Wireless Ad Hoc and Sensor Networks

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6Distributed Power Control and RateAdaptation for Wireless Ad Hoc NetworksIn the last chapter, the distributed power control (DPC) scheme wasdemonstrated for cellular networks both analytically and via simulation.Ad hoc wireless networks have gained great importance in recent years.Wireless communication technology has come into wide use with theadvent of the IEEE 802.11 standard. An ad hoc network is a group ofwireless mobile nodes dynamically forming a temporary network withoutany fixed infrastructure or centralized administration. The applicationsfor ad hoc networks have grown tremendously with the increase in theuse of wireless sensor networks. For wireless networks, it was demonstratedthat energy efficiency is an important QoS metric besides throughput,loss rate, and end-to-end delay. Therefore DPC is necessary even forad hoc wireless and sensor networks. The DPC derived for the cellularnetworks is extended to ad hoc wireless networks.In this chapter, DPC scheme from the previous chapter is reviewed anda medium access control (MAC) protocol based on the DPC is introducedfor wireless ad hoc networks (Zawodniok and Jagannathan 2004) in thepresence of radio channel uncertainties such as path loss, shadowing, andRayleigh fading. The DPC quickly estimates the time-varying nature ofthe channel and uses the information to select a suitable transmitter powervalue, even for ad hoc wireless and sensor networks, to maintain a targetsignal-to-interference ratio (SIR) at the receiver. To accommodate the suddenchanges in channel state, a safety factor is incorporated in the powerselection. The standard assumption of a constant interference during alink’s power update used in other research works is relaxed.The performance of the DPC for ad hoc wireless networks can be demonstratedanalytically because it is exactly the same as that of the cellularnetworks. Moreover, the power used for all RTS-CTS-DATA-ACK framesis selected using the proposed DPC; hence, energy savings and modestimprovement in spatial reuse can be achieved. The hidden-terminal problem,which is commonly encountered in ad hoc wireless networks, can beovercome by periodically increasing the power. The NS-2 simulator is233
234 Wireless Ad Hoc and Sensor Networksused to compare the proposed scheme with that of 802.11. The proposedMAC protocol renders significant increase in throughput in the presenceof channel variations compared with 802.11 although consuming lowenergy per bit.6.1 Introduction to DPCThe objectives of transmitter power control include minimizing powerconsumption while increasing the network capacity and prolonging thebattery life of mobile units by managing mutual interference so that eachmobile unit can meet its SIR and other quality of service (QoS) requirements.Rigorous work on DPC was performed for cellular networks (Bambos1998, Dontula and Jagannathan 2004, Jagannathan et al. 2002,Jagannathan et al. 2004, Hashem and Sousa 1998). A few DPC schemes(Park and Sivakumar 2002, Jung and Vaidya 2002, Gomez et al. 2001, Karn1990, Pursley et al. 2000) were developed for wireless ad hoc networkswhere the topology constantly changes because of node mobility andcommunication link failures. Similarly, see Maniezzo et al. (2002), Wooand Culler (2001), Ye et al. (2002), Singh and Raghavendra (1998).Unlike wired networks, radio channel uncertainties in a wireless network,for instance path loss, shadowing, and Rayleigh fading, can attenuatethe power of the transmitted signal causing variations in the receivedSIR and thus degrading the performance of any DPC. Low SIR meanshigh bit error rate (BER), which is unsatisfactory. Reported DPC schemes(Park and Sivakumar 2002, Jung and Vaidya 2002, Gomez et al. 2001, Karn1990, Pursley et al. 2000) for ad hoc networks assume that: (1) only pathloss is present, (2) no other channel uncertainty exists, and (3) the mutualinterference among the users is held constant during power update ofeach user. Moreover, improvement of spatial reuse factor is not adequatelyaddressed. Our previous effort (Jagannathan et al. 2004) was to developnew protocols to accommodate channel uncertainties for cellular networks.No work is currently reported for ad hoc wireless networks thataccommodate channel uncertainties.Furthermore, in an ad hoc network as mentioned in Chapter 1, requestto send (RTS) and clear to send (CTS) messages are used to establish aconnection for data transmission between a transmitter and a receiver.In (Jung and Vaidya 2002, Gomez et al. 2001), authors propose usingmaximum transmitter power only for RTS-CTS, whereas DATA andACK transmission is accomplished at a much lower power. This lowerpower is calculated according to RTS and CTS reception conditions.However, the channel state can change between the RTS and the DATAtransmissions resulting in an inaccurate power selection. On the other hand,
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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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4Admission Controller Design for Hi
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Admission Controller Design for Hig
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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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