Wireless Ad Hoc and Sensor Networks

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Distributed Power Control of Wireless Cellular and Peer-to-Peer Networks 211400Plot of average admission delay vs arrival rate350Average admission delay300250200150100500 0.005 0.01 0.015 0.02 0.025 0.03Arrival rate of links/iterationFIGURE 5.24Average admission delay with arrivals.6Plot of average dropped links vs arrival rate5Average dropped links432100 0.005 0.01 0.015 0.02 0.025 0.03Arrival rate of links/iterationFIGURE 5.25Average dropped links with arrivals.
212 Wireless Ad Hoc and Sensor Networksaverage admission delay and dropped links on the arrival rate. As arrivalrate of the users increases, interference in the network increases. Thepower control scheme would take more time to assign reasonable powerlevels for the large number of admission-seeking users. Some nodes dueto this reason may not reach their target SIRs in the predefined admissiontime assigned; hence, they drop out. Therefore, as arrival rate of the usersin the network increases, the admission delay and average number ofdropped links increase.5.4 Distributed Power Control in the Presenceof Fading ChannelsEarlier DPC works (Bambos 2000, Jantti and Kim 2000, Jagannathan et al.2002, Dontula and Jagannathan 2004) presented in Section 5.2 neglect thechanges observed in the radio channel. In fact, they all assume: (1) onlythe path loss component is present, (2) no other uncertainty exists in thechannel, and (3) the interference is held constant. Consequently, the convergencespeed of these algorithms and the associated power updates areof an issue in a highly dynamic wireless environment in which usermobility is quite common, and shadowing and Rayleigh fading effects aretypically observed in the channel. The proposed work in this sectionovercomes these limitations.In this section, we present a novel DPC scheme (Jagannathan et al. 2006)for the next generation wireless networks with channel uncertainties. Thisalgorithm estimates the variations in the slowly varying channel, and it issubsequently used in the power update so that a desired SIR is maintained.This algorithm, being highly distributive in nature, does not require interlinkcommunication, centralized computation, and reciprocity assumptionas required in a centrally controlled wireless environment. In addition, themodified DPC scheme (Jagannathan et al. 2006) converges faster comparedto the other schemes in the presence of channel uncertainties. As the necessityof interlink communication is eliminated, network capacity increases,and easy controlled recovery from error events is possible.5.4.1 Radio Channel UncertaintiesThe radio channel places fundamental limitations on wireless communicationsystems. The path between the transmitter and the receiver canvary from simple line-of-sight to one that is severely obstructed by buildings,mountains, and foliage. Unlike wired channels that are stationaryand predictable, radio channels involve many uncertain factors, so they
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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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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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