과제정보
This research was supported by National Natural Science Foundation of China (61871261) and the Natural Science Foundation of Shanghai (22ZR1422200).
참고문헌
- J. Li, Y. Zhao, J. Zhang, R. Jiang, C. Tao, and Z. Tan, Radio channel measurements and analysis at 2.4/5GHz in subway tunnels, China Commun. 12 (2015), no. 1, 36-45. https://doi.org/10.1109/CC.2015.7084382
- Y. Wu, G. Zheng, A. Saleem, and Y. P. Zhang, An experimental study of MIMO performance using leaky coaxial cables in a tunnel, IEEE Ant. Propag. Lett. 16 (2017), 1663-1666. https://doi.org/10.1109/LAWP.2017.2662209
- B. Ai, K. Guan, Z. Zhong, C. F. Lopez, L. Zhang, C. BrisoRodriguez, and R. He, Measurement and analysis of extra propagation loss of tunnel curve, IEEE Trans. Veh. Technol. 65 (2016), no. 4, 1847-1858. https://doi.org/10.1109/TVT.2015.2425218
- Y. P. Zhang, Novel model for propagation loss prediction in tunnels, IEEE Trans. Veh. Technol. 52 (2003), no. 5, 1308-1314. https://doi.org/10.1109/TVT.2003.816647
- D. Dudley, M. Lienard, S. Mahmoud, and P. Degauque, Wireless propagation in tunnels, IEEE Ant. Propag. Mag. 49 (2007), no. 2, 11-26.
- S. Loyka, Multiantenna capacities of waveguide and cavity channels, IEEE Trans. Veh. Technol. 54 (2005), no. 3, 863-872. https://doi.org/10.1109/TVT.2005.844640
- P. V. Nikitin, D. D. Stancil, and E. A. Erosheva, Estimating the number of modes in multimode waveguide propagation environment, (IEEE International Symposium on Antennas and Propagation, Spokane, WA, USA), Aug. 2011, pp. 1662-1665.
- A. Hrovat, G. Kandus, and T. Javornik, A survey of radio propagation modeling for tunnels, IEEE Commun. Surv. Tutor. 16 (2014), no. 2, 658-669. https://doi.org/10.1109/SURV.2013.091213.00175
- Y. Wang, S. Safavi-Naeini, and S. K. Chaudhuri, A hybrid technique based on combining ray tracing and FDTD methods for site-specific modeling of indoor radio wave propagation, IEEE Trans. Ant. Propag. 48 (2000), no. 5, 743-754. https://doi.org/10.1109/8.855493
- A. Fourie and D. Nitch, SuperNEC: Antenna and indoorpropagation simulation program, IEEE Ant. Propag. Mag. 42 (2000), no. 3, 31-48. https://doi.org/10.1109/74.848946
- R. Martelly and R. Janaswamy, Modeling radio transmission loss in curved, branched and rough-walled tunnels with the ADI-PE method, IEEE Trans. Ant. Propag. 58 (2010), no. 6, 2037-2045. https://doi.org/10.1109/TAP.2010.2046862
- M. Jia, G. Zheng, and W. Ji, A new model for predicting the characteristic of RF propagation in rectangular tunnel, (International Conference on Wireless Communications, Networking and Mobile Computing. (Dalian, China), Oct. 2008, pp. 1-4.
- S. H. Chen and S. K. Jeng, SBR image approach for radio wave propagation in tunnels with and without traffic, IEEE Trans. Veh. Technol. 45 (1996), no. 3, 570-578. https://doi.org/10.1109/25.533772
- F. M. Pallares, F. J. P. Juan, and L. Juan-Llacer, Analysis of path loss and delay spread at 900 MHz and 2.1 GHz while entering tunnels, IEEE Trans. Veh. Technol. 50 (2001), no. 3, 767-776. https://doi.org/10.1109/25.933311
- M. H. Kermani, and M. Kamarei, A ray-tracing method for predicting delay spread in tunnel environments, (IEEE International Conference on Personal Wireless Communications Conference Proceedings, Hyderabad, India), Aug. 2000, pp. 538-542.
- E. Masson, P. Combeau, M. Berbineau, and R. Vauzelle, Measurements and simulations comparisons of radio wave propagation in arch-shaped tunnels for mass transit applications, (9th International Conference on Intelligent Transport Systems Telecommunications(Lille, France), Oct. 2009, pp. 37-41.
- E. Ostlin, H. Zepernick, and H. Suzuki, Macrocell path-loss prediction using artificial neural networks, IEEE Trans. Veh. Technol. 59 (2010), no. 6, 2735-2747. https://doi.org/10.1109/TVT.2010.2050502
- L. Azpilicueta, M. Rawat, K. Rawat, F. M. Ghannouchi, and F. Falcone, A ray launching-neural network approach for radio wave propagation analysis in complex indoor environments, IEEE Trans. Ant. Propag. 62 (2014), no. 5, 2777-2786. https://doi.org/10.1109/TAP.2014.2308518
- A. Neskovic, N. Neskovic, and D. Paunovic, Indoor electric field level prediction model based on the artificial neural networks, IEEE Commun. Lett. 4 (2000), no. 6, 190-192. https://doi.org/10.1109/4234.848409
- G. P. Ferreira, L. J. Matos, and J. M. M. Silva, Improvement of outdoor signal strength prediction in UHF band by artificial neural network, IEEE Trans. Ant. Propag. 64 (2016), no. 12, 5404-5410. https://doi.org/10.1109/TAP.2016.2617379
- S. I. Popoola, A. Jefia, A. A. Atayero, O. Kingsley, N. Faruk, O. F. Oseni, and R. O. Abolade, Determination of neural network parameters for path loss prediction in very high frequency wireless channel, IEEE Access 7 (2019), 150462-150483. https://doi.org/10.1109/ACCESS.2019.2947009
- J. Liu, X. Jin, F. Dong, L. He, and H. Liu, Fading channel modelling using single-hidden layer feedforward neural networks, Multidim. Syst. Signal Process. 28 (2017), 885-903. https://doi.org/10.1007/s11045-015-0380-1
- J. O. Eichie, O. D. Oyedum, M. O. Ajewole, and A. M. Aibinu, Comparative analysis of basic models and artificial neural network based model for path loss prediction, Pier m 61 (2017), 133-146. https://doi.org/10.2528/PIERM17060601
- A. Malone, and C. D. Sarris, "Electromagnetic vision": Machine intelligence models of radiowave propagation in tunnels, (IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, Boston, MA, USA), July 2018, pp. 557-558.
- X. Zhao, F. Du, S. Geng, N. Sun, Y. Zhang, Z. Fu, and G. Wang, Neural network and GBSM based time-varying and stochastic channel modeling for 5G millimeter wave communications, China Commun. 16 (2019), no. 6, 80-90. https://doi.org/10.23919/JCC.2019.06.007
- N. Sun, S. Geng, S. Li, X. Zhao, M. Wang, and S. Sun, Channel modeling by RBF neural networks for 5G Mm-wave communication, (IEEE/CIC International Conference on Communications in China, Beijing, China), Aug. 2018, pp. 768-772.
- L. Bai, C. X. Wang, J. Huang, Q. Xu, Y. Yang, G. Goussetis, J. Sun, and W. Zhang, Predicting wireless mmWave massive MIMO channel characteristics using machine learning algorithms, Wireless Commun. Mobile Comput. 2018 (2018), 9783863.
- J. Huang, C. X. Wang, L. Bai, J. Sun, Y. Yang, J. Li, O. Tirkkonen, and M. T. Zhou, A big data enabled channel model for 5G wireless communication systems, IEEE Trans. Big Data 6 (2020), no. 2, 211-222. https://doi.org/10.1109/TBDATA.2018.2884489
- P. Petrus, J. H. Reed, and T. S. Rappaport, Geometrical-based statistical macrocell channel model for mobile environments, IEEE Trans. Commun. 50 (2002), no. 3, 495-502. https://doi.org/10.1109/26.990911
- R. B. Ertel and J. H. Reed, Angle and time of arrival statistics for circular and elliptical scattering models, IEEE J. Sel. Areas Commun. 17 (1999), no. 11, 1829-1840. https://doi.org/10.1109/49.806814
- G. D. Kondylis, F. De Flaviis, G. J. Pottie, and Y. RahmatSamii, Indoor channel characterization for wireless communications using reduced finite difference time domain (R-FDTD), (IEEE VTS 50th Vehicular Technology Conference, Amsterdam, Netherlands), Sept. 1999, pp. 1402-1406.
- M. M. Rana and A. S. Mohan, Segmented-locally-one-dimensional-FDTD method for EM propagation inside large complex tunnel environments, IEEE Trans. Magn. 48 (2012), no. 2, 223-226. https://doi.org/10.1109/TMAG.2011.2177075
- F. Fuschini and G. Falciasecca, A mixed rays-Modes approach to the propagation in real road and railway tunnels, IEEE Trans. Ant. Propag. 60 (2012), no. 2, 1095-1105. https://doi.org/10.1109/TAP.2011.2173137
- C. Briso-Rodriguez, J. M. Cruz, and J. I. Alonso, Measurements and modeling of distributed antenna systems in railway tunnels, IEEE Trans. Veh. Technol. 56 (2007), no. 5, 2870-2879. https://doi.org/10.1109/TVT.2007.900500
- S. Wang, H. Zhao, G. Zheng, F. Zhang, A. Saleem, K. Zhang, and L. Cang, Ultra-high mobility analysis of MIMO wireless system in tunnel scenarios, IEEE Commun. Lett. 26 (2021), no. 3, 687-691.
- T. Zhou, H. Li, R. Sun, Y. Wang, L. Liu, and C. Tao, Simulation and analysis of propagation characteristics for tunnel trainground communications at 1.4 and 40 GHz, IEEE Access 7 (2019), 105123-105131. https://doi.org/10.1109/ACCESS.2019.2932125
- D. He, B. Ai, K. Guan, Z. Zhong, B. Hui, J. Kim, H. Chung, and I. Kim, Channel measurement, simulation, and analysis for high-speed railway communications in 5G millimeter-wave band, IEEE Trans. Intell. Transp. Syst. 19 (2018), no. 10, 3144- 3158. https://doi.org/10.1109/TITS.2017.2771559
- I-R. P.2040, Effects of building materials and structures on radiowave propagation above about 100 MHz, International Telecommunication Union Radiocommunication Sector ITU-R P, 2015.
- S. Geng, J. Kivinen, X. Zhao, and P. Vainikainen, Millimeterwave propagation channel characterization for short-range wireless communications, IEEE Trans. Veh. Technol. 58 (2009), no. 1, 3-13. https://doi.org/10.1109/TVT.2008.924990
- S. D. Li, Y. J. Liu, L. K. Lin, Z. Sheng, X. C. Sun, Z. P. Chen, and X. J. Zhang, Channel measurements and modeling at 6 GHz in the tunnel environments for 5G wireless systems, Int. J. Ant. Propag. 2017 (2017), 15130380.
- C. Wang, W. Ji, G. Zheng, and A. Saleem, Analysis of propagation characteristics for various subway tunnel scenarios at 28 GHz, Int. J. Ant. Propag. 2021 (2021), 7666624.
- T. Guillod, P. Papamanolis, and J. W. Kolar, Artificial neural network (ANN) based fast and accurate inductor modeling and design, IEEE Open J. Power Electron. 1 (2020), 284-299. https://doi.org/10.1109/OJPEL.2020.3012777
- Z. Sun and I. F. Akyildiz, Channel modeling and analysis for wireless networks in underground mines and road tunnels, IEEE Trans. Commun. 58 (2010), no. 6, 1758-1768. https://doi.org/10.1109/TCOMM.2010.06.080353
- S. Bashir, Effect of antenna position and polarization on UWB propagation channel in underground mines and tunnels, IEEE Trans. Ant. Propag. 62 (2014), no. 9, 4771-4779. https://doi.org/10.1109/TAP.2014.2334352
- M. Zhai, K. Zhai, H. Cui, and D. Li, Multifrequency channel characterization for curved tunnels, IEEE Ant. Wireless Propag. Lett. 20 (2021), no. 12, 2457-2460. https://doi.org/10.1109/LAWP.2021.3114553
- C. Briso-Rodriguez, P. Fratilescu, and Y. Xu, Path loss modeling for train-to-train communications in subway tunnels at 900/2400 MHz, IEEE Ant. Wireless Propag. Lett. 18 (2019), no. 6, 1164-1168. https://doi.org/10.1109/LAWP.2019.2911406
- K. Guan, Z. Zhong, B. Ai, R. He, B. Chen, Y. Li, and C. Briso-Rodriguez, Complete propagation model in tunnels, IEEE Ant. Wireless Propag. Lett. 12 (2013), no. 2013, 741-744. https://doi.org/10.1109/LAWP.2013.2270937
- X. Zhang, N. Sood, and C. D. Sarris, Fast radio-wave propagation modeling in tunnels with a hybrid vector parabolic equation/waveguide mode theory method, IEEE Trans. Ant. Propag. 66 (2018), no. 12, 6540-6551. https://doi.org/10.1109/TAP.2018.2864344
- Z. Hu, W. Ji, H. Zhao, X. Zhai, A. Saleem, and G. Zheng, Channel measurement for multiple frequency bands in subway tunnel scenario, Int. J. Ant. Propag. 2021 (2021), 9991758.
- C. Garcia-Pardo, J. M. Molina-Garcia-Pardo, M. Lienard, D. P. Gaillot, and P. Degauque, Double directional channel measurements in an arched tunnel and interpretation using ray tracing in a rectangular tunnel, Pier m 22 (2012), no. 22, 91-107. https://doi.org/10.2528/PIERM11070110
- M. Yang, B. Ai, R. He, Z. Ma, Z. Zhong, J. Wang, L. Pei, Y. Li, J. Li, and N. Wang, Non-stationary vehicular channel characterization in complicated scenarios, IEEE Trans. Veh. Technol. 70 (2021), no. 9, 8387-8400. https://doi.org/10.1109/TVT.2021.3096973
- A. Saleem, H. Cui, Y. He, and A. Boag, Channel Propagation Characteristics for Massive Multiple-Input/Multiple-Output Systems in a Tunnel Environment [Measurements Corner]. IEEE Ant. Propag. Mag. 64 (2022), no. 3, 126-142. https://doi.org/10.1109/map.2022.3162807
- M. E. Morocho-Cayamcela, H. Lee and W. Lim, Machine Learning for 5G/B5G Mobile and Wireless Communications: Potential, Limitations, and Future Directions, IEEE Access. 7 (2019), 137184-137206. https://doi.org/10.1109/ACCESS.2019.2942390
- M. T. Hagan and M. B. Menhaj, Training feedforward networks with the Marquardt algorithm, IEEE Trans. Neural Netw. 5 (1997), no. 6, 989-993. https://doi.org/10.1109/90.650156
- G. Cerri, M. Cinalli, F. Michetti, and P. Russo, Feed forward neural networks for path loss prediction in urban environment, IEEE Trans. Ant. Propag. 52 (2004), no. 11, 3137-3139. https://doi.org/10.1109/TAP.2004.835252
- S. P. Sotiroudis, S. K. Goudos, K. A. Gotsis, K. Siakavara, and J. N. Sahalos, Application of a composite differential evolution algorithm in optimal neural network design for propagation path-loss prediction in mobile communication systems, IEEE Ant. Wireless Propag. Lett. 12 (2013), 364-367. https://doi.org/10.1109/LAWP.2013.2251994
- S. O. Ajose and A. I. Imoize, Propagation measurements and modelling at 1800 MHz in Lagos Nigeria, Int. J. Wireless Mobile Comput. 6 (2013), no. 2, 154-173.
- S. K. Jin, S. H. Jang, D. K. Shin, S. H. Yoon, and H. G. Jung, Performance analysis of WAVE communication for emergency broadcasting in metro environments, (Tenth International Conference on Ubiquitous and Future Networks (ICUFN). Prague, Czech Republic), July 2018, pp. 557-560.
- A. Saleem, and Y. He, Investigation of massive MIMO channel spatial characteristics for indoor subway tunnel environment, (Computing, Communications and IoT Applications, Shenzhen, China), Nov. 2021, pp. 162-167.
- R. Sun, Y. Lei, Z. Chen, and Z. Sun, Investigation of MIMO channel characteristics in tunnel at 1.4725 and 6 GHz, Radio Sci. 55 (2020), no. 10, 1-11.