Wireless Ad Hoc and Sensor Networks

Adaptive and Probabilistic Power Control Scheme 479100Minimum distance of 9 metersPercentage of time achieving desired range9080706050403020PPC beta (0.1, 0.1)10PPC beta (2, 2)DAPC05 10 15 30 45 60Number of readers in the networkFIGURE 10.7Percentage of time the desired range is achieved with number of readers.overcomes the interference produced, thereby achieving the desiredrange. In contrast, Beta(0.1, 0.1) has a 30% probability of being off; therefore,the probability of attaining the desired range will be low.In Figure 10.8, considering the average detection range for the samescenario, the DAPC converges to the 2 m desired range and outperformsboth PPC algorithms. We can also observe the average power level usedfor each algorithm in Figure 10.9. As the mean for both Beta(2, 2) andBeta(0.1, 0.1) is 0.5, the average reader output power stays at 500 mW,which is half of the maximum power. Meanwhile, DAPC is able to dynamicallyadjust its output power to find the optimal level for which thedesired range can be achieved as the size of the network varies.Performance of the power control schemes in denser networks is nowanalyzed. For network with a minimum distance of 6 m, the desired rangeis not attainable by all readers as the transmission power is not able toovercome the interference, forcing the yielding strategy of each algorithmto test. The detection range and percentile vs. number of readers arepresented in Figure 10.10 and Figure 10.11 respectively. As the number ofreaders increases, the overall interference in the network will also increase.Consequently, the percentage of time r a reader attains its desired rangewill drop, as shown in Figure 10.10. It is observed that PPC withBeta(0.1, 0.1) offers the best performance in terms of r. This is because on