modelled and critical aspects in system design and performance can be investigated. Focus is thus on scenarios testing limits of performance. 8.1 Usage Scenarios As defined in Recommendation ITU-R M.2083, IMT-2020 is envisaged to expand and support diverse usage scenarios and applications that will continue beyond IMT-Advanced. There are three usage scenarios for IMT-2020 as follows: – Enhanced Mobile Broadband (eMBB): This usage scenario will come with new application areas and requirements in addition to existing Mobile Broadband applications for improved performance and an increasingly seamless user experience. This usage scenario covers a range of cases, including wide-area coverage and hotspot, which have different requirements. – Massive machine type communications (mMTC): This usage scenario is characterized by a very large number of connected devices typically transmitting a relatively low volume of non-delay-sensitive data. – Ultra-reliable and low latency communications (URLLC): This usage scenario has stringent requirements for capabilities such as throughput, latency and availability. Some examples include wireless control of industrial manufacturing or production processes, remote medical surgery, distribution automation in a smart grid, transportation safety, etc. 8.2 Test environments A test environment reflects a combination of geographic environment and usage scenario. There are five selected test environments for IMT-2020 as follows: − Indoor Hotspot-eMBB: An indoor isolated environment at offices and/or in shopping malls based on stationary and pedestrian users with very high user density. − Dense Urban-eMBB: An urban environment with high user density and traffic loads focusing on pedestrian and vehicular users. − Rural-eMBB: A rural environment with larger and continuous wide area coverage, supporting pedestrian, vehicular and high speed vehicular users. − Urban Macro–mMTC: An urban macro environment targeting continuous coverage focusing on a high number of connected machine type devices. − Macro–URLLC: An urban macro environment targeting ultra-reliable and low latency communications. The mapping of the five test environments and the three usage scenarios is given in Table 8-1. TABLE 8-1 Mapping of test environments and usage scenarios Usage scenarios mMTC URLLC Test environments Indoor Hotspot – eMBB Dense Urban – eMBB Rural – eMBB Urban Macro – mMTC Urban Macro – URLLC
A3-1 Definition of d2D and d3D for outdoor UTs (left), definition of d2D-out, d2D-in, d3D-out, and d3D-in for indoor UTs (right) Note that: (3-1) In the Tables A3-1 to A3-4, the following applies – Note 1: fc in GHz denotes the center frequency normalized by 1 GHz, distance related values in meters are normalized by 1 m, unless it is stated otherwise. – Note 2: hUT and hBS are the antenna height at BS and UT, respectively. h and W are the average building height and average street width. – Note 3: For UMa_x, UMi_x, break point distance d'BP = 4 h'BS h'UT fc/c, where fc is the centre frequency in Hz, c = 3.0108 m/s is the propagation velocity in free space, and h'BS and h'UT are the effective antenna heights at the BS and the UT, respectively. The effective antenna heights h'BS and h'UT are computed as follows: h'BS = hBS – hE, h'UT = hUT – hE, where hBS and hUT are the actual antenna heights, and hE is the effective environment height. For UMi_x hE=1 m. For UMa_x hE=1m with a probability equal to 1/(1+C(d2D, hUT)) and chosen from a discrete uniform distribution uniform(12,15,…,(hUT-1.5)) otherwise. Here C(d2D, hUT) given by: where: . – Note 4: For RMa_x, break point distance dBP = 2π hBS hUT fc/c, where fc is the centre frequency in Hz, c = 3.0108 m/s is the propagation velocity in free space, and hBS and hUT are the antenna heights at the BS and the UT, respectively.
3.1.1 InH_x A3-1 Path loss and shadow fading for InH_x InH_A InH_B LOS LOS ,dB, 0 m ≤ d2D ≤ 150 m, ,dB, 1 m ≤ d3D ≤ 150 m ,, 1 m ≤ d3D ≤ 150 m NLOS NLOS , dB, 0 m ≤ d2D ≤ 150 m ,dB,1 m ≤ d3D ≤ 150 m Optional:, dB , dB, 1 m ≤ d3D ≤ 150 m Optional: , dB 3 m ≤ hBS ≤ 6 m, 1 m ≤ hUT ≤ 2.5 m Optional Model I Optional Model II LOS LOS ,dB , ,dB, 1m ≤ d3D ≤ 150m,, NLOS NLOS ,dB , , dB
, , see Note 4 , dB , dB , see Note 4 , dB , dB NLOS NLOS , PLRMa-NLOS = 161.04 – 7.1 log10 (W) + 7.5 log10 (h) – (24.37 – 3.7(h/hBS)2) log10 (hBS) + (43.42 – 3.1 log10 (hBS)) (log10 (d3D)-3) + 20 log10(fc) – (3.2 (log10 (11.75 hUT)) 2 - 4.97), dB for 10 m < d2D < 21 km. For LMLC , , for 10 m < d2D < 21 km ,dB For LMLC , , , The applicability ranges: ,, , , , , The applicability ranges: ,, , Note: the RMa pathloss model for >7 GHz is validated based on a single measurement campaign conducted at 24 GHz.
ASA vs SF -0.5 -0.4 –0.5 –0.4 –0.5 –0.4 0 0 ASD vs SF -0.4 0 –0.4 0 –0.4 0 0 0 DS vs SF -0.8 -0.5 –0.8 –0.5 –0.8 –0.5 0.5 0.6 ASD vs ASA 0.4 0 0.4 0 0.4 0 0.1 0.1 ASD vs  0 N/A 0 N/A 0 N/A -0.2 N/A ASA vs  0 N/A 0 N/A 0 N/A 0.4 N/A DS vs  -0.5 N/A -0.5 N/A -0.5 N/A -0.3 N/A SF vs  0.5 N/A 0.5 N/A 0.5 N/A -0.2 N/A Cross-Correlations 1) ZSD vs SF 0.2 0 0.2 0 0.2 0 0 0 ZSA vs SF 0.3 0 0.3 0 0.3 0 0 0 ZSD vs K 0 N/A 0 N/A 0 N/A 0 N/A ZSA vs K 0.1 N/A 0.1 N/A 0.1 N/A 0 N/A ZSD vs DS 0.1 -0.27 0.1 -0.27 0.1 -0.27 0.2 0.2 ZSA vs DS 0.2 -0.06 0.2 -0.06 0.2 -0.06 0.3 0.1 ZSD vs ASD 0.5 0.35 0.5 0.35 0.5 0.35 0.2 0.1 ZSA vs ASD 0 0.23 0 0.23 0 0.23 0.1 0.3 ZSD vs ASA 0 -0.08 0 -0.08 0 -0.08 -0.3 0 ZSA vs ASA 0.5 0.43 0.5 0.43 0.5 0.43 0.1 0 ZSD vs ZSA 0 0.42 0 0.42 0 0.42 0.2 -0.1 Delay distribution Exp Exp Exp Exp Exp Exp Exp Exp
AOD and AOA distribution Laplacian Laplacian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian ZOD and ZOA distribution Laplacian Laplacian Laplacian Laplacian Laplacian Laplacian Laplacian Laplacian Delay scaling parameter r 3.6 3 3.6 3 3.6 3 N/A N/A XPR [dB] XPR 11 10 11 10 11 10 N/A N/A XPR 4 4 4 4 4 4 N/A N/A Number of clusters 15 19 15 19 15 19 4 7 Number of rays per cluster 20 20 20 20 20 20 20 20 Cluster DS () N/A N/A N/A N/A N/A N/A 6 5 Cluster ASD () 5 5 5 5 5 5 N/A N/A Cluster ASA () 8 11 8 11 8 11 N/A N/A Cluster ZSA () 9 9 9 9 9 9 N/A N/A Per cluster shadowing std  [dB] 6 3 6 3 6 3 N/A N/A Correlation distance in the horizontal plane [m] DS 8 5 8 5 8 5 0.2 0.8 ASD 7 3 7 3 7 3 2 1.5 ASA 5 3 5 3 5 3 2 3 SF 10 6 10 6 10 6 7 1 K 4 N/A 4 N/A 4 N/A 0.8 N/A ZSA 4 4 4 4 4 4 2 3 ZSD 4 4 4 4 4 4 2 4
TABLE A4-8 ZSD and ZOD offset parameters in InH_x Frequency Parameters InH_x LOS NLOS InH_A 0.5 GHz≤ fc ≤ 6 GHz ZOD spread (ZSD) lgZSD=log10(ZSD/1) lgZSD 1.02 1.08 0.41 0.36 ZOD offset µoffset,ZOD 0 0 6 GHz <fc ≤ 100 GHz ZOD spread (ZSD) lgZSD=log10(ZSD/1) lgZSD -1.43 log10(1+ fc)+2.228 1.08 lgZSD 0.13 0.36 ZOD offset µoffset,ZOD 0 0 InH_B 0.5 GHz≤ fc ≤ 100 GHz NOTE: For InH and frequencies below 6 GHz, use fc = 6 when determining the values of the ZSD parameter values ZOD spread (ZSD) lgZSD=log10(ZSD/1) lgZSD -1.43 fc)+2.228 1.08 lgZSD 0.13 log10(1+fc)+0.30 0.36 ZOD offset µoffset,ZOD 0 0 Optional Model I 28 GHz ZOD spread (ZSD) lgZSD=log10(ZSD/1) lgZSD 0.16 0.06 lgZSD 0.18 0.17 4.5.2 UMa_x TABLE A4-9 Fast fading parameters for UMa_x UMa_A UMa_B
1) ZSD vs SF 0 0 0 0 0 0 0 0 0 ZSA vs SF 0 0 0 0 0 0 0 0 0 ZSD vs K 0 N/A N/A 0 N/A N/A 0 N/A N/A ZSA vs K 0 N/A N/A 0 N/A N/A 0 N/A N/A ZSD vs DS 0 -0.5 -0.6 0 -0.5 -0.6 0 -0.5 -0.6 ZSA vs DS 0.2 0 -0.2 0.2 0 -0.2 0.2 0 -0.2 ZSD vs ASD 0.5 0.5 -0.2 0.5 0.5 -0.2 0.5 0.5 -0.2 ZSA vs ASD 0.3 0.5 0 0.3 0.5 0 0.3 0.5 0 ZSD vs ASA 0 0 0 0 0 0 0 0 0 ZSA vs ASA 0 0.2 0.5 0 0.2 0.5 0 0.2 0.5 ZSD vs ZSA 0 0 0.5 0 0 0.5 0 0 0.5 Delay distribution Exp Exp Exp Exp Exp Exp Exp Exp Exp AOD and AOA distribution Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian Wrapped Gaussian ZOD and ZOA distribution Laplacian Laplacian Laplacian Laplacian Laplacian Laplacian Laplacian Laplacian Laplacian scaling parameter r 3.2 3 2.2 3 2.1 2.2 3 2.1 2.2 XPR [dB] XPR 9 8.0 9 9 8.0 9 9 8.0 9 XPR 3 3 11 3 3 5 3 3 5 Number of clusters 12 19 12 12 19 12 12 19 12 Number of rays per cluster 20 20 20 20 20 20 20 20 20 Cluster DS () NA NA NA 5 11 11 5 11 11 Cluster ASD () 3 10 5 3 10 5 3 10 5
ASD vs K 0 N/A N/A ASA vs K 0 N/A N/A DS vs K 0 N/A N/A SF vs K 0 N/A N/A Cross-Correlations ZSD vs SF -0.04 0 ZSA vs SF -0.17 -0.25 0 ZSD vs K 0 N/A N/A ZSA vs K -0.02 N/A N/A ZSD vs DS -0.05 -0.10 0 ZSA vs DS 0.27 -0.40 0 ZSD vs ASD 0.73 0.42 0.66 ZSA vs ASD -0.14 -0.27 0.47 ZSD vs ASA -0.20 -0.18 -0.55 ZSA vs ASA 0.24 0.26 -0.22 ZSD vs ZSA -0.07 -0.27 0 Delay scaling parameter r 3.8 1.7 1.7 XPR [dB] XPR 12 7 7 XPR 4 3 3 Number of clusters 11 10 10 Number of rays per cluster 20 20 20 Cluster DS () in [ns] N/A N/A N/A Cluster ASD () in [deg] 2 2 2 Cluster ASA () in [deg] 3 3 3 Cluster ZSA () in [deg] 3 3 3 Per cluster shadowing std  [dB] 3 3 3 Correlation distance in the horizontal plane [m] DS 50 36 36 ASD 25 30 30
ASA 35 40 40 SF 37 120 120 K 40 N/A N/A ZSA 15 50 50 ZSD 15 50 50 TABLE A4-14 ZSD and ZOD offset parameters for RMa GHz≤ fc ≤ 6 GHz, GHz≤ fc ≤ 7 Parameters LOS NLOS O2I ZOD spread (ZSD) lgZSD max(-1, -0.17*( d2D /1000)-0.01*( hUT -1.5)+0.22) max(-1, -0.19*( d2D /1000)-0.01*( hUT -1.5)+0.28) max(-1, -0.19*( d2D /1000)-0.01*( hUT -1.5)+0.28) lgZSD 0.34 0.30 0.30 ZOD offset µoffset,ZOD 0 arctan((35-3.5)/ d2D) - d2D) arctan((35-3.5)/ d2D) - d2D)
A2.1.8 Time-spatial profile in cluster a) Delay profile in the ith cluster An empirical profile model normalized by the first arrival path’s power in the ith cluster is given as follows: (A2-28) where lI and lImax denote the average excess path distance and the maximum excess path distance in the cluster, respectively. On the other hand, the excess path distance l (m) can be changed to the access delay time  (s) by using the relation of . The delay profile model in the cluster, , can then be determined: (A2-29) where  I and Imax denote the excess average delay time and the maximum excess delay time in the cluster, respectively. b) Departure angular profile in the ith cluster An empirical departure angular profile AODI (ik) with departure angle ik in the ith cluster normalized by its central angular path’s power is given as: (A2-30) c) Arrival angular profile in the ith cluster An empirical arrival angular profile model AOAI (ik) with arrival angle AI in the ith cluster normalized by its central angular path’s power is given by: (A2-31) where AI denotes the average arrival angle in the cluster. AI 180º is a typical value. A2.2 Generation of reduced variability models based on TSP model A2.2.1 NLOS scenario The reduced variability is created by setting its key parameters. Each channel can be realized by the following procedure: Step 1: Set test environments and key parameters Set the Frequency conditions, City structure and Cell conditions on Table AA2-1. Step 2: Set the simulation conditions Set the number of clusters for NLOS and LOS, level difference between the peak path’s power and cut off power in NLOS scenario Lth and LOS scenario LSth. Step 3: Generation of long-term TSP Step 3.1: Generation of delay time a) Calculation of maximum delay time Convert excess distance l (m) into excess delay time  (s) by equation (A2-32): (A2-32) The maximum delay time can be calculated by considering Lth as follows: