10-06-2013, 04:03 PM
On Cell Breathing in CDMA Network
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Abstract
The objective of this paper is to provide an
assessment of the advantages that cell breathing may give in
optimal management of CDMA network capacity. The paper
studies the capabilities of cell breathing and is primarily
intended to determine whether there are any deploymant
and/or traffic scenarios where the breathing algorithm can be
used to improve capacity in high traffic cells by redirecting
mobiles to surrounding cells.
Introduction
A large number of IS95 based CDMA networks have been
deployed in recent years. A great deal of work has been done
over the last few years to study optimal CDMA cell design in
order to minimize the number of cell sites required while
maintaining the grade of service [2]-[6]. These studies
concentrate on maximizing the cell radius for a giken
maximum transmit power while meeting the grade of service
in a specified percentage of the cell area, under uniform
distribution of traffic in each cell. In this paper, we study the
impact of non uniform distribution of traffic in different cells
on cellular network performance. Specifically, we are
interested in evaluating the performance gain achievable
through cell breathing. Cell breathing is a mechanism that
attempts to keep the forward and reverse link handoff
boundaries balanced by changing the forward link coverage
according to the changes in the reverse link interference levd.
Overview of Soft Wandoff Process
As discussed in [l], in IS95 CDMA systems the mobile
measures the ]pilot E, /Io from neighboring cell sites. If a pilot
is found whose E, /Iq is above a threshold called T-ADD, the
mobile reports that pilot to the base station to be included in
the set of pilots in soft handoff referred to as the active set.
On the other hand, if the Eci /Z0 of a pilot in the active set is
below a threshold called T-DROP for more than a certain
time, the mobile will report that pilot to the base station so that
it may be removed from the active set. Therefore, the handoff
region is primarily determined by the pilot Ec /Zo values as
measured by the mobile. Figure 1 shows the handoff boundary
of two adjaceint cell sites marked as A and B. Since Zo=Zo~+
Z,B +No, where Zoi is the power spectral density of the total
signal received from cell site i at the mobile and No is the
thermal noise power spectral density, then we get Zo ;ZA,
near the edge of soft handoff region closer to cell site A.
Impact of Breathing on Forward Link Performance
On the forward link, it is generally believed that once a
given cell becomes heavily loaded then the breathing
algorithm will reduce the cell’s coverage thereby shedding
some of the traffic to the surrounding cells relieving the
overloaded cell. Shedding of traffic from the heavily loaded
cell occurs because as discussed in Section 2, the soft handoff
region on the side of the cell with less loading shrinks. As a
result, some of the mobiles in the lightly loaded cell which
were in soft handoff with the heavily loaded cell will now go
out of soft handoff with the heavily loaded cell. This releases
some of the radio links from the heavily loaded cell that
serviced the users in soft handoff from the neighboring cells.
The released radio links can be used to support new users in
the heavily loaded cell. The question is how much capacity
increase may be expected in the heavily loaded cell and what
the impact will be to the overall call quality
Conclusion
The impact of cell breathing on the coverage of CDMA
cells was studied. It was shown that the main impact of cell
breathing is reduced soft handoff region. There is almost one
dB reduction in soft handoff region for each dB of breathing
attenuation. Therefore, if cell breathing is used to distribute
traffic in certain deploymenthraffic scenarios, the impact of
the reduced soft handoff region on call quality needs to be
assessed. It was shown that under very specific deployment
conditions whlere one cell is heavily loaded and is surrounded
by lightly loaded cells, cell breathing may provide a small
increase in capacity. This capacity gain may, however, be at
some call quality cost. In order to minimize impact to call
quality, the aimount of breathing attenuation must be limited
and controlled carefully. Given that the above deployment
scenario is not generally realistic, cell breathing does not
provide much advantage from a capacity point of view.