Digital Signal Processing Reference
In-Depth Information
Fig. 7.8
A centralized topology: 802.11 Access Points form a hexagonal grid. 802.11 User Equip-
ments are distributed randomly according to a spatial Poisson process. The UEs are associated with
the nearest access point
In Fig.
7.9
, we present a comparison between SB and SL. Results are averaged
over 100 seeds, using the topology of Fig.
7.8
. We can see that our new
T
CS
defi-
nition, based on
P
r
, significantly increases throughput. The definition based on
T
Rx
does not provide a lot of differentiation among the different states. This can be seen
by the fact that SL cannot improve over SB using these states and by the fact that it
reduces the transmission power significantly for these states. However the introduc-
tion of the new states also causes more unfairness in the network as terminals are
less inclined to listen to each other and hidden terminals become more prominent.
By allowing the nodes to scale down power, SL compensates for this and reaches
the same levels of fairness
1
as the
T
Rx
-states. Most importantly, SL is shown to
outperform SB by 33% in throughput using the
P
r
-based states.
The impact of heuristics on the convergence of SL is illustrated in Fig.
7.10
.
Again, the topology of Fig.
7.8
is used and averaged over 100 seeds. It can be clearly
seen that the use of domain knowledge in the form of heuristics results in a signifi-
cant increase in convergence speed.
To demonstrate the interoperability of SL, we show the performance of SL in
a legacy 802.11 network in Fig.
7.11
. As most of the current commercial 802.11
cards support some kind of ARF, we have implemented this for the legacy 802.11
1
We use Jain's Fairness Index as an indicator for fairness. This index is calculated as follows:
f
=
(
i
=
1
S
i
)
2
n
i
=
1
S
i
[40].
