FR2验证    

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Co-Estimation of State of Charge and Capacity for Lithium-Ion Batteries with Multi-Stage Model Fusion Method Article

Rui Xiong, Ju Wang, Weixiang Shen, Jinpeng Tian, Hao Mu

Engineering 2021, Volume 7, Issue 10,   Pages 1471-1484 doi: 10.1016/j.eng.2020.10.022

Abstract:

Lithium-ion batteries (LIBs) have emerged as the preferred energy storage systems for various types of electric transports, including electric vehicles, electric boats, electric trains, and electric airplanes. The energy management of LIBs in electric transports for all-climate and long-life operation requires the accurate estimation of state of charge (SOC) and capacity in real-time. This study proposes a multistage
model fusion algorithm to co-estimate SOC and capacity. Firstly, based on the assumption of a normal distribution, the mean and variance of the residual error from the model at different ageing levels are used to calculate the weight for the establishment of a fusion model with stable parameters. Secondly, a differential error gain with forward-looking ability is introduced into a proportional–integral observer
(PIO) to accelerate convergence speed. Thirdly, a fusion algorithm is developed by combining a multistage model and proportional–integral–differential observer (PIDO) to co-estimate SOC and capacity under a complex application environment. Fourthly, the convergence and anti-noise performance of the fusion algorithm are discussed. Finally, the hardware-in-the-loop platform is set up to verify the performance
of the fusion algorithm. The validation results of different aged LIBs over a wide range of temperature show that the presented fusion algorithm can realize a high-accuracy estimation of SOC and capacity with the relative errors within 2% and 3.3%, respectively.

Keywords： State of charge     Capacity estimation     Model fusion     Proportional–integral–differential observer     Hardware-in-the-loop    

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Title Author Date Type Operation

Improving the Performance of OFDM Channel Estimation through Subspace Projecting and Tracking

Dong Liang,Cao Xiuying,Bi Guangguo

Journal Article

Prior information based channel estimation for millimeter-wave massive MIMO vehicular communications in 5G and beyond

Zhao Yi, Weixia Zou, Xuebin Sun,yz17tx@bupt.edu.cn,zwx0218@bupt.edu.cn

Journal Article

Compressed sensing-based structured joint channel estimation in a multi-user massive MIMO system

Ruo-yu ZHANG, Hong-lin ZHAO, Shao-bo JIA

Journal Article

On detecting primary user emulation attack using channel impulse response in the cognitive radio network

Qiao-mu JIANG, Hui-fang CHEN, Lei XIE, Kuang WANG

Journal Article

Joint DOA and channel estimation with data detection based on 2D unitary ESPRITin massive MIMO systems

Jing-ming KUANG, Yuan ZHOU, Ze-song FEI

Journal Article

Gaze Estimation via a Differential Eyes’ Appearances Network with a Reference Grid

Song Gu, Lihui Wang, Long He, Xianding He, Jian Wang

Journal Article

Non-ideal space division multiple access and its application

Ji-ying XIANG

Journal Article

An Estimate Method of Parametric in Reliability Engineering

Han Ming

Journal Article

Ergodic secrecy capacity ofMRC/SC in single-inputmultiple-output wiretap systems with imperfect channel state information

Hui ZHAO, You-yu TAN, Gao-feng PAN, Yun-fei CHEN

Journal Article

Cooperative channel assignment for VANETs based on multiagent reinforcement learning

Yun-peng Wang, Kun-xian Zheng, Da-xin Tian, Xu-ting Duan, Jian-shan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn

Journal Article

A data-driven method for estimating the target position of low-frequency sound sources in shallow seas

Xianbin Sun, Xinming Jia, Yi Zheng, Zhen Wang,robin_sun@qut.edu.cn,jiaxinming_123@163.com

Journal Article

A study of uplink and downlink channel spatial characteristics in an urban micro scenario at 28 GHz

Tao Jiang, Jianhua Zhang, Pan Tang, Lei Tian,jet@bupt.edu.cn,jhzhang@bupt.edu.cn

Journal Article

Channelmeasurements and models for 6G: current status and future outlook

Jian-hua ZHANG, Pan TANG, Li YU, Tao JIANG, Lei TIAN

Journal Article

Spatial fading channel emulation for over-the-air testing of millimeter-wave radios: concepts and experimental validations

Wei Fan, Lassi Hentilä, Pekka Kyösti,wfa@es.aau.dk

Journal Article

Co-Estimation of State of Charge and Capacity for Lithium-Ion Batteries with Multi-Stage Model Fusion Method

Rui Xiong, Ju Wang, Weixiang Shen, Jinpeng Tian, Hao Mu

Journal Article