Space-Frequency-Interpolated Radio Map

This paper presents a novel method for radio map construction that simultaneously interpolates the received signal power values over space and frequency domains. Radio maps can be used to improve spectrum management and for localization systems, which are related to wireless systems in general such as cellular systems, Internet of Things (IoT) networks, and vehicular communications. Researchers have shown that crowdsourcing using spatial interpolation techniques can be used to accurately construct a radio map to improve these applications; however, because of the limitation in the spatial domain, conventional methods can build a radio map for only those frequencies at which sensing can be performed. Our proposed method focuses on the fact that the shadowing values show strong correlation over a wide range of frequency domains. The main idea is to treat the shadowing values obtained over various frequencies as the ones over target frequency. Using the actual datasets obtained over 870, 2115, and 3500 MHz in a cellular system, we show that the proposed method can accurately generate a radio map, even if no (or few) datasets are available in the target frequency.

[1]  K. Siakavara,et al.  Application of a Composite Differential Evolution Algorithm in Optimal Neural Network Design for Propagation Path-Loss Prediction in Mobile Communication Systems , 2013, IEEE Antennas and Wireless Propagation Letters.

[2]  Takeo Fujii,et al.  Modeling the Kriging-Aided Spatial Spectrum Sharing Over Log-Normal Channels , 2019, IEEE Wireless Communications Letters.

[3]  Yongtao Ma,et al.  A Probabilistic Radio Map Construction Scheme for Crowdsourcing-Based Fingerprinting Localization , 2016, IEEE Sensors Journal.

[4]  Ainslie,et al.  CORRELATION MODEL FOR SHADOW FADING IN MOBILE RADIO SYSTEMS , 2004 .

[5]  Andreas Achtzehn,et al.  Improving accuracy for TVWS geolocation databases: Results from measurement-driven estimation approaches , 2014, 2014 IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN).

[6]  Takeo Fujii,et al.  Frequency correlation of shadowing over TV bands in suburban area , 2018 .

[7]  Ye Tao,et al.  A Novel System for WiFi Radio Map Automatic Adaptation and Indoor Positioning , 2018, IEEE Transactions on Vehicular Technology.

[8]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[9]  Fredrik Tufvesson,et al.  Path Loss Modeling for Vehicle-to-Vehicle Communications , 2011, IEEE Transactions on Vehicular Technology.

[10]  D. C. Cox,et al.  Shadow fading correlation between uplink and downlink , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[11]  Jie Xu,et al.  Radio-Map-Based Robust Positioning Optimization for UAV-Enabled Wireless Power Transfer , 2019, IEEE Wireless Communications Letters.

[12]  Lei Xue,et al.  A Two-Phase Transfer Learning-Based Power Spectrum Maps Reconstruction Algorithm for Underlay Cognitive Radio Networks , 2020, IEEE Access.

[13]  Jordi Pérez-Romero,et al.  On the use of radio environment maps for interference management in heterogeneous networks , 2015, IEEE Communications Magazine.

[14]  Georgios B. Giannakis,et al.  Cooperative Spectrum Sensing for Cognitive Radios Using Kriged Kalman Filtering , 2009, IEEE Journal of Selected Topics in Signal Processing.

[15]  Dirk Grunwald,et al.  Bounding the error of path loss models , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[16]  Xiaoli Xu,et al.  Towards Environment-Aware 6G Communications via Channel Knowledge Map , 2020, ArXiv.

[17]  Carlos T. Calafate,et al.  Path Loss Predictions in the VHF and UHF Bands Within Urban Environments: Experimental Investigation of Empirical, Heuristics and Geospatial Models , 2019, IEEE Access.

[18]  Pradipta De,et al.  A Survey of Fingerprint-Based Outdoor Localization , 2016, IEEE Communications Surveys & Tutorials.

[19]  Hao Jiang,et al.  WinIPS: WiFi-Based Non-Intrusive Indoor Positioning System With Online Radio Map Construction and Adaptation , 2017, IEEE Transactions on Wireless Communications.

[20]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[21]  Andreas F. Molisch,et al.  Dual Frequency Bands Shadowing Correlation Model in a Micro-Cellular Environment , 2019, 2019 IEEE Global Communications Conference (GLOBECOM).

[22]  M. Hata,et al.  Empirical formula for propagation loss in land mobile radio services , 1980, IEEE Transactions on Vehicular Technology.

[23]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[24]  Nasir Faruk,et al.  Determination of Neural Network Parameters for Path Loss Prediction in Very High Frequency Wireless Channel , 2019, IEEE Access.

[25]  Zunwen He,et al.  Path Loss Prediction Based on Machine Learning Methods for Aircraft Cabin Environments , 2019, IEEE Access.

[26]  Jenq-Shiou Leu,et al.  Construction of an indoor radio environment map using gradient boosting decision tree , 2020, Wireless Networks.

[27]  Georgios B. Giannakis,et al.  Channel Gain Map Tracking via Distributed Kriging , 2011, IEEE Transactions on Vehicular Technology.

[28]  Masahiro Morikura,et al.  Transfer Learning-Based Received Power Prediction with Ray-tracing Simulation and Small Amount of Measurement Data , 2020, 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall).

[29]  Takeo Fujii,et al.  On the Performance of Neural Network Residual Kriging in Radio Environment Mapping , 2019, IEEE Access.

[30]  Robert Haining,et al.  Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95 , 1993 .

[31]  Dirk Grunwald,et al.  A Survey of Wireless Path Loss Prediction and Coverage Mapping Methods , 2013, IEEE Communications Surveys & Tutorials.

[32]  Bei Zhang,et al.  Shadow fading cross-correlation of multi-frequencies in curved subway tunnels , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[33]  P. D. Doncker,et al.  Correlation for multi-frequency propagation in urban environment , 2012 .

[34]  Francisco Cercas,et al.  Cloud-Based Implementation of an Automatic Coverage Estimation Methodology for Self-Organising Network , 2020, IEEE Access.

[35]  Yunlong Cai,et al.  Joint Resource Allocation and Trajectory Optimization for UAV-Aided Relay Networks , 2019, 2019 IEEE Global Communications Conference (GLOBECOM).

[36]  S. Tabbane,et al.  A UHF Path Loss Model Using Learning Machine for Heterogeneous Networks , 2017, IEEE Transactions on Antennas and Propagation.

[37]  Chenshu Wu,et al.  Automatic Radio Map Adaptation for Indoor Localization Using Smartphones , 2018, IEEE Transactions on Mobile Computing.

[38]  Takeo Fujii,et al.  Radio Environment Map Construction with Joint Space-Frequency Interpolation , 2020, 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC).

[39]  Bo Gao,et al.  An Overview of Dynamic Spectrum Sharing: Ongoing Initiatives, Challenges, and a Roadmap for Future Research , 2016, IEEE Transactions on Cognitive Communications and Networking.

[40]  Theodore S. Rappaport,et al.  Propagation Path Loss Models for 5G Urban Micro- and Macro-Cellular Scenarios , 2015, 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring).

[41]  Hans-Jürgen Zepernick,et al.  Macrocell Path-Loss Prediction Using Artificial Neural Networks , 2010, IEEE Transactions on Vehicular Technology.

[42]  Zhi Ding,et al.  Engineering Radio Maps for Wireless Resource Management , 2018, IEEE Wireless Communications.

[43]  Hamid Reza Karimi,et al.  Geolocation databases for white space devices in the UHF TV bands: Specification of maximum permitted emission levels , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[44]  Shahrokh Valaee,et al.  Joint Indoor Localization and Radio Map Construction with Limited Deployment Load , 2015, IEEE Transactions on Mobile Computing.

[45]  Zhongming Zheng,et al.  LTE-unlicensed: the future of spectrum aggregation for cellular networks , 2015, IEEE Wireless Communications.

[46]  Audra E. Kosh,et al.  Linear Algebra and its Applications , 1992 .

[47]  Takeo Fujii,et al.  Kriging-Based Interference Power Constraint: Integrated Design of the Radio Environment Map and Transmission Power , 2017, IEEE Transactions on Cognitive Communications and Networking.

[48]  Paramvir Bahl,et al.  SenseLess: A database-driven white spaces network , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[49]  Patrick Claus F. Eggers,et al.  Urban area radio propagation measurements at 955 and 1845 MHz for small and micro cells , 1991, IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record.