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SCIENCE CHINA Information Sciences, Volume 64 , Issue 4 : 140302(2021) https://doi.org/10.1007/s11432-020-2986-8

Application of NOMA for cellular-connected UAVs: opportunities and challenges

Wee Kiat NEW 1,*, Chee Yen LEOW 1, Keivan NAVAIE 2, Yanshi SUN 3, Zhiguo DING 4,*
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  • ReceivedMar 19, 2020
  • AcceptedJul 17, 2020
  • PublishedMar 1, 2021
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Abstract


Acknowledgment

The work of Z G Ding was supported by the UK EPSRC (Grant No. EP/P009719/2). This work was also supported in part by H2020-MSCA-RISE-2015 (Grant No. 690750) and Ministry of Education Malaysia and Universiti Teknologi Malaysia (Grant Nos. 4J416, 08G83, 19H58, 04G37).


References

[1] Hayat S, Yanmaz E, Muzaffar R. Survey on Unmanned Aerial Vehicle Networks for Civil Applications: A Communications Viewpoint. IEEE Commun Surv Tutorials, 2016, 18: 2624-2661 CrossRef Google Scholar

[2] Zeng Y, Lyu J, Zhang R. Cellular-Connected UAV: Potential, Challenges, and Promising Technologies. IEEE Wireless Commun, 2019, 26: 120-127 CrossRef Google Scholar

[3] Zeng Y, Wu Q, Zhang R. Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond. Proc IEEE, 2019, 107: 2327-2375 CrossRef Google Scholar

[4] Afonso L, Souto N, Sebastiao P, et al. Cellular for the skies: exploiting mobile network infrastructure for low altitude air-to-ground communications. IEEE Aerosp Electron Syst Mag, 2016, 31: 4--11. Google Scholar

[5] Goddemeier N, Daniel K, Wietfeld C. Coverage evaluation of wireless networks for unmanned aerial systems. In: Proceedings of IEEE Globecom Workshops, Miami, 2010. 1760--1765. Google Scholar

[6] Dai L, Wang B, Ding Z. A Survey of Non-Orthogonal Multiple Access for 5G. IEEE Commun Surv Tutorials, 2018, 20: 2294-2323 CrossRef Google Scholar

[7] Ding Z, Lei X, Karagiannidis G K. A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends. IEEE J Sel Areas Commun, 2017, 35: 2181-2195 CrossRef Google Scholar

[8] Tse D, Viswanath P. Fundamentals of Wireless Communication. Cambridge: Cambridge University Press, 2005. Google Scholar

[9] New W K, Leow C Y, Navaie K. Robust Non-Orthogonal Multiple Access for Aerial and Ground Users. IEEE Trans Wireless Commun, 2020, 19: 4793-4805 CrossRef Google Scholar

[10] Agiwal M, Roy A, Saxena N. Next Generation 5G Wireless Networks: A Comprehensive Survey. IEEE Commun Surv Tutorials, 2016, 18: 1617-1655 CrossRef Google Scholar

[11] Generation Partnership Project. Unmanned aerial system (UAS) support in 3GPP — stage 1. TS 22.125. 2019. Google Scholar

[12] Mei W, Zhang R. Uplink Cooperative NOMA for Cellular-Connected UAV. IEEE J Sel Top Signal Process, 2019, 13: 644-656 CrossRef ADS arXiv Google Scholar

[13] Pang X, Gui G, Zhao N. Uplink Precoding Optimization for NOMA Cellular-Connected UAV Networks. IEEE Trans Commun, 2020, 68: 1271-1283 CrossRef Google Scholar

[14] Teng E, Falcao J, Iannucci B. Holes-in-the-sky: a field study on cellular-connected UAS. In: Proceedings of International Conference on Unmanned Aircraft Systems (ICUAS), Miami, 2017. 1165--1174. Google Scholar

[15] Khawaja W, Guvenc I, Matolak D W. A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles. IEEE Commun Surv Tutorials, 2019, 21: 2361-2391 CrossRef Google Scholar

[16] Khuwaja A A, Chen Y, Zhao N. A Survey of Channel Modeling for UAV Communications. IEEE Commun Surv Tutorials, 2018, 20: 2804-2821 CrossRef Google Scholar

[17] Amorim R, Nguyen H, Mogensen P. Radio Channel Modeling for UAV Communication Over Cellular Networks. IEEE Wireless Commun Lett, 2017, 6: 514-517 CrossRef Google Scholar

[18] Al-Hourani A, Kandeepan, Jamalipour A. Modeling air-to-ground path loss for low altitude platforms in urban environments. In: Proceedings of IEEE Global Communications Conference, Austin, 2014. 2898--2904. Google Scholar

[19] Al-Hourani A, Gomez K. Modeling Cellular-to-UAV Path-Loss for Suburban Environments. IEEE Wireless Commun Lett, 2018, 7: 82-85 CrossRef Google Scholar

[20] Lin X, Yajnanarayana V, Muruganathan S D. The Sky Is Not the Limit: LTE for Unmanned Aerial Vehicles. IEEE Commun Mag, 2018, 56: 204-210 CrossRef Google Scholar

[21] Generation Partnership Project. Study on Enhanced LTE Support for Aerial Vehicles. Technical Report 36.777, 2017. Google Scholar

[22] Qualcomm Technologies, Inc. LTE Unmanned Aircraft Systems: Trial Report v1.0.1. Technical Report, 2017. Google Scholar

[23] Van Der Bergh B, Chiumento A, Pollin S. LTE in the sky: trading off propagation benefits with interference costs for aerial nodes. IEEE Commun Mag, 2016, 54: 44-50 CrossRef Google Scholar

[24] Kovacs I, Amorim R, Nguyen H C, et al. Interference analysis for UAV connectivity over LTE using aerial radio measurements. In: Proceedings of the 86th Vehicular Technology Conference (VTC-Fall), Toronto, 2017. Google Scholar

[25] Stanczak J, Kovacs I, Koziol D, et al. Mobility challenges for unmanned aerial vehicles connected to cellular LTE networks. In: Proceedings of the 87th Vehicular Technology Conference (VTC Spring), Porto, 2018. Google Scholar

[26] Nguyen H C, Amorim R, Wigard J. How to Ensure Reliable Connectivity for Aerial Vehicles Over Cellular Networks. IEEE Access, 2018, 6: 12304-12317 CrossRef Google Scholar

[27] Xue Z, Wang J, Shi Q. Time-Frequency Scheduling and Power Optimization for Reliable Multiple UAV Communications. IEEE Access, 2018, 6: 3992-4005 CrossRef Google Scholar

[28] Yajnanarayana V, Wang Y P E, Gao S W, et al. Interference mitigation methods for unmanned aerial vehicles served by cellular networks. In: Proceedings of IEEE 5G World Forum (5GWF), Silicon Valley, 2018. 118--122. Google Scholar

[29] Euler S, Maattanen H, Lin X, et al. Mobility support for cellular connected unmanned aerial vehicles: performance and analysis. In: Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), Marrakesh, 2019. Google Scholar

[30] Xu X L, Zeng Y. Cellular-connected UAV: performance analysis with 3D antenna modelling. In: Proceedings of IEEE International Conference on Communications Workshops (ICC Workshops), Shanghai, 2019. Google Scholar

[31] Azari M M, Rosas F, Pollin S. Reshaping cellular networks for the sky: major factors and feasibility. In: Proceedings IEEE International Conference on Communications (ICC), Kansas, 2018. Google Scholar

[32] Azari M M, Rosas F, Pollin S. Cellular Connectivity for UAVs: Network Modeling, Performance Analysis, and Design Guidelines. IEEE Trans Wireless Commun, 2019, 18: 3366-3381 CrossRef Google Scholar

[33] Mei W, Zhang R. Cooperative Downlink Interference Transmission and Cancellation for Cellular-Connected UAV: A Divide-and-Conquer Approach. IEEE Trans Commun, 2020, 68: 1297-1311 CrossRef Google Scholar

[34] Chandhar P, Larsson E G. Massive MIMO for Connectivity With Drones: Case Studies and Future Directions. IEEE Access, 2019, 7: 94676-94691 CrossRef Google Scholar

[35] Geraci G, Garcia-Rodriguez A, Galati Giordano L. Understanding UAV Cellular Communications: From Existing Networks to Massive MIMO. IEEE Access, 2018, 6: 67853-67865 CrossRef Google Scholar

[36] Amer R, Saad W, Marchetti N. Toward a Connected Sky: Performance of Beamforming With Down-Tilted Antennas for Ground and UAV User Co-Existence. IEEE Commun Lett, 2019, 23: 1840-1844 CrossRef Google Scholar

[37] Challita U, Saad W, Bettstetter C. Interference Management for Cellular-Connected UAVs: A Deep Reinforcement Learning Approach. IEEE Trans Wireless Commun, 2019, 18: 2125-2140 CrossRef Google Scholar

[38] Zhang S W, Zhang R. Trajectory design for cellular-connected UAV under outage duration constraint. In: Proceedings of IEEE International Conference on Communications (ICC), Shanghai, 2019. Google Scholar

[39] Bulut E, Guevenc I. Trajectory optimization for cellular-connected UAVs with disconnectivity constraint. In: Proceedings of IEEE International Conference on Communications Workshops (ICC Workshops), Kansas, 2019. Google Scholar

[40] Khamidehi B, Sousa E S. Power efficient trajectory optimization for the cellular-connected aerial vehicles. In: Proceedings of the 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Istanbul, 2019. Google Scholar

[41] Cao X W, Xu J, Zhang R. Mobile edge computing for cellular-connected UAV: computation offloading and trajectory optimization. In: Proceedings of the 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Kalamata, 2018. Google Scholar

[42] Long Y, Yang T, Feng H, et al. Latency-aware base station selection scheme for cellular-connected UAVs. In: Proceedings of the 88th Vehicular Technology Conference (VTCFall), Chicago, 2018. Google Scholar

[43] Challita U, Ferdowsi A, Chen M. Machine Learning for Wireless Connectivity and Security of Cellular-Connected UAVs. IEEE Wireless Commun, 2019, 26: 28-35 CrossRef Google Scholar

[44] Vaezi M, Ding Z G, Poor H V. Multiple access technique for 5G wireless networks and beyond. Berlin: Springer, 2019. Google Scholar

[45] Liu L, Zhang S W, Zhang R. Exploiting NOMA for multi-beam UAV communication in cellular uplink. In: Proceedings of IEEE International Conference on Communications (ICC), Shanghai, 2019. Google Scholar

[46] Mu X, Liu Y, Guo L, Lin J. Non-Orthogonal Multiple Access for Air-to-Ground Communication. IEEE Transactions on Communications, 2020, Early Access: 1-1. Google Scholar

[47] Senadhira N, Durrani S, Zhou X. Uplink NOMA for Cellular-Connected UAV: Impact of UAV Trajectories and Altitude. IEEE Trans Commun, 2020, 68: 5242-5258 CrossRef Google Scholar

[48] Zaidi S K, Hasan S F, Gui X. Outage Analysis of Ground-Aerial NOMA With Distinct Instantaneous Channel Gain Ranking. IEEE Trans Veh Technol, 2019, 68: 10775-10790 CrossRef Google Scholar

[49] Mei W, Zhang R. Cooperative NOMA for Downlink Asymmetric Interference Cancellation. IEEE Wireless Commun Lett, 2020, 9: 884-888 CrossRef Google Scholar

[50] El-Gamal A, Kim Y. Networks Information Theory. Cambridge: Cambridge University Press, 2011. Google Scholar

[51] Zeng M, Yadav A, Dobre O A. Capacity Comparison Between MIMO-NOMA and MIMO-OMA With Multiple Users in a Cluster. IEEE J Sel Areas Commun, 2017, 35: 2413-2424 CrossRef Google Scholar

[52] Liu Y, Pan G, Zhang H. On the Capacity Comparison Between MIMO-NOMA and MIMO-OMA. IEEE Access, 2016, 4: 2123-2129 CrossRef Google Scholar

[53] Ali M S, Hossain E, Kim D I. Coordinated Multipoint Transmission in Downlink Multi-Cell NOMA Systems: Models and Spectral Efficiency Performance. IEEE Wireless Commun, 2018, 25: 24-31 CrossRef Google Scholar

[54] Nguyen V D, Tuan H D, Duong T Q. Precoder Design for Signal Superposition in MIMO-NOMA Multicell Networks. IEEE J Sel Areas Commun, 2017, 35: 2681-2695 CrossRef Google Scholar

[55] Ding Z, Fan P, Poor H V. Impact of User Pairing on 5G Nonorthogonal Multiple-Access Downlink Transmissions. IEEE Trans Veh Technol, 2016, 65: 6010-6023 CrossRef Google Scholar

[56] Ding Z G, Schober R, Poor H V. Unveiling the importance of SIC in NOMA systems: Part I — state of the art and recent findings. 2020,. arXiv Google Scholar

[57] Salehi M, Tabassum H, Hossain E. Accuracy of Distance-Based Ranking of Users in the Analysis of NOMA Systems. IEEE Trans Commun, 2019, 67: 5069-5083 CrossRef Google Scholar

[58] Guo S, Zhou X. Robust Resource Allocation With Imperfect Channel Estimation in NOMA-Based Heterogeneous Vehicular Networks. IEEE Trans Commun, 2019, 67: 2321-2332 CrossRef Google Scholar

[59] Azari M M, Rosas F, Chen K C. Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity. IEEE Trans Commun, 2018, 66: 330-344 CrossRef Google Scholar

[60] Usman M R, Khan A, Usman M A, et al. On The performance of perfect and imperfect SIC in downlink non orthogonal multiple access (NOMA). In: Proceedings of International Conference on Smart Green Technology in Electrical and Information Systems (ICSGTEIS), Bali, 2016. 102--106. Google Scholar

[61] Abu Mahady I, Bedeer E, Ikki S. Sum-Rate Maximization of NOMA Systems Under Imperfect Successive Interference Cancellation. IEEE Commun Lett, 2019, 23: 474-477 CrossRef Google Scholar

[62] Chen X, Jia R, Ng D W K. On the Design of Massive Non-Orthogonal Multiple Access With Imperfect Successive Interference Cancellation. IEEE Trans Commun, 2019, 67: 2539-2551 CrossRef Google Scholar

[63] Zhu J, Wang J, Huang Y. On Optimal Power Allocation for Downlink Non-Orthogonal Multiple Access Systems. IEEE J Sel Areas Commun, 2017, : 1-1 CrossRef Google Scholar

[64] Yang Z, Ding Z, Fan P. A General Power Allocation Scheme to Guarantee Quality of Service in Downlink and Uplink NOMA Systems. IEEE Trans Wireless Commun, 2016, 15: 7244-7257 CrossRef Google Scholar

[65] Chen Z, Ding Z, Dai X. An Optimization Perspective of the Superiority of NOMA Compared to Conventional OMA. IEEE Trans Signal Process, 2017, 65: 5191-5202 CrossRef ADS arXiv Google Scholar

[66] Zamani M R, Eslami M, Khorramizadeh M. Energy-Efficient Power Allocation for NOMA With Imperfect CSI. IEEE Trans Veh Technol, 2019, 68: 1009-1013 CrossRef Google Scholar

[67] Fang F, Zhang H, Cheng J. Joint User Scheduling and Power Allocation Optimization for Energy-Efficient NOMA Systems With Imperfect CSI. IEEE J Sel Areas Commun, 2017, 35: 2874-2885 CrossRef Google Scholar

[68] Sun Y, Ng D W K, Ding Z G, et al. Optimal joint power and subcarrier allocation for MC-NOMA systems. In: Proceedings of IEEE Global Communications Conference (GLOBECOM), Washington, 2016. Google Scholar

[69] Salaün L, Chen C S, Coupechoux M. Optimal joint subcarrier and power allocation in NOMA is strongly NP-hard. In: Proceedings of IEEE International Conference on Communications (ICC), Kansas City, 2018. Google Scholar

[70] Liang W, Ding Z, Li Y. User Pairing for Downlink Non-Orthogonal Multiple Access Networks Using Matching Algorithm. IEEE Trans Commun, 2017, 65: 5319-5332 CrossRef Google Scholar

[71] Sedaghat M A, Muller R R. On User Pairing in Uplink NOMA. IEEE Trans Wireless Commun, 2018, 17: 3474-3486 CrossRef Google Scholar

[72] Chen X, Gong F K, Li G. User Pairing and Pair Scheduling in Massive MIMO-NOMA Systems. IEEE Commun Lett, 2018, 22: 788-791 CrossRef Google Scholar

[73] Bui V, Nguyen P X, Nguyen H V, et al. Optimal user pairing for achieving rate fairness in downlink NOMA networks. In: Proceedings of International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Okinawa, 2019. 575--578. Google Scholar

[74] Budhiraja I, Tyagi S, Tanwar S. Cross Layer NOMA Interference Mitigation for Femtocell Users in 5G Environment. IEEE Trans Veh Technol, 2019, 68: 4721-4733 CrossRef Google Scholar

[75] Shin W, Vaezi M, Lee B. Non-Orthogonal Multiple Access in Multi-Cell Networks: Theory, Performance, and Practical Challenges. IEEE Commun Mag, 2017, 55: 176-183 CrossRef Google Scholar

[76] Beylerian A, Ohtsuki T. Coordinated non-orthogonal multiple access (CO-NOMA). In: Proceedings of IEEE Global Communications Conference (GLOBECOM), Washington, 2016. Google Scholar

[77] Choi J. Non-Orthogonal Multiple Access in Downlink Coordinated Two-Point Systems. IEEE Commun Lett, 2014, 18: 313-316 CrossRef Google Scholar

[78] Sun X, Yang N, Yan S. Joint Beamforming and Power Allocation in Downlink NOMA Multiuser MIMO Networks. IEEE Trans Wireless Commun, 2018, 17: 5367-5381 CrossRef Google Scholar

[79] Sun Y, Ding Z, Dai X. A Feasibility Study on Network NOMA. IEEE Trans Commun, 2018, 66: 4303-4317 CrossRef Google Scholar

[80] Ding Z, Adachi F, Poor H V. The Application of MIMO to Non-Orthogonal Multiple Access. IEEE Trans Wireless Commun, 2016, 15: 537-552 CrossRef Google Scholar

[81] Ding Z, Schober R, Poor H V. A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment. IEEE Trans Wireless Commun, 2016, 15: 4438-4454 CrossRef Google Scholar

[82] Ding Z, Poor H V. Design of Massive-MIMO-NOMA With Limited Feedback. IEEE Signal Process Lett, 2016, 23: 629-633 CrossRef ADS arXiv Google Scholar

[83] Badrudeen A A, Leow C Y, Won S H. Performance Analysis of Hybrid Beamforming Precoders for Multiuser Millimeter Wave NOMA Systems. IEEE Trans Veh Technol, 2020, 69: 8739-8752 CrossRef Google Scholar

[84] Khoshkholgh M G, Navaie K, Shin K G. Coverage Analysis of Multi-Stream MIMO HetNets With MRC Receivers. IEEE Trans Wireless Commun, 2017, 16: 7816-7833 CrossRef Google Scholar

[85] Gong M, Yang Z. The Application of Antenna Diversity to NOMA With Statistical Channel State Information. IEEE Trans Veh Technol, 2019, 68: 3755-3765 CrossRef Google Scholar

[86] Cherif N, Alzenad M, Yanikomeroglu H, et al. Downlink coverage and rate analysis of an aerial user in integrated aerial and terrestrial networks. 2019,. arXiv Google Scholar

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    Figure 1

    (Color online) Superiority of NOMA over OMA. (a) Rate region; (b) gain over FDMA.

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    Figure 2

    (Color online) Downlink multi-cell networks with co-existence of AU and TU.

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    Figure 3

    (Color online) Ground-to-air channel. (a) Channel attenuation; (b) probability of LOS.

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    Figure 4

    (Color online) Signal characteristics. (a) Coverage probability; (b) desired signal strength; (c) ICI level.

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    Figure 5

    (Color online) Signal behaviors. (a) Coverage probability; (b) desired signal; (c) NOMA co-channel interference.

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    Figure 6

    (Color online) NOMA vs. OMA. (a) Average TU rate; (b) average AU rate.

  • Table 1  

    Table 1Summary of related work
    Reference System Work type Key findings
    [14-25] OMA G2A channel: analysis, measurement, Effects of LOS/NLOS, sidelobe, coverage holes,
    simulation, modeling shadowing, small-scale fading, interference, mobility
    [18,19] OMA Air-to-ground (A2G) channel: analysis, Probability of LOS/NLOS
    measurement, simulation, modeling
    [24,26-33] OMA ICI: analysis and mitigation methods Coding, user association, transmitting,
    and receiving strategies could efficiently mitigate ICI
    [34-36] OMA Massive MIMO Array gain and spatial multiplexing can be obtained
    [37-43] OMA AUs' trajectories AUs may plan their optimal trajectories
    based on existing cellular infrastructure
    [12,13,45-47] NOMA Uplink NOMA technique can further be used to
    [9,48,49] Downlink improve AUs' performance
  • Table 2  

    Table 2Simulation parameters
    Parameter Value Parameter Value
    ($\varphi$, $\xi$, $\zeta$) (1, 0.151, 1) $G^{\text{rx}}_u$/$G^{\text{rx}}_t~$ 1 dB
    ($E_u$, $E_t$) ($-3$, 10) dB $(m^{\text{L}}_{u}$, $m^{\text{N}}_{u}$, $m_t$) (3, 2, 1)
    $\lambda_b$ 10 BSs/km$^2$ ($\theta^{\text{L}}_{u}$, $\theta^{\text{N}}_{u}$, $\theta_t$) ($\frac{1}{3}$, $\frac{1}{2}$, $1$)
    $B_{\rm~w}$ 180 KHz/RB $f_{\rm~c}$ 2 GHz