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| 1 | Convolutional Neural Networks Based Indoor Wi-Fi Localization with a Novel Kind of CSI Images显示文摘Indoor Wi-Fi localization of mobile devices plays a more and more important role along with the rapid growth of location-based services and Wi-Fi mobile devices.In this paper,a new method of constructing the channel state information(CSI)image is proposed to improve the localization accuracy.Compared with previous methods of constructing the CSI image,the new kind of CSI image proposed is able to contain more channel information such as the angle of arrival(AoA),the time of arrival(TOA)and the amplitude.We construct three gray images by using phase differences of different antennas and amplitudes of different subcarriers of one antenna,and then merge them to form one RGB image.The localization method has off-line stage and on-line stage.In the off-line stage,the composed three-channel RGB images at training locations are used to train a convolutional neural network(CNN)which has been proved to be efficient in image recognition.In the on-line stage,images at test locations are fed to the well-trained CNN model and the localization result is the weighted mean value with highest output values.The performance of the proposed method is verified with extensive experiments in the representative indoor environment. | Haihan Li Xiangsheng Zeng Yunzhou Li Shidong Zhou Jing Wang | 2019 | China Communications2019，16，9： | 7 |
| 2 | Wireless channel feature extraction via GMM and CNN in the tomographic channel model显示文摘Wireless channel modeling has always been one of the most fundamental highlights of the wireless communication research.The performance of new advanced models and technologies heavily depends on the accuracy of the wireless CSI(Channel State Information).This study examined the randomness of the wireless channel parameters based on the characteristics of the radio propagation environment.The diversity of the statistical properties of wireless channel parameters inspired us to introduce the concept of the tomographic channel model.With this model,the static part of the CSI can be extracted from the huge amount of existing CSI data of previous measurements,which can be de ned as the wireless channel feature.In the proposed scheme for obtaining CSI with the tomographic channel model,the GMM(Gaussian Mixture Model)is applied to acquire the distribution of the wireless channel parameters,and the CNN(Convolutional Neural Network)is applied to automatically distinguish di erent wireless channels.The wireless channel feature information can be stored oine to guide the design of pilot symbols and save pilot resources.The numerical results based on actual measurements demonstrated the clear diversity of the statistical properties of wireless channel parameters and that the proposed scheme can extract the wireless channel feature automatically with fewer pilot resources.Thus,computing and storage resources can be exchanged for the nite and precious spectrum resource. | Haihan Li Yunzhou Li Shidong Zhou Jing Wang | 2017 | Journal of Communications and Information Networks2017，2，1： | 6 |
| 3 | A Learning-Based Channel Model for Synergetic Transmission Technology显示文摘It is extensively approved that Channel State Information(CSI) plays an important role for synergetic transmission and interference management. However, pilot overhead to obtain CSI with enough precision is a significant issue for wireless communication networks with massive antennas and ultra-dense cell. This paper proposes a learning- based channel model, which can estimate, refine, and manage CSI for a synergetic transmission system. It decomposes the channel impulse response into multiple paths, and uses a learning-based algorithm to estimate paths' parameters without notable degradation caused by sparse pilots. Both indoor measurement and outdoor measurement are conducted to verify the feasibility of the proposed channel model preliminarily. | Liang Chen Li Haihan Li Yunzhou Zhou Shidong Wang Jing | 2015 | China Communications2015，12，9： | 4 |
| 4 | Capacitive Performances of Reduced Graphene Oxide Hydrogel Prepared by Using Sodium Hypophosphite as Reducer显示文摘减少的 graphene 氧化物(rGOHGs ) 的 hydrogels 通过对待被综合了与钠次磷酸盐的各种各样的集中相配(不 2 在热水的状况下面的 PO 2) 。结果表明 rGOHGs 的结构与集中的增加一起变化不 2 PO 2 。与低集中准备的 rGO 表不 2 PO 2 展览更多成波形并且更大的特定的表面区域比与高集中准备的那些不 2 PO 2 。rGOHGs 的电容的表演的大小表明 rGOHGs 与低集中准备了不 2 PO 2 拥有更大的特定的电容(C s ) 与高集中比那准备了不 2 在低周期的 voltammetry 扫描的 PO 2 评价。然而, rGOHGs 与高集中准备了不 2 PO 2 拥有更大的 C 以比那些的高扫描率,更多的稳定性和更好高率的能力的 s 在低集中准备了。rGOHGs 的结构和性质能被控制集中调整,这被相信不 2 PO 2 根据要求。 | Cuixian Liu Gaoyi Han Yunzhen Chang Yaoming Xiao Yanping Li Miaoyu Li Haihan Zhou | 2016 | Chinese Journal of Chemistry2016，34，1： | 2 |
| 5 | Static CSI Extraction and Application in the Tomographic Channel Model显示文摘In this paper, the statistical properties of parameters of each path in wireless channel models are analyzed to prove that there is the static part in channel state information(CSI) which can be extracted from huge amounts of CSI data. Based on the analysis, the concept of the Tomographic Channel Model(TCM) is presented. With cluster algorithms, the static CSI database can be built in an off-line manner. The static CSI database can provide prior information to help pilot design to reduce overhead and improve accuracy in channel estimation. A new CSI prediction method and a new channel estimation method between different frequency bands are introduced based on the static CSI database. Using measurement data, the performance of the new channel prediction method is compared with that of the Auto Regression(AR) predictor. The results indicate that the prediction range of the new method is better than that of the AR method and the new method can predict with fewer pilot symbols. Using measurement data, the new channel estimation method between different frequency bands can estimate the CSI of one frequency band based on known CSI of another frequency band without any feedback. | Haihan Li Yunzhou Li Shidong Zhou Jing Wang | 2019 | China Communications2019，16，12： | 1 |
| 6 | Platinum Wire Implants Coated with PEDOT/Carbon Nanotube Conducting Polymer Films in the Brain of Rats: A Histological Evaluation显示文摘Platinum (Pt) implants coated with poly (3, 4-ethylenedioxythiophene)/carbon nanotube (PEDOT/CNT) composite films were implanted into the brain of rats, and the brain response was evaluated 6 weeks after the implantation. The surface morphology of Pt implants with and without the PEDOT/CNT coating was studied using scanning electron microscopy (SEM). After 6 weeks post-implantation, the expression of laminin (vascular endothelial marker) and neuronal nuclei (NeuN, neuronal marker) were evaluated by immnohistochemistry. It is revealed that the obvious improvements of the surface density of blood vessels and neurons aound the Pt implants with the coating, which were evidenced by laminin and NeuN staining in the zone within the distance of 150 μm to the implant interface. These results suggest the PEDOT/CNT composite films can improve the biocompatibility of the Pt electrodes while it is implanted in brain. | 程璇 LI Chengyan RAO Li ZHOU Haihan 李涛 段晏文 | 2012 | Journal of Wuhan University of Technology(Materials Science)2012，27，6： | 0 |
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