Wireless Ad Hoc and Sensor Networks

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Distributed Power Control and Rate Adaptation 265TABLE 6.1Power Thresholds for Selecting the MostEnergy-Efficient RateSNR[dB]SNRRate[Mbps]Upper Thresholds ofTx Power [mW]10 10.00 1 > 20.0914 25.12 2 20.0922 158.49 4 10.6428 630.96 6 1.4932 1584.89 8 0.30REMARK 3The power threshold given by Equation 6.33 depends upon DPC calculationsfor the lowest supported rate. The power thresholds can be calculatedin advance, reducing online calculation overhead of the protocol.Table 6.1 presents the thresholds calculated for a set of five rates used inthe simulations. For example, if the transmission power calculated by theDPC algorithm is equal to 15 mW, 2 Mbps is the most energy efficientrate, because 15 mW belongs to a set defined between 20.09 mW (2 Mb)and 10.64 mW (4 Mbps).6.8.5 Modulation Rate to Overcome CongestionIn the previous subsections, the maximum throughput and energyefficientrates were calculated. The throughput increases with rate; however,the lower the rate used, larger the number of bits that can be transmittedper joule. Therefore, the rate adaptation has to generate a trade-off betweenthe throughput and energy-efficiency. Hence, the selection of a modulationscheme that results in the best throughput while satisfying the energyconstraint is discussed next. Moreover, in the proposed protocol, the bufferutilization at the transmitter is used as an indication of the requiredthroughput, and will impact the rate selection method.Because a high transmission rate implies high buffer occupancy at thereceiving node, provided the channel is conducive, the buffer occupancyat each node should be taken into consideration during rate adaptation.The basic idea is presented in Figure 6.16. Here the lowest supported rateis selected when the queue at the transmitting node has low utilization.Increased queue occupancy at this node indicates a higher traffic demand.Hence, the modulation rate that results in higher throughput is selected.This rate adaptation based on buffer occupancy can be explained as follows.The lowest supported rate will be chosen if the congestion is low. As thecongestion in the network increases, the queue occupancy will increase. Consequently,a higher rate will be selected to clear the congestion, rendering a
266 Wireless Ad Hoc and Sensor NetworksRate selection based on queue utilizationModulation rate8 Mbps6 Mbps4 Mbps2 Mbps1 Mpbs0.5 0.6 0.7 0.8 0.9 1Normalized queue utilizationFIGURE 6.16Rate selection as a function of queue utilization.higher throughput in contrary to the belief that increased congestion levelsshould be controlled by decreasing transmission. As the congestion decreases,the lower rate will be selected resulting in higher energy efficiency.6.8.6 Power Selection for the RateThe DPC algorithm calculates the transmission power only for the lowestsupported rate. In the case of proposed rate adaptation scheme, the necessarypower has to be selected to reflect the used rate. Hence, an appropriatetransmission power for a given rate is calculated as follows.THEOREM 6.8.2 (POWER CONTROL WITH RATE ADAPTATION)Given the lower and upper threshold values of SNR for a given rate, and theinformation for the lowest supported rate through DPC, the transmission powerfor the proposed energy-efficient rate adaptation scheme is given byPt () t = Pt () t ∗ SNR / SNRk 0 k 0(6.34)where SNR 0 is the target SNR for the lowest supported rate, SNR k is thetarget SNR for the k th modulation scheme, Pt0( t)is the estimated powervalue for the lowest supported rate, and Ptk( t)is the power value for thekth modulation scheme. Moreover, the error in estimation of power isbounded.
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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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100 Wireless Ad Hoc and Sensor Netw
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4Admission Controller Design for Hi
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Admission Controller Design for Hig
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Page 326 and 327: 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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