CLIENT ASSISTED MINIMUM CONFLICT PAIRS SCHEME
5.2 Minimum Conflict Pairs Scheme
In this section, a client assisted channel assignment scheme is described. Insights obtained from the study on the impact of interference on throughput in the previous section are used in identifying a metric that can give a good indication of the expected throughput. The number of conflict pairs metric is not only intuitive but also simple to determine even in high density networks. Employing this metric, the client assisted MICP A scheme is proposed. In this scheme, each AP maximizes its expected throughput by selecting the channel with the minimum number of conflict pairs.
Before the client assisted channel assignment scheme can be developed, a metric that correlates with the expected throughput across all three interference classes is needed.
Towards this end, the number of conflict pairs, XP, has been identified as a suitable metric. Conflict pairs are defined as two source and destination pairs that cannot transmit in parallel without interfering with each other. In other words, at most only a single transmission can take place among the conflict pairs. A larger number of conflict pairs indicates a higher proportion of source and destination pairs that can be prevented from transmitting simultaneously. On the other hand, a smaller number of conflict pairs means that source and destination pairs that are not blocked have more opportunities to transmit in parallel. Because of this, it is expected that the number of conflict pairs can be used as a good indicator of the expected throughput.
Another advantage of using the number of conflict pairs lies in its simplicity. As will be seen, the number of conflict pairs can be easily determined even for high density networks. To illustrate this, the number of conflict pairs for each interference class is now described using the interference topologies from the previous study. The number of unique source and destination pairs for any two interfering BSSs (BSS 1 and BSS2) is
ncl x ne2. For Class-I, because parallel transmissions are not possible for all topologies, all source and destination pairs are conflict pairs, that is
XP = nclxne2. (5.2.1)
In Class-II, only a single transmission can take place if either all of API 's clients or all of AP2's clients are in region 0. This means that for these topologies, all source and destination pairs are conflict pairs. Therefore the number of conflict pairs for these topologies are the same as those for Class-I, as given in (5.2.1 ). Otherwise, for topologies that have parallel transmissions, the number of conflict pairs is dependent on the number of clients from each AP in region 0. Recall that in Class-fi, clients in region 0 from one AP prevents transmissions from all clients of the other AP. Hence, the number of conflict pairs for Class-II topologies with parallel transmissions can be given as
XP =neal x ne2 + nea2 x ncl- neal x nea2. (5.2.2)
In (5.2.2}, the first term represents the conflict pairs between each of API 's clients in region 0 with all of AP2' clients, the second term represents the conflict pairs between each of AP2's clients in region 0 with all of API 's clients, and the last term accounts tor conflict pairs that appear in both the first and second terms.
Finally, for Class-III, only clients in region 0 can interfere with each other. Therefore, the number of conflict pairs is simply the product of the clients from each BSS that is in region 0, that is
XP =neal x nea2. (5.2.3)
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(a) Class_I_2_1: XP = 9 (b) Class II 2 I: - - - XP= 7
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Figure 5.9: Number of conflict pairs for each interference class.
Fig. 5.9 shows the number of conflict pairs for the topology with nco I = 2 and nco2 ~I
from each of the interference classes.
For the purpose of verifying the relation between the number of conflict pairs and the expected throughput, the throughputs obtained from each of the interference classes are plotted against the number of conflict pairs, as shown in Fig. 5.I 0. For each of the interference classes, it can be seen that the throughput obtained is inversely related to the number of conflict pairs. In other words, higher throughputs can be achieved by selecting topologies that have a lower number of conflict pairs.
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Number of Conflict Pairs
Figure 5.10: Relation between the number of conflict pairs and throughput for all interference classes.
Therefore, in the MICPA scheme, each AP-i maximizes its expected throughput by choosing the channel dmin that has the minimum number of conflict pairs, as given by
dmin (i) = arg min X~ ( i) .
dEC (5.2.4)
The MICPA scheme, which is run at each AP, can be described as follows:
Algorithm 9: MICP A
1) The AP performs its own measurements by sensing the presence of interfering APs and their clients.
2) The AP broadcasts the interference information (which is the collated measurements from the AP and all clients in the previous iteration) to all of its clients periodically and requests them to perform similar measurements at specified intervals.
3) The clients perform the measurements and report back to the AP.
4) The AP combines and uses this information to determine the channel with the minimum number of conflict pairs. If a new channel is found, it switches into that channel. Otherwise, it stays on its current channel.
5) Steps 1 - 4 are repeated at specific intervals.
Overheads incurred by the transmission of measurement reports from clients are an important factor that needs to be considered. To minimize the number of measurements that needs to be transmitted to the AP, the AP broadcasts the updated interference information that it and its clients have sensed. Now the clients compare this information with its measurements and only feedback measurements that are different to those of the AP. This reduces the amount of information that needs to be relayed back to the AP, ensuring that any overheads incurred are only for the transmissions of useful information. Furthermore, since the location of APs and its clients is usually constant in a short period of time, most clients will not need to send reports at every interval.
On the other hand, APs can also over time identify and only request measurements from clients that are located farther from themselves. These clients have a higher probability of sensing interference that is uncorrelated to the AP. Finally, to further
minimize overheads, the interference information that needs to be broadcasted can be appended to beacon frames that are already transmitted by APs periodically.