Location Aware Beamforming in Millimeter-Wave Band Ultra-Dense Radio Access Networks. Part 1. Model of Two Links

The evolution of 1G to 4G radio access networks (RANs) over the past 40 years has shown that beamforming (BF) capabilities add an additional spatial dimension to traditional device multiplexing methods. When base stations (gNodeB - gNB) and user equipment (UE) form narrow antenna radiation patterns (APPs), in addition to frequency, time and code division of channels, an additional spatial dimension appears that implements spatial multiplexing. This concept has been known for quite a long time, but the full implementation of its capabilities in practice is expected with the widespread adoption of millimeter wave (mmWave) ultra-dense networks (UDN) of the fifth (5G) and subsequent (B5G) generations. To control APP, the approach of preliminary analysis of training sequences about the current situation in the radio channel  - CSI (Channel State Information) - can be used, but its overhead costs become unacceptably high in conditions of ultra-dense distribution of devices. An alternative approach is positioning-based BF. The validity, relevance and prospects of this approach are determined by the fact that for 5G networks, unlike previous generations, for the first time the requirements for UE positioning accuracy up to one meter are formalized. Initial research in the field of location-aware BF has already been carried out over the past years, however, mainly for particular scenarios of one or more radio links between gNBs and fixed UEs. In this work, for the first time, a scientifically based methodology for controlling the beam pattern of a stationary gNB based on the positioning of a mobile UE for a two-radio link scenario is formalized and implemented in software. The problem of practical implementation of BF is the difficulties to predict level of interference due to the mutual influence of radio links with mobile UEs. When estimating the instantaneous signal-to-interference ratio in a two-radio link scenario between two fixed gNBs that perform BF based on the current location of mobile UEs as they move, it is necessary to take into account the mutual influence of each other's radio links on each other. In such a scenario, a transmitter on one radio link acts both as a source of a wanted signal for one UE and as a source of an interfering signal for another UE. The task of assessing interference for such a scenario is complicated by the nonlinearity of the transmitter and/or receiver ARPs. The model developed and implemented in software in this work uses the functions of the Phased Array System Toolbox Matlab extension package. The simulation results show a significant scatter (tens of dB) of the instantaneous signal-to-interference ratio depending on the territorial separation of devices and can be used to justify scenarios for the construction and operation of 5G/B5G UDN.

1. Fokin G.A. Concept of Location-Aware Beamforming in 5G Networks. Vestnik Ssviazy. 2022;10:1‒7.

2. Russian Science Foundation. Location aware beamforming in mm-wave band ultra-dense radio access networks. URL: https://rscf.ru/en/project/22-29-00528 [Accessed 10.09.2023]

3. Fokin G.A., Koucheryavy A.E. Network positioning in the 5G ecosystem. Electrosvyaz. 2020;9:51‒58. DOI:10.34832/ELSV. 2020.10.9.006

4. Fokin G.A. Utilization of Network Positioning Methods in the 5G Ecosystem. Elektrosvyaz. 2020;11:29‒37. DOI:10.34832/ ELSV.2020.12.11.002

5. Fokin G.A. A Set of Models and Methods for Positioning Devices in Fifth-Generation Networks. D.Sc Thesis. St. Petersburg: The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Publ.; 2021. 499 p.

6. Fokin G.A. Technologies of Network Positioning. St. Petersburg: The Bonch-Bruevich State University of Telecommunications Publ.; 2020. 558 p.

7. Fokin G.A. 5G Network Positioning Technologies. Moscow: Hot Line - Telecom Publ.; 2021. 456 p.

8. Fokin G.А. Simulation of ultra dense 5G radio access networks with beamforming. T-Comm. 2021;15(5):4‒21. DOI:10.36724/2072-8735-2021-15-5-4-21

9. Fokin G.А. Beamforming models in ultra-dense 5G radio access networks. Part 1: Interference evaluation. First mile. 2021;3(95):66‒73. DOI:10.22184/2070-8963.2021.95.3.66.73

10. Fokin G.А. Beamforming models in ultra-dense 5G radio access networks. Part 2: Device separation evaluation. First mile. 2021;4(96):66‒73. DOI:10.22184/2070-8963.2021.96.4.66.72

11. Fokin G.А. Beam alignment procedures for 5G NR devices. Elektrosvyaz. 2022;2:26‒31. DOI:10.34832/ELSV.2022.27.2.003

12. Fokin G.А. Beam management models in 5G NR networks. Part 1. Beam alignment during link establishment. First mile. 2022;1(101):42‒49. DOI:10.22184/2070-8963.2022.101.1.42.49

13. Fokin G.А. Beam management models in 5G NR networks. Part 2. Beam alignment during radio communication. First mile. 2022;3(103):62‒69. DOI:10.22184/2070-8963.2022.103.3.62.68

14. Fokin G. Simulation Model of 5G NR PRS Network Positioning Technology with Meter Accuracy. Part 1. PRS Signals Configuration. Proc. of Telecommun. Univ. 2022;8(2):48‒63. DOI:10.31854/1813-324X-2022-8-2-48-63

15. Fokin G. Simulation Model of 5G NR Network Positioning Technology with Meter Accuracy. Part 2. PRS Signals Processing. Proc. of Telecommun. Univ. 2022;8(3):80‒99. DOI:10.31854/1813-324X-2022-8-3-80-99

16. Fokin G.A., Lazarev V.O. Software Module for Assessing the Mutual Influence of Radio Links of Two Adaptive Antennas During Beamforming. Patent RF, no. 2021662103, 14.07.2021.

17. Rappaport T.S., Gutierrez F., Ben-Dor E., Murdock J.N., Qiao Y., Tamir J.I. Broadband Millimeter-Wave Propagation Measurements and Models Using Adaptive-Beam Antennas for Outdoor Urban Cellular Communications. IEEE Transactions on Antennas and Propagation. 2013;61(4):1850‒1859. DOI:10.1109/TAP.2012.2235056

18. Nam Y.-H., Ng B.L., Sayana K., Li Y., Zhang J. Kim Y., et al. Full-dimension MIMO (FD-MIMO) for next generation cellular technology. IEEE Communications Magazine. 2013;51(6):172‒179. DOI:10.1109/MCOM.2013.6525612

19. Lu L., Li G.Y., Swindlehurst A.L., Ashikhmin A., Zhang R. An Overview of Massive MIMO: Benefits and Challenges. IEEE Journal of Selected Topics in Signal Processing. 2014;8(5):742‒758. DOI:10.1109/JSTSP.2014.2317671

20. Razavizadeh S.M., Ahn M., Lee I. Three-Dimensional Beamforming: A new enabling technology for 5G wireless networks. IEEE Signal Processing Magazine. 2014;31(6):94‒101. DOI:10.1109/MSP.2014.2335236

21. Roh W., Seol J.-Y., Park J., Lee B., Lee J., Kim Y., et al. Millimeter-wave beamforming as an enabling technology for 5G cellular communications: theoretical feasibility and prototype results. IEEE Communications Magazine. 2014;52(2):106‒113. DOI:10.1109/MCOM.2014.6736750

22. Larsson E.G., Edfors O., Tufvesson F., Marzetta T.L. Massive MIMO for next generation wireless systems. IEEE Communications Magazine. 2014;52(2):186‒195. DOI:10.1109/MCOM.2014.6736761

23. Sun S., Rappaport T.S., Heath R.W., Nix A., Rangan S. Mimo for millimeter-wave wireless communications: beamforming, spatial multiplexing, or both? IEEE Communications Magazine. 2014;52(12):110‒121. DOI:10.1109/MCOM.2014.6979962

24. Han S., I C.-l., Xu Z., Rowell C. Large-scale antenna systems with hybrid analog and digital beamforming for millimeter wave 5G. IEEE Communications Magazine. 2015;53(1):186‒194. DOI:10.1109/MCOM.2015.7010533

25. Kutty S., Sen D. Beamforming for Millimeter Wave Communications: An Inclusive Survey. IEEE Communications Surveys & Tutorials. 2016;18(2):949‒973. DOI:10.1109/COMST.2015.2504600

26. Rappaport T.S., Xing Y., MacCartney G.R., Molisch A.F., Mellios E., Zhang J. Overview of Millimeter Wave Communications for Fifth-Generation (5G) Wireless Networks – With a Focus on Propagation Models. IEEE Transactions on Antennas and Propagation. 2017;65(12):6213‒6230. DOI:10.1109/TAP.2017.2734243

27. Heath R.W., González-Prelcic N., Rangan S., Roh W., Sayeed A.M. An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems. IEEE Journal of Selected Topics in Signal Processing. 2016;10(3):436‒453. DOI:10.1109/JSTSP. 2016.2523924

28. Björnson E., Sanguinetti L., Wymeersch H., Hoydis J., Marzetta T.L. Massive MIMO is a reality ‒ What is next? Five promising research directions for antenna arrays. Digital Signal Processing. 2019;94:3‒20. DOI:10.1016/j.dsp.2019.06.007

29. Heng Y., Andrews J.G., Mo J., Va V., Ali A., Ng B.L., et al. Six Key Challenges for Beam Management in 5.5G and 6G Systems. IEEE Communications Magazine. 2021;59(7):74‒79. DOI:10.1109/MCOM.001.2001184

30. Bang J., Chung H., Hong J., Seo H., Choi J., Kim S. Millimeter-Wave Communications: Recent Developments and Challenges of Hardware and Beam Management Algorithms. IEEE Communications Magazine. 2021;59(8):86‒92. DOI:10.1109/MCOM.001.2001010

31. Maiberger R., Ezri D., Erlihson M. Location based beamforming. Proceedings of the 26th Convention of Electrical and Electronics Engineers in Israel, 17‒20 November 2010, Eilat, Israel. IEEE; 2010. p.000184‒000187. DOI:10.1109/EEEI.2010.5661954

32. Alkhateeb A., Ayach O.El., Leus G., Heath R.W. Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems. IEEE Journal of Selected Topics in Signal Processing. 2014;8(5):831‒846. DOI:10.1109/JSTSP.2014.2334278

33. Va V., Zhang X., Heath R.W. Beam Switching for Millimeter Wave Communication to Support High Speed Trains. Proceedings of the 82nd Vehicular Technology Conference, VTC2015-Fall, 06‒09 September 2015, Boston, USA. IEEE; 2015. DOI:10.1109/VTCFall.2015.7390855

34. Va V., Heath R.W. Basic Relationship between Channel Coherence Time and Beamwidth in Vehicular Channels. Proceedings of the 82nd Vehicular Technology Conference, VTC2015-Fall, 06‒09 September 2015, Boston, USA. IEEE; 2015. DOI:10.1109/VTCFall.2015.7390852

35. Va V., Choi J., Heath R.W. The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and Its Implications. IEEE Transactions on Vehicular Technology. 2017;66(6):5014‒5029. DOI:10.1109/TVT.2016.2622164

36. Va V., Shimizu T., Bansal G., Heath R.W. Beam design for beam switching based millimeter wave vehicle-to-infrastructure communications. Proceedings of the International Conference on Communications, ICC, 22‒27 May 2016, Kuala Lumpur, Malaysia. IEEE; 2016. DOI:10.1109/ICC.2016.7511414

37. Andrews J.G., Zhang X., Durgin G.D., Gupta A.K. Are we approaching the fundamental limits of wireless network densification? IEEE Communications Magazine. 2016;54(10):184‒190. DOI:10.1109/MCOM.2016.7588290

38. Chiaraviglio L., Turco S., Bianchi G., Blefari-Melazzi N. “Cellular Network Densification Increases Radio-Frequency Pol-lution”: True or False? IEEE Transactions on Wireless Communications. 2022;21(4):2608‒2622. DOI:10.1109/TWC.2021.3114198

39. Thors B., Furuskär A., Colombi D., Törnevik C. Time-Averaged Realistic Maximum Power Levels for the Assessment of Radio Frequency Exposure for 5G Radio Base Stations Using Massive MIMO. IEEE Access. 2017;5:19711‒19719. DOI:10.1109/ ACCESS.2017.2753459

40. Chiaraviglio L., Rossetti S., Saida S., Bartoletti S., Blefari-Melazzi N. “Pencil Beamforming Increases Human Exposure to ElectroMagnetic Fields”: True or False? IEEE Access. 2021;9:25158‒25171. DOI:10.1109/ACCESS.2021.3057237

41. Ali A., Karabulut U., Awada A., Viering I., Tirkkonen O., Barreto A.N., et al. System Model for Average Downlink SINR in 5G Multi-Beam Networks. Proceedings of the 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 08‒11 September 2019, Istanbul, Turkey. IEEE; 2019. DOI:10.1109/PIMRC.2019.8904367

42. Awada A., Lobinger A., Enqvist A., Talukdar A., Viering I. A simplified deterministic channel model for user mobility investigations in 5G networks. Proceedings of the International Conference on Communications, ICC, 21‒25 May 2017, Paris, France. IEEE; 2017. DOI:10.1109/ICC.2017.7997079

43. Yu B., Yang L., Ishii H. Load Balancing With 3-D Beamforming in Macro-Assisted Small Cell Architecture. IEEE Transactions on Wireless Communications. 2016;15(8):5626‒5636. DOI:10.1109/TWC.2016.2563430

44. Velazquez S.R., Broadstone S.R., Chiang A.M. Communication system using geographic position data. Patent U.S., no. 20040104839, 2004.

45. Wu W.R., Wang, Y.K. Localization-based beamforming scheme for systems with multiple antennas. Patent U.S., no. 9755797, 2017.

46. Gross F. Smart Antennas for Wireless Communications: With MATLAB. McGraw-Hill Professional; 2005. 288 p.

47. Balanis C.A. Antenna theory: analysis and design. John Wiley & Sons; 2016. 1104 p.

48. Mailloux R.J. Phased Array Antenna Handbook. Artech House; 2017. 691 p.

49. MathWorks. phased.URA. Uniform rectangular array. URL: https://www.mathworks.com/help/phased/ref/phased.ura-system-object.html [Accessed 10.09.2023]

50. MathWorks. beamwidth. Beamwidth of antenna. URL: https://www.mathworks.com/help/antenna/ref/beamwidth.html [Accessed 10.09.2023]

51. MathWorks. viewArray. View array geometry. URL: https://www.mathworks.com/help/phased/ref/phased.ura.viewarray.html [Accessed 10.09.2023]

52. MathWorks. pattern. Plot URA array pattern. URL: https://www.mathworks.com/help/phased/ref/phased.ura.pattern. html [Accessed 10.09.2023]

53. MathWorks. patternAzimuth. Plot URA array directivity or pattern versus azimuth. URL: https://uk.mathworks.com/help/ phased/ref/phased.ura.patternazimuth.html [Accessed 10.09.2023]

54. MathWorks. patternElevation. Plot URA array directivity or pattern versus elevation. URL: https://www.mathworks.com/help/phased/ref/phased.ura.patternelevation.html [Accessed 10.09.2023]

55. MathWorks. phased.SteeringVector. Sensor array steering vector. URL: https://www.mathworks.com/help/phased/ref/phased.steeringvector-system-object.html [Accessed 10.09.2023]

56. MathWorks. phased.ArrayGain. Sensor array gain. URL: https://www.mathworks.com/help/phased/ref/phased.arraygain-system-object.html [Accessed 10.09.2023]

57. MathWorks. rangeangle. Range and angle calculation. URL: https://www.mathworks.com/help/phased/ref/rangeangle.html [Accessed 10.09.2023]

58. MathWorks. fspl. Free space path loss. URL: https://www.mathworks.com/help/phased/ref/fspl.html [Accessed 10.09.2023]

59. MathWorks. Phased Array System Toolbox. URL: https://www.mathworks.com/help/phased [Accessed 10.09.2023]

60. GitHub. LAB Link Level Simulator with Phased Array System Toolbox. URL: https://github.com/grihafokin/LAB_link_ level_past_rus [Accessed 10.09.2023]