Wireless Ad Hoc and Sensor Networks

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Distributed Power Control of Wireless Cellular and Peer-to-Peer Networks 1976Total power of all nodes54Total power321Node 1Node 2Node 3Node 4Node 5Node 6Node 7Node 8Node 9Node 10Node 1100 200 400 600 800 1000Time units1200 14001600 1800FIGURE 5.12Response of Bambos DPC scheme.transmitter/receivers were considered to be requesting admission into thenetwork, one at a time, at predefined intervals of time. The network isthen simulated, and the SIRs computed using various schemes discussedin the chapter and are plotted as shown in Figure 5.12, Figure 5.13, andFigure 5.14. From these figures, we can observe that the SSCD andoptimal control schemes help the new links to attain target SIR in afewer number of iterations when compared to Bambos. But the totalpower from each of these schemes, plotted at every time instant, showsthat Bambos’ scheme consumes slightly less power when comparedwith our schemes (see Figure 5.15). By varying the gains k 1 and k 2 , wecan allow the new links in the network to attain target SIR using lesspower with SSCD and optimal schemes compared to Bambos. But thenumber of iterations needed for convergence would be more. Therefore,there is a trade-off between the convergence speed and total powerconsumed in all the schemes discussed in this paper in peer-to-peercase. In other words, the selection of k i and the weight matrices Q i andT i affect the power and convergence. This option is not available in thework of Bambos.Further, within the proposed suite of DPC/ALP schemes, the simulationsshow that the total power of all the transmitters with the optimalDPC scheme (see Figure 5.16) is quite small compared to using SSCD
198 Wireless Ad Hoc and Sensor Networks6Plot for SIR vs time units54SIR321Node 1Node 2Node 3Node 4Node 5Node 6Node 7Node 8Node 9Node 10Node 1100 200 400 600 800 1000Time units1200 1400 16001800FIGURE 5.13Response of SSCD scheme.5Plot for SIR vs time unitsSIR4.543.532.521.510.5Node 1Node 2Node 3Node 4Node 5Node 6Node 7Node 8Node 9Node 10Node 1100 200 400 600 800 1000Time units1200 1400 1600 1800FIGURE 5.14Response of optimal DPC.
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Wireless Ad Hocand SensorNetworksPr
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18. Chaos in Automatic Control, edi
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CRC PressTaylor & Francis Group6000
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Table of Contents1 Background on Ne
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3 Congestion Control in ATM Network
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5.4.2 Distributed Power Controller
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7.3 Adaptive and Distributed Fair S
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9.2.2 Overview.....................
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the number of connections in each l
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y Maheswaran Thiagarajan, and tirel
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2 Wireless Ad Hoc and Sensor Networ
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10 Wireless Ad Hoc and Sensor Netwo
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2BackgroundIn this chapter, we prov
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Background 51u(k)x n (k + 1)x n (k)
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Background 53with x( 0)being the in
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Background 55with tr(.) the matrix
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Background 57nGiven a function ft (
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Background 592.3.2 Lyapunov Stabili
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Background 61as well as Jagannathan
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Background 63The subsequent example
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Background 65Evaluating this along
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Background 67Now, select the feedba
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Background 69is SISL if and only if
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Background 71L 1 (x)L(x, t)L 0 (x)0
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Background 73for some R > 0 such th
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Background 75Evaluating the first d
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Background 77Section 2.4Problem 2.4
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7Distributed Fair Scheduling in Wir
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Distributed Fair Scheduling in Wire
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8Optimized Energy and Delay-Based R
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Optimized Energy and Delay-Based Ro
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9Predictive Congestion Control for
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Predictive Congestion Control for W
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10Adaptive and Probabilistic Power
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Adaptive and Probabilistic Power Co
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Wireless Ad Hoc and Sensor Networks

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