"WINNER II Channel Models", ver 1.1, Sept

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WINNER II D1.1.2 V1.1 Above it has been assumed that the CIR samples are taken for each MIMO channel separately and that the angle information has been vanished in this process. This is the case, when using the model e.g. with the WIM implementation [WIN2WIM]. 5.4.2.2 Down-scaling in frequency domain If desired, the down-scaling can also be performed in the frequency domain. Then the starting point will be the original CIR specified in the delay domain. This CIR is transformed in the frequency domain for each simulation block. Then the transformed CIR can be filtered as desired, e.g. by removing the extra frequency samples, and used in the simulation as normally. The maximum frequency sampling interval is determined by the coherence bandwidth 1 B c = , (5.4) Cσ τ where σ τ is the rms delay spread and C is a scaling constant related to fading distribution. 5.4.3 FDD modeling In next steps we explain how to obtain both uplink and downlink channel of an FDD system with bandwidths of 100 MHz. The center carrier frequencies are f c and f c + ∆f c : • Define BS and MS positions, calculate the channel for one link, e.g. BS to MS at certain carrier frequency • Save the small scale parameters • Exchange the positions of the BS and MS f c • Calculate the other link, in this example the MS to BS by: o Using saved small scale parameters o Randomizing the and initial phases of rays o Changing the carrier frequency to + ∆f 5.5 Comparison tables of WINNER channel model versions This section shows the main differences between the different versions of WINNER channel models (Phase I (D5.4), Phase II Interim (D1.1.1), and Phase II Final (D1.1.2) models). Note! This section is aimed as comparison of the different versions, not as the primary source of channel model parameters. f c Table below shows which scenarios are available in the different versions. Note that all the scenarios of Phase I have been updated in Phase II models. Table 5-2:Availability of Generic and CDL models Phase I Phase II Scenario D5.4 D1.1.1 D1.1.2 Code Definition Generic model CDL Generic model CDL Generic model CDL A1 indoor office yes yes yes yes yes yes A2 indoor-to-outdoor yes yes yes yes B1 urban micro-cell yes yes yes yes yes yes B2 bad urban micro-cell yes yes yes yes B3 large indoor hall yes yes yes yes yes yes Page 56 (82)
WINNER II D1.1.2 V1.1 B4 outdoor-to-indoor yes yes yes yes B5a stationary feeder yes yes yes B5b stationary feeder yes yes yes B5c stationary feeder yes yes yes B5d stationary feeder yes B5f stationary feeder yes yes C1 suburban macro-cell yes yes yes yes C2 urban macro-cell yes yes yes yes C3 bad urban macro-cell yes yes C4 urban macro outdoor-to-indoor yes C5 LOS feeder yes yes D1 rural macro-cell yes yes yes yes yes yes D2a moving networks yes yes yes yes D2b moving networks yes yes The features of Phase I model and Phase II model are compared in table below. Table 5-3: Comparison of Features. Feature Number of main scenarios (see table above) Number of scenarios including subscenarios (a,b,c,…) Number of scenarios including subscenarios and LOS/NLOS versions generic model Phase I Phase II D5.4 D1.1.1 D1.1.2 CDL generic model CDL generic model 7 7 13 13 14 14 10 10 16 16 18 18 15 15 21 21 24 24 CDL Indoor-to-outdoor models yes yes yes yes Outdoor-to-indoor models yes yes yes yes Bad urban models yes yes yes yes Moving networks models yes yes yes yes Support of coordinate system yes yes yes Support of multi-cell and multi-user simulations Support of multihop and relaying simulations yes yes yes yes yes* yes yes* yes yes* Correlation of large-scale parameters yes yes yes Support of interference simulations yes yes yes Time evolution yes yes Reduced variability clustered delay line (CDL) model for calibration, yes yes yes Page 57 (82)
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WINNER II D1.1.2 V1.1 IST-4-027756
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WINNER II D1.1.2 V1.1 Authors Partn
Page 5 and 6: WINNER II D1.1.2 V1.1 Table of Cont
Page 7 and 8: WINNER II D1.1.2 V1.1 1. Introducti
Page 9 and 10: WINNER II D1.1.2 V1.1 2. Definition
Page 11 and 12: WINNER II D1.1.2 V1.1 XPR XPRH XPRV
Page 13 and 14: WINNER II D1.1.2 V1.1 s t u Index t
Page 15 and 16: WINNER II D1.1.2 V1.1 Table 2-1 (co
Page 17 and 18: WINNER II D1.1.2 V1.1 2.3.3 B1 - Ur
Page 19 and 20: WINNER II D1.1.2 V1.1 2.3.7.4 B5f T
Page 21 and 22: WINNER II D1.1.2 V1.1 2.4.1 Propsou
Page 23 and 24: WINNER II D1.1.2 V1.1 This means th
Page 25 and 26: WINNER II D1.1.2 V1.1 Table 2-7 CRC
Page 27 and 28: WINNER II D1.1.2 V1.1 3.1 WINNER Ge
Page 29 and 30: WINNER II D1.1.2 V1.1 MS BS link se
Page 31 and 32: WINNER II D1.1.2 V1.1 ⎡ ρ(d) ∝
Page 33 and 34: WINNER II D1.1.2 V1.1 Let us assume
Page 35 and 36: WINNER II D1.1.2 V1.1 coefficients
Page 37 and 38: WINNER II D1.1.2 V1.1 4. Channel Mo
Page 39 and 40: WINNER II D1.1.2 V1.1 ( τ ' − mi
Page 41 and 42: WINNER II D1.1.2 V1.1 H u, s, n ( t
Page 43 and 44: WINNER II D1.1.2 V1.1 Table 4-3 Far
Page 45 and 46: WINNER II D1.1.2 V1.1 B3 LOS A = 13
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Page 49 and 50: WINNER II D1.1.2 V1.1 assumption th
Page 51 and 52: WINNER II D1.1.2 V1.1 d 2 2 BS , (
Page 53 and 54: WINNER II D1.1.2 V1.1 Figure 5-4: D
Page 55: WINNER II D1.1.2 V1.1 5.2 Space-tim
Page 59 and 60: WINNER II D1.1.2 V1.1 B3 LOS AoD sp
Page 61 and 62: WINNER II D1.1.2 V1.1 6. Parameter
Page 63 and 64: WINNER II D1.1.2 V1.1 6.3 B1 - Urba
Page 65 and 66: WINNER II D1.1.2 V1.1 Table 6-7 Sce
Page 67 and 68: WINNER II D1.1.2 V1.1 Table 6-10 Cl
Page 69 and 70: WINNER II D1.1.2 V1.1 Cluster # Del
Page 71 and 72: WINNER II D1.1.2 V1.1 Table 6-16 Sc
Page 73 and 74: WINNER II D1.1.2 V1.1 6.12.2 Scenar
Page 75 and 76: WINNER II D1.1.2 V1.1 15 1790 -20.3
Page 77 and 78: WINNER II D1.1.2 V1.1 7. References
Page 79 and 80: WINNER II D1.1.2 V1.1 [KKM02] [KBM+
Page 81 and 82: WINNER II D1.1.2 V1.1 [SCK05] [SCT0
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"WINNER II Channel Models", ver 1.1, Sept

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