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Beamforming in 5G Mm-Wave Radio Networks Importance of Frequency Multiplexing for Users in Urban Macro Environments

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Beamforming in 5G Mm-Wave Radio Networks Importance of Frequency Multiplexing for Users in Urban Macro Environments UPTEC E 20002 Examensarbete 30 hp Mars 2020 Beamforming in 5G mm-wave radio networks Importance of frequency multiplexing for users in urban macro environments Carl Lutnaes Abstract Beamforming in 5G mm-wave radio networks Carl Lutnaes Teknisk- naturvetenskaplig fakultet UTH-enheten 5G brings a few key technological improvements compared to previous generations in telecommunications. These include, but are not limited to, greater speeds, Besöksadress: increased capacity and lower latency. These improvements are in part due to using Ångströmlaboratoriet Lägerhyddsvägen 1 high band frequencies, where increased capacity is found. By advancements in Hus 4, Plan 0 various technologies, mobile broadband traffic has become increasingly chatty, i.e. more small packets are being sent. From a capacity standpoint this Postadress: characteristic poses a challenge for early 5G millimeter-wave advanced antenna Box 536 751 21 Uppsala systems. This thesis investigates if network performance of 5G millimetre-wave systems can be improved by increasing the utilisation of the bandwidth by using Telefon: adaptive beamforming. Two adaptive codebook approaches are proposed; a single- 018 – 471 30 03 beam and a multi-beam approach. The simulations are performed in an outdoor urban Telefax: macro scenario. The results show that for a small packet scenario with good 018 – 471 30 00 coverage the ability to frequency multiplex users is important for good network performance. Hemsida: http://www.teknat.uu.se/student Handledare: Erik Larsson Ämnesgranskare: Steffi Knorn Examinator: Tomas Nyberg ISSN: 1654-7616, UPTEC E 20002 Popul¨arvetenskaplig sammanfattning 5G ¨arn¨astagenerations telekommunikationsstandard. Nya 5G–n¨atverksprodukter kommer att ha ¨okad kapacitet vilket leder till snabbare data¨overf¨oringaroch mindre f¨ordr¨ojningarf¨orenheter i n¨atverken, exempelvis mobiler. Tidiga pro- dukter utmanas ur ett kapacitetsperspektiv med att mobiltrafik k¨annetecknas av m˚angasm˚adatapaket. De m˚angaoch sm˚adatapaketen g¨ordet sv˚art att ha en h¨ogeffektivitet av totala kapaciteten. Detta examensarbete unders¨oker m¨ojlighetenatt ¨oka denna kapacitet, och s˚aledesn¨atverksprestandan, genom att optimera str˚alningm¨onstretsom kommer fr˚anantennerna. Scenariot som anv¨ands¨arett bra t¨ackningsscenario med sm˚adatapaket. Resultaten visar att ett adaptivt flertopps–m¨onster (eng. multi{beam), givet bra t¨ackning och sm˚adatapaket, kan ¨oka anv¨and kapacitet. Strategin kan vara anv¨andbari specifika 5G{applikationer. Detta examensarbete har utf¨ortsi sammarbete med Ericsson, som i sin tur har valt att s¨oka om patentr¨attigheterp˚aden f¨orslagnaflertopps{strategin. III Contents Popul¨arvetenskaplig sammanfattning III PrefaceIX Acknowledgements.......................IX Author's Note..........................X NotationXI Norms and operators......................XI Initialisms............................ XII 1 Introduction1 1.1 Research Question ....................... 2 1.2 Thesis Structure......................... 3 2 Theoretical Framework4 2.1 Introduction........................... 4 2.2 Domains of Beamforming.................... 5 2.2.1 Challenges Related to User Characteristics...... 5 2.3 Mathematical Definitions.................... 6 2.3.1 Coordinate System................... 6 2.3.2 Channel Capacity.................... 7 2.3.3 Wave Superposition................... 8 2.4 Antenna Theory......................... 9 2.4.1 Basics of Antennas and Antenna Beamforming.... 9 2.4.2 Key Antenna Characteristics.............. 10 2.4.3 EP............................ 11 2.4.4 Uniform Linear Array ................. 12 2.4.5 Uniform Planar Array (UPA)............. 17 2.5 Beamforming in Principle ................... 19 IV 2.5.1 DFT-based Codebook ................. 20 2.5.2 Pattern Modulation Through Tapering . 22 2.5.3 Adaptive Single Beam Approach ........... 24 2.5.4 Adaptive Multi-Beam Approach............ 25 2.5.5 UPA Beamforming................... 26 2.6 Scheduling............................ 26 2.6.1 5G New Radio Physical Layer............. 27 3 Methodology 31 3.1 Simulator ............................ 31 3.1.1 Simulator Setup..................... 31 3.2 Simulation cases......................... 34 3.3 Figure of Merits......................... 35 3.3.1 Served Traffic...................... 35 3.3.2 User Throughput.................... 35 3.3.3 Frequency Utilization.................. 36 3.3.4 Time Utilization .................... 36 3.3.5 Frequency Multiplexing of Users............ 36 4 Results and Analysis 37 4.1 User Throughput........................ 38 4.2 Frequency Utilization...................... 41 4.3 Time Utilization ........................ 44 4.4 Frequency Multiplexing..................... 46 4.5 Power Gain of Multi-beam Approach............. 48 5 Discussion 50 5.1 Good Coverage, Small File Size Results............ 50 5.2 Good Coverage, Large File Size Results............ 50 5.3 Low Coverage, Small File Size Results ............ 51 5.4 Limitations of The Findings.................. 52 5.5 Further Research........................ 52 5.5.1 Single Beam Approach................. 52 5.5.2 Multi Beam Approach................. 53 5.5.3 Simulation Improvements ............... 53 6 Conclusion 54 V List of Figures 2.1 Definition of spherical angles and unit vectors in the Cartesian coordinate system. ....................... 7 2.2 Illustration of relationship between bandwidth and S/N to channel capacity. ........................ 8 2.3 Two archetype cases of wave interference............ 9 2.4 AP of ULA with 4 elements. Element spacing is half the wave- length. The length of HPBW is illustrated in the main lobe. Each element has 0 dBi gain. ................. 11 2.5 EP used in simulations...................... 12 2.6 Illustration of an Uniform Linear Array (ULA). 13 2.7 Illustration of EP, AF and AP. ULA with N = 8 elements; ele- ment separation equalp to half the wavelength; the 8 weights are each set to wk = 1= 8 power; and the beam is subsequently steered towards θ = 90◦..................... 15 2.8 Illustration of the Uniform Linear Array of Antenna Elements 16 2.9 Gain of APs with different number of elements in the ULA. 17 2.10 Illustration of a 4x4 Uniform Planar Array (UPA). 18 2.11 Illustration a 2 × 1 ULA with vertical 2 × 1 sub-arrays. 18 2.12 Sub-array and AP for a 2 × 1 ULA with 2 × 1-sized sub-arrays. 19 2.13 Illustrates evenly spaced beams based on the DFT-codebook design. ULA with N=3 elements. Element separation of half the wavelength. Oversampling of 2 for a total of 6 beams. Each AP has a corresponding codeword representing it. 22 VI 2.14 16 element ULA. On elements: 4/16. Peak gain is 6 dB with no beam-steering......................... 24 2.15 16 element ULA. On elements: 16/16. Peak gain is 12 dB with no beam-steering...................... 24 2.16 Multipeak AP, N=16 antenna elements............. 25 2.17 The structure of the resource grid, resource element and phys- ical resource block in the 5G NR Physical Layer. 27 2.18 Each color represent one selected beam; each beam can be used by more than one UE if multiple UEs are in the same beam. The number of PRBs filled with a specific colour symbolizes the amount of resources the UEs gets. White color is unused resources. ............................ 30 3.1 Hexagonal Grid of placement of the 7 BS. .......... 32 3.2 Illustration of the used antenna in the simulations. 33 4.1 User throughput over served traffic. ISD: 200. File size: 12 kbit. 95th percentile (solid line), 50th percentile (dashed) and 5th percentile (dotted line) user throughput displayed. 38 4.2 User throughput over served traffic. ISD: 200. File size: 192 kbit. 95th percentile (solid line), 50th percentile (dashed) and 5th percentile (dotted line) network performance displayed. Note: target; multi-beam 2, 4 and 8 cases performs the same. 39 4.3 User throughput over served traffic. ISD: 500. File size: 12 kbit. 95th percentile (solid line), 50th percentile (dashed) and 5th percentile (dotted line) user throughput displayed. Note: target and multi-beam 8 cases performs the same for the 50th percentile user. ......................... 39 4.4 Frequency utilization of network. File size: 12 kbit. ISD: 200m 42 4.5 Frequency utilization of network. File size: 192 kbit. ISD: 200m. Note: target; multi-beam 2, 4 and 8 cases performs the same................................ 42 4.6 Frequency utilization of network. File size: 12 kbit. ISD: 500m. Note: target and multi-beam 8 cases performs the same. 43 4.7 Time utilization of network. File size: 12 kbit. ISD 200m. 44 4.8 Time utilization of network. File size: 192 kbit. ISD 200m. Note: target; multi-beam 2, 4 and 8 cases performs the same. 45 VII 4.9 Time utilization of network. File size: 12 kbit. ISD 500m. Note: target; multi-beam 4 and 8 cases performs the same. 45 4.10 Frequency multiplexing in the network. File size: 12 kbit. ISD: 200m. ........................... 46 4.11 Frequency multiplexing in the network. File size: 192 kbit. ISD: 200m. Note: target; multi-beam 2, 4 and 8 cases per- forms the same.......................... 47 4.12 Frequency multiplexing in the network. File size: 12 kbit. ISD: 500m. Note: target and multi-beam 8 cases performs the same. ............................ 47 4.13 Power gain of multi-beam codebook design approach. 48 List of Tables 3.1 Summary of the main simulation parameters. 33 3.2 Legends of the different studied cases. The case colour is the same across all figures for continuity. See Section 2.5.3 for Adaptive Width codebook beam design. See Section 2.5.4 for Multi-beam codebook
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