1. Hierarchical Cell Structure System for MBMS in UMTS Networks
Alexandra Boal1
, Rui Salomé1
, Américo Correia1,2
ADETTI1
, Av. Forças Armadas, Edifício ISCTE, Lisbon, Portugal
Instituto de Telecomunicações2
, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
Phone: +351-217903292, e-mail: americo.correia@iscte.pt
Abstract1
— To support the great demand of wireless
bandwidth resource in the future, a high density microcell
structure will be adopted. Among radio technologies, multiple-
input multiple-output (MIMO) systems have attracted wide
research interests in recent years. It is widely recognized that
MIMO systems can be employed for achieving a high capacity
and a high diversity order, for mitigating the effects of various
types of interfering signals, and for supporting space-division
multiple-access (SDMA). In this study a MIMO assisted cellular
system using distributed antennas is proposed and investigated,
where a big number of antennas are distributed in the area
covered by the system. The proposed system is capable of
providing a platform for possibly integrating the conventional
cellular systems into the future advanced, high-flexibility, ad-
hoc and cooperative wireless networks. This system is
considered for MBMS (Multimedia Broadcast Multicast Service)
that enables mobile operators to deliver rich multimedia to a
huge number of subscribers by broadcasting over the radio
frequencies assigned to WCDMA.
I. INTRODUCTION
The MBMS is an unidirectional Point to Multipoint (PtM)
service for delivering high bit rate multimedia services to a
large number of mobile users. There are two modes of
operation: multicast and broadcast.
In a radio communication system, MIMO refers to links for
which the transmitting end as well as the receiving end is
equipped with multiple antenna elements. The idea behind
MIMO is that the signals on the transmit antennas at one end
and the receive antennas at the other end are “combined” in
such a way that the quality (Bit-Error Rate or Block Error
Rate - BER/BLER) or the data rate (bits/sec) of the
communication for each MIMO user will be improved.
In this study we integrated the MIMO principles into the
hierarchical cell structure system using distributed antenna.
The idea of Hierarchical Cell Structure (HCS) has been used
in several wireless access technologies, including GSM and
UMTS systems. Using this feature improves the network
capability to achieve better routing/management, and to
enhance the utilization of the network resources by the
operators.
It is well-known that, in conventional cellular systems [1],
each cell is centered around a Node-B, which may employ a
set of antennas. By contrast, in the proposed cellular system,
each cell has numerous sets of antennas (distributed
This work is co-funded by the European Commission under the framework
of IST-2005 27423 Project, C-MOBILE – Advanced MBMS for the Future
Mobile World.
antennas), which are distributed within the area covered by a
cell and connected to the Node-B using fiber or cable.
In the proposed topology, the distributed antennas (DAs)
are connected with a number of signal processing centers,
which are referred to as base stations (BSs), using optical
fibers or cables. Here we still use the concept of BS,
however, it is now just a signal processing center, which may
be converted from a conventional BS. The antennas at the BS
of the proposed system have no priority in comparison with
the other distributed antennas. The BS is responsible for the
signal processing of the users within the area, which is
covered by the distributed antennas connected with this BS.
This paper is organized as follows. Section II describes the
Hierarchical Cell Structure System using distributed
antennas, namely the system description and the typical
characteristics. Section III describes the simulation aspects
and Section IV shows the simulation results and contains a
discussion of those results. Finally the Section V contains a
brief conclusion of the subjects discussed in the previous
sections.
II. HIERARCHICAL CELL STRUCTURE SYSTEM
A. System Description
The novel concept of the proposed system using distributed
antennas can be well described with the aid of Figure 1.
Fig. 1. A conceptual cellular system structure with DAs.
In the proposed system (Figure 1), the antennas near the
borders may be connected with two or three Node-Bs. In
more details, each of the antennas within the dash-dotted box
are connected with Node-B of Cell 1 and Node-B of Cell 2,

2. respectively, while the antennas within the dashed circle at
the conner jointing Cells 1, 2 and 3 are all connected with
respective Node-B of these cells.
In the considered system, for the convenience of analysis,
we assume that the cells are shaped as hexagons with the
common radius of R. As shown in Figure 1, we assume that
any pair of adjacent antennas are separated by a distance of r
(in this study we assumed that r = 250m and R=1000m).
Hence, each antenna is surrounded by numerous DAs located
at the layered hexagons. Note that, the structure of Figure 1 is
sufficiently general for approximately modeling HCS
systems using distributed antennas that may have an arbitrary
antenna density. This can be done by appropriately changing
the radius value of R in Figure 1.
In this system, we assume that the DAs only implement the
functions of conveying a signal from radio frequency (RF) to
baseband or from baseband to RF, in order to make the
computation burden at a DA as low as possible. Hence, in
our DA are conveyed to the BSs, where the processing is
carried out. Simultaneously, all the DAs are also used for
transmitting signals from the Node-Bs to the mobile
terminals (MTs), in order to improve the DL transmission
quality.
B. Typical Characteristics
The objectives of DAs in wireless systems include the
increase of the system capacity, to decrease the transmission
power, to reduce the dependence on the centralized control
and to redeem the system capacity spent for system
configuration in conventional cellular systems. In more
details, in comparison to the conventional cellular CDMA
systems, the distributed antenna cellular systems have the
following typical characteristics:
• In HCS system using DAs, the system capacity can be
extremely higher than that of the conventional 3rd
generation (3G) cellular systems, as well as that of the
possible cellular systems built on the conventional
cellular concepts [2, 3, 4].
• A distributed antenna aided cellular system is a high
power-efficiency wireless system. In HCS system using
DAs, each MT can be viewed as the center of a “virtual
cell” and it communicates only with the antennas within
its virtual cell. Due to the fact of short distances between
a MT and the antennas around it, and the fact of
relatively low transmission path-loss, satisfactory
transmission power is possible in DA cellular systems,
even in the case of transmitting a high data rate that can
be supported by integrating the MIMO principles into
the HCS system using DAs [1, 5].
• In HCS system using DAs, the demand on power control
can be relieved, or even use no power control at all. No
matter where a MT is, it communicates with a number of
antennas located within the LoS area of the considered
MT or within its virtual cell. Hence, the signals sampled
from the antennas in the virtual cell fall within the
cluster of strongest signal. In more detail, as shown in
Figure 1, the received power by antennas DA1, DA2 and
DA3 from MT D will be usually higher than that from
the other MTs or at least they are on a similar level.
• Handover in HCS system using DAs is simply
geometrically based and its principles can be readily
understood with referring to Figure 1[1]. Specifically, in
HCS system using DAs, the antennas near the borders
may be connected with two or three BSs.
• In HCS systems using DAs, signal processing is location
dependent, since a MT is only related to a number of
antennas within its virtual cell. The signals in
correspondence to a specific MT will become
sufficiently weak at a location sufficiently away from the
MT.
III. SIMULATION ASPECTS
In our simulations, we study two different topologies:
Macrocell Topology and HCS Topology using DAs.
The chosen tool to develop the simulator at the system
level was JAVA, due to the fact of being a multi-platform
technology and independent of any other simulation tool.
For the Urban Macrocell Topology, 18 tri-sectorial base
stations with a site to site distance of 1000m were
considered. For the HCS Topology using DAs, were
considered 18 tri-sectorial base stations with a site to site
distance of 1000m, and some DAs with a site to site of 250m.
The location of DAs was obtained by cell splitting twice with
radius R/2. The following figure shows the Macrocell
Topology (left) and the HCS Topology (right).
Fig. 2. Macrocell (left) and HCS (right) topologies.
Table I presents some of the parameters used in both
simulated scenarios.
Table I
Macrocell and HCS Topologies Parameters
We assumed that the base station total transmission power

3. is 20W (43dBm). The expected total transmission power of
each distributed antenna is about 22dBm based on the
considered factor of attenuation of the transmitted power of
the cellular system (Cost 231) β=3.5, so:
128/1)4/1()/()/( 5.35.3
2121 === DDDD β
(1)
dBmdBW
W
228
128
20
⇒−⇒ (2)
IV. SIMULATION RESULTS
The link performance of the FACH channel is obtained for
a chosen geometry factor (G) in terms of BLER vs Ec/Ior.
This indicates the fraction of power that must be allocated to
PtM MBMS transmissions to meet a specific target BLER at
a receiver experiencing a determined geometry factor, i.e. for
the worst case user to experience no worse than the target
BLER.
The geometry factor is given by the relationship between
the own cell interference experienced by the mobile user and
the interference from neighboring cells plus the White
Gaussian Noise. A lower geometry factor is expected when
user is located at the cell edge (the case where the
interference received from the neighboring cells is higher
than the interference experienced in its own cell), this way a
relationship between the fraction of power allocated for the
PtM transmission and the verified geometry factor can be
made in a order where when the geometry factor decreases
the corresponding Ec/Ior for a given BLER increases being
necessary a higher transmitted PtM power to maintain the
desired coverage.
Figure 4 shows the Cumulative Distribution Function
(CDF) of geometry factors (most relevant range of value)
obtained for the Macrocell and HCS environments. These
simulations were made by populating the simulated topology
in a random way, where the mobile users (Vehicular A case)
at a speed of 3km/h were moving randomly across the
topology and considering Rb=128kbps. For each of the users
it was calculated the geometry factor at the different positions
they were moving.
Fig. 4. CDF Geometry Macro and HCS cells.
Observing Figure 4, we notice that for the Macrocell
environment about 95% of the users experience a geometry
factor of -5.5dB or better and about 80% of the users
experienced geometry of -3dB or better. In the case of the
HCS topology we can observe that 95% of the users had
geometry of -5.25dB or better and about 80% had a geometry
factor of -2.75dB or better.
Notice that the HCS scenario is a more benign environment
due to the fact that better geometry distributions were
obtained in this environment. This is essentially due to the
fact that in this scenario there is less interference due to
inherent macro diversity combining.
Figure 5 presents the BLER versus the fraction of the total
transmitted power with a single spreading code with SF=16.
The S-CCPCH bit rates are 128kbps, 256kbps and 384kbps
using SISO 1x1, MIMO 2x2 and MIMO 3x3, respectively,
for dBG 3−= .
Fig. 5. BLER vs Ec/Ior for SISO (1x1), MIMO (2x2) and
MIMO (3x3).
The results obtained (coverage and throughput) are
presented along this document for a service BLER of 1%, for
both scenarios and for two of the 3GPP referred multipath
channel models, namely Vehicular A and Pedestrian B.
A Vehicular A
In Figure 6 is illustrated the average coverage vs the Ec/Ior
for Vehicular A at a speed of 3km/h, and both for Macrocell
Topology and HCS Topology.
Fig. 6. Average Coverage vs Ec/Ior, Vehicular A.
As we can see in Figure 6, the results of the HCS
Topology are better than the results obtained for the
Macrocell Topology.
We can see that for the required BLER of 1%, for HCS
Topology and coverage of about 95%, the necessary fraction
of transmitted power is about 85% (1x1), 48% (2x2) and

4. 30% (3x3) of the total available power on the cell and for a
coverage of 80% the minimum fraction should be about 44%
(1x1), 30% (2x2) and 20% (3x3), for the case of Vehicular A
scenario. For the Macrocell Topology and coverage of about
95% the necessary fraction of transmitted power is about
77% of the total available power on the cell and for coverage
of 80% the minimum fraction should be about 49%. Notice
that in the latter topology there is no macro diversity
combining scheme.
In Figure 7 is Error! Reference source not found.shown
the average user received throughput for Vehicular A, at a
speed of 3km/h, for both scenarios.
Fig. 7. Average Throughput vs Ec/Ior, Vehicular A.
We can see that bit rates of 256kbps and 384kbps can be
achievable for multicast/broadcast services in HCS
environment (2x2 and 3x3), however the same doesn't
happen with the Macrocell environment and HCS
environment (1x1), where the bit rate of 128kbps can only be
achievable requiring high power transmission.
B. Pedestrian B
In Figure 8 is illustrated the average coverage vs the Ec/Ior
for Pedestrian B at a speed of 3km/h, and both for Macrocell
Topology and HCS Topology.
Fig. 8. Average Coverage vs Ec/Ior, Pedestrian B.
As we can see in Figure 8, the results of both topologies
considering Pedestrian B are better than considering
Vehicular A.
We also conclude that HCS Topology has a better
coverage than the Macrocell Topology.
In Figure 9 is shown the average user received throughput
for Pedestrian B, at a speed of 3km/h, for both scenarios.
Fig. 9. Average Throughput vs Ec/Ior, Pedestrian B.
We also can see that high bit rates can be easily achieved
for multicast/broadcast services in HCS Topology (1x1, 2x2,
3x3), however the same doesn’t happen with the Macrocell
topology. For the same fraction of total transmitted power the
average throughput with Pedestrian B channel is higher than
in the case of Vehicular A.
V. CONCLUSIONS
From the above presented results, it was demonstrated that
high bit rates could be supported by the HCS Topology using
distributed antennas, especially at the cell borders. The use of
this topology increased the system capacity, decreased the
transmission power, reduced the dependence on the
centralized control and offered an almost uniform
distribution of capacity throughout all area. The last feature is
very important for broadcast/multicast services.
As expected the HCS Topology using distributed antennas
and MIMO is the environment that provides better
performance results compared to the macrocell topology
using SISO, the “reference” environment.
With this study we conclude that MIMO/HCS is a key
technology in modern digital communication to provide
substantial capacity increments not only for unicast services
but also for broadcast/multicast services.
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