Final report on link level and system level channel models - Winner

WINNER D5.4 v. 1.4
2.1.7 Scenario D1: Rural macro-cell
Scenario D1 is defined only through its size (100 km 2 ) and hexagonal cell lay-out in [D7.2].
The rural environment we measured is flat, consisting of mainly sparsely located houses along roads that
lead trough fields and some small forests and a small village. This should be considered when interpreting
results based on our model.
3. WINNER Channel Models
This chapter describes WINNER MIMO channel models of seven propagation scenarios for link level and
system level simulations. Link level is defined for a single communication link. System level is defined
for multi communication links and base stations. Five of these scenarios are the prioritized propagation
scenarios defined in the WINNER project in [D7.2] for short range and wide area wireless
communications. The prioritized scenarios are: Scenario A1 for indoor small office environments,
Scenario B1 for microcell urban environment, Scenario B5 for hotspot LOS stationary wireless feeder,
Scenario C2 for Metropolitan ubiquitous coverage in macrocell urban environment, Scenario D1 for
macrocell rural environment. The two additional scenarios are part of the WINNER channel model:
Scenario B3 for indoor propagation and Scenario C1 for macrocell suburban environment.
In this chapter, we provide description of the generic channel model, which is based on the principles of
the SCM [3GPP SCM], for scenario A1, B1, B3, C1, C2, and D1. We also present clustered delay line
(CDL) models for the mentioned six scenarios of interest to generic model, and stationary feeder models
for scenario B5. The generic channel model is a geometric-based stochastic channel model. The following
subsections describe the WINNER phase-I MIMO channel models at 5 GHz.
3.1 Generic model
We apply the framework of the generic channel modelling approach presented in Chapter 4 to WINNER
scenarios A1, B1, B3, C1, C2, and D1. Scenario B5 is not considered in the generic channel model since
it is a stationary wireless feeder scenario, where transmitter and receiver ends are fixed. Scenario B5 is
modelled separately as clustered (tapped) delay line model (CDL) in Section 3.2.4.
The generic channel model generates a number of ZDSCs. Their delays and directional properties are
extracted from statistical distributions that correspond to a specific scenario, which are obtained from
measurement results or from literature. The number of ZDSCs varies from one scenario to another.
Indeed, the number of ZDSCs itself is a random variable. However, in order to reduce the complexity for
simulation purpose, it has been kept as a fixed parameter. The median of the number ZDSCs is selected.
We fix the number of rays within each ZDSC to 10 rays that have same delays and powers and may differ
in angles, either departure or arrival. The directional properties of each ZDSC may vary from one
scenario to another and from departure side to arrival side. The WINNER generic channel model is
antenna independent. Hence, different antenna configurations can be supported. In later terminology, the
downlink is considered, where the transmitter is the fixed station (BS) and the receiver is the mobile
station (MS). However, the same models can also be used for uplink simulations due to the reciprocity of
the radio channel.
3.1.1 Large-scale parameters
The radio channel is in general not stationary. Nevertheless, over short periods of time and space, channel
parameters experience small variations, and the assumption of short-term stationarity is often a very good
approximation. The parameters characterizing our channel model are called bulk parameters. The time
durations, over which these bulk parameters are constant, are termed channel segments a.k.a. drops in the
nomenclature of the SCM. Over time and space, bulk parameters change and we characterize this
variability statistically.
There are a large number of bulk parameters. Bulk parameters include detailed or low-level bulk
parameters such as number of paths, path powers, path angles at both link ends, path elevations at both
link ends, and path delays. To characterize the channel with fewer parameters, higher level, e.g. secondorder,
statistics are extracted on a per-segment basis, which we denote large-scale or dispersion metric
parameters. Large-scale parameters characterize the distributions of and between previously mentioned
low-level bulk parameters. Because realisations of large-scale parameters are drawn only once per
channel segment, they are bulk parameters themselves. The following large-scale parameters are
considered:
• Shadowing. The log-normal shadowing (LNS) value is the common shadowing across (i.e., for
all) clusters. The variability across clusters around the LNS is given by an additive (in logdomain)
Gaussian distribution with a fixed standard deviation of 3 dB.
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