A general altitude-dependent path loss model for UAV-to-ground millimeter-wave communications
Tóm tắt
A general empirical path loss (PL) model for air-to-ground (A2G) millimeter-wave (mmWave) channels is proposed in this paper. Different from existing PL models, the new model takes the height factor of unmanned aerial vehicles (UAVs) into account, and divides the propagation conditions into three cases (i.e., line-of-sight, reflection, and diffraction). A map-based deterministic PL prediction algorithm based on the ray-tracing (RT) technique is developed, and is used to generate numerous PL data for different cases. By fitting and analyzing the PL data under different scenarios and UAV heights, altitude-dependent model parameters are provided. Simulation results show that the proposed model can be effectively used to predict PL values for both low- and high-altitude cases. The prediction results of the proposed model better match the RT-based calculation results than those of the Third Generation Partnership Project (3GPP) model and the close-in model. The standard deviation of the PL is also much smaller. Moreover, the new model is flexible and can be extended to other A2G scenarios (not included in this paper) by adjusting the parameters according to the simulation or measurement data.
Tài liệu tham khảo
3GPP, 2016. Technical Specification Group Radio Access Network; Channel Model for Frequency Spectrum above 6 GHz (Release 14). TR 38.900 V14.2.0. 3rd Generation Partnership Project (3GPP).
Al-Hourani A, Gomez K, 2018. Modeling cellular-to-UAV path-loss for suburban environments. IEEE Wirel Commun Lett, 7(1):82–85. https://doi.org/10.1109/LWC.2017.2755643
Bhuvaneshwari A, Hemalatha R, Satyasavithri T, 2015. Path loss prediction analysis by ray tracing approach for NLOS indoor propagation. Proc Int Conf on Signal Processing and Communication Engineering Systems, p.486–491. https://doi.org/10.1109/SPACES.2015.7058202
Cai XS, Wang NX, Rodríguez-Piñeiro J, et al., 2019. Low altitude air-to-ground channel characterization in LTE network. Proc 13th European Conf on Antennas and Propagation, p.1–5.
Chen XM, Hu XJ, Zhu QM, et al., 2018. Channel modeling and performance analysis for UAV relay systems. China Commun, 15(12):89–97. https://doi.org/10.12676/j.cc.2018.12.007
Cheng LL, Zhu QM, Wang CX, et al., 2020. Modeling and simulation for UAV air-to-ground mmWave channels. Proc 14th European Conf on Antennas and Propagation, p.1–5. https://doi.org/10.23919/EuCAP48036.2020.9136077
Cui ZZ, Briso-Rodríguez C, Guan K, et al., 2019. Measurement-based modeling and analysis of UAV air-ground channels at 1 and 4 GHz. IEEE Antenn Wirel Propag Lett, 18(9):1804–1808. https://doi.org/10.1109/LAWP.2019.2930547
Dutta S, Hsieh F, Vook FW, 2019. HAPS based communication using mmWave bands. Proc IEEE Int Conf on Communications, p.1–6. https://doi.org/10.1109/ICC.2019.8761640
Fan W, Carton I, Nielsen JØ, et al., 2016. Measured wideband characteristics of indoor channels at centimetric and millimetric bands. EURASIP J Wirel Commun Netw, 2016(1):58. https://doi.org/10.1186/s13638-016-0548-x
Hur S, Baek S, Kim B, et al., 2016. Proposal on millimeter-wave channel modeling for 5G cellular system. IEEE J Sel Top Signal Process, 10(3):454–469. https://doi.org/10.1109/JSTSP.2016.2527364
ITU, 2017. Terrain Cover Types. International Telecommunication Union.
Khawaja W, Guvenc I, Matolak DW, et al., 2019. A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles. IEEE Commun Surv Tut, 21(3):2361–2391. https://doi.org/10.1109/COMST.2019.2915069
Li JF, Zhang XF, Cao RZ, et al., 2013. Reduced-dimension MUSIC for angle and array gain-phase error estimation in bistatic MIMO radar. IEEE Commun Lett, 17(3):443–446. https://doi.org/10.1109/LCOMM.2013.012313.122113
MacCartney GR, Rappaport TS, 2017a. Rural macrocell path loss models for millimeter wave wireless communications. IEEE J Sel Areas Commun, 35(7):1663–1677. https://doi.org/10.1109/JSAC.2017.2699359
MacCartney GR, Rappaport TS, 2017b. Study on 3GPP rural macrocell path loss models for millimeter wave wireless communications. Proc IEEE Int Conf on Communications, p.1–7. https://doi.org/10.1109/ICC.2017.7996793
MacCartney GR, Rappaport TS, Sun S, et al., 2015. Indoor office wideband millimeter-wave propagation measurements and channel models at 28 and 73 GHz for ultradense 5G wireless networks. IEEE Access, 3:2388–2424. https://doi.org/10.1109/ACCESS.2015.2486778
Mani F, Vitucci EM, Barbiroli M, et al., 2018. 26GHz ray-tracing pathloss prediction in outdoor scenario in presence of vegetation. Proc 12th European Conf on Antennas and Propagation, p.1–5. https://doi.org/10.1049/cp.2018.0384
Mededović P, Veletić M, Blagojević Z, 2012. Wireless insite software verification via analysis and comparison of simulation and measurement results. Proc 35th Int Convention MIPRO, p.776–781.
Rappaport TS, MacCartney GR, Samimi MK, et al., 2015. Wideband millimeter-wave propagation measurements and channel models for future wireless communication system design. IEEE Trans Commun, 63(9):3029–3056. https://doi.org/10.1109/TCOMM.2015.2434384
Rappaport TS, Sun S, Shafi M, 2017a. Investigation and comparison of 3GPP and NYUSIM channel models for 5G wireless communications. Proc IEEE 86th Vehicular Technology Conf, p.1–5. https://doi.org/10.1109/VTCFall.2017.8287877
Rappaport TS, Xing YC, MacCartney GR, et al., 2017b. Overview of millimeter wave communications for fifth-generation (5G) wireless networks—with a focus on propagation models. IEEE Trans Antenn Propag, 65(12):6213–6230. https://doi.org/10.1109/TAP.2017.2734243
Samimi MK, Rappaport TS, MacCartney GR, 2015. Probabilistic omnidirectional path loss models for millimeter-wave outdoor communications. IEEE Wirel Commun Lett, 4(4):357–360. https://doi.org/10.1109/LWC.2015.2417559
Shi Y, Enami R, Wensowitch J, et al., 2018. Measurement-based characterization of LOS and NLOS drone-to-ground channels. Proc IEEE Wireless Communications and Networking Conf, p.1–6. https://doi.org/10.1109/WCNC.2018.8377104
Sun S, Rappaport TS, Thomas TA, et al., 2016. Investigation of prediction accuracy, sensitivity, and parameter stability of large-scale propagation path loss models for 5G wireless communications. IEEE Trans Veh Technol, 65(5):2843–2860. https://doi.org/10.1109/TVT.2016.2543139
Wang CX, Bian J, Sun J, et al., 2018. A survey of 5G channel measurements and models. IEEE Commun Surv Tut, 20(4):3142–3168. https://doi.org/10.1109/COMST.2018.2862141
Wang XY, Gursoy MC, 2019. Coverage analysis for energy-harvesting UAV-assisted mmWave cellular networks. IEEE J Sel Areas Commun, 37(12):2832–2850. https://doi.org/10.1109/JSAC.2019.2947929
Wu YY, Gao ZB, Chen CB, et al., 2015. Ray tracing based wireless channel modeling over the sea surface near Diaoyu Islands. Proc 1st Int Conf on Computational Intelligence Theory, Systems and Applications, p.124–128. https://doi.org/10.1109/CCITSA.2015.35
Yang GS, Zhang Y, He ZW, et al., 2019. Machine-learning-based prediction methods for path loss and delay spread in air-to-ground millimetre-wave channels. IET Micro Antenn Propag, 13(8):1113–1121. https://doi.org/10.1049/iet-map.2018.6187
You XH, Wang CX, Huang J, et al., 2021. Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts. Sci China Inform Sci, 64(1):110301. https://doi.org/10.1007/s11432-020-2955-6
Zhang JH, Shafi M, Molisch A, et al., 2018. Channel models and measurements for 5G. IEEE Commun Mag, 56(12):12–13. https://doi.org/10.1109/MCOM.2018.8570033
Zhao XW, Du F, Geng SY, et al., 2020. Playback of 5G and beyond measured MIMO channels by an ANN-based modeling and simulation framework. IEEE J Sel Area Commun, 38(9):1945–1954. https://doi.org/10.1109/JSAC.2020.3000827
Zhong WZ, Xu L, Zhu QM, et al., 2019a. MmWave beam-forming for UAV communications with unstable beam pointing. China Commun, 16(1):37–46.
Zhong WZ, Xu L, Zhu QM, et al., 2019b. A novel beam design method for mmWave multi-antenna arrays with mutual coupling reduction. China Commun, 16(10):37–44. https://doi.org/10.23919/JCC.2019.10.002
Zhu QM, Li H, Fu Y, et al., 2018. A novel 3D non-stationary wireless MIMO channel simulator and hardware emulator. IEEE Trans Commun, 66(9):3865–3878. https://doi.org/10.1109/TCOMM.2018.2824817
Zhu QM, Wang YW, Jiang KL, et al., 2019. 3D non-stationary geometry-based multi-input multi-output channel model for UAV-ground communication systems. IET Microw Antenn Propag, 13(8):1104–1112. https://doi.org/10.1049/iet-map.2018.6129
Zhu QM, Jiang S, Wang CX, et al., 2020. Effects of digital map on the RT-based channel model for UAV mmWave communications. Proc Int Wireless Communications and Mobile Computing, p.1648–1653. https://doi.org/10.1109/IWCMC48107.2020.9148461