Wireless Ad Hoc and Sensor Networks

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Distributed Power Control and Rate Adaptation 255mainly on maximizing the throughput, regardless of transmission power,channel state, and network congestion. For instance, the auto rate fallback(ARF) (Kamerman and Monteban 1997) protocol incrementally alters thetransmission rate after experiencing a number of consecutive correct orerroneous packet receptions. As a result, ARF slowly converges to themore appropriate rate dropping significant number of packets because oflow signal-to-noise ratio (SNR) or SIR. In some cases, transmission rateis much lower than acceptable reducing the throughput. By contrast, theRBAR protocol proposed in (Holland et al. 2001) uses the predefined lowerand upper SNR thresholds to select an appropriate modulation schemeand hence the rate. By using the measured SNR value from the previousMAC frame, a more suitable modulation scheme is selected using SNRthresholds. However, the channel measurements used to select a givenrate are from the previous transmission, and they do not accuratelydescribe the channel state for the subsequent transmission. A commonproblem that is found in both ARF and RBAR, and with many availableprotocols, is the transmission of data at the maximum power reducingenergy efficiency. Additionally, the protocols (Holland et al. 2001, Kamermanand Monteban 1997) ignore the effect of congestion on throughputand energy efficiency.A more appropriate energy-efficient rate adaptation would be to useseveral modulation schemes and dynamically selecting a suitable oneonline, based on the channel state and the network traffic. The basicconcept was analyzed in Schurgers et al. (2001) and proved to be effective.Relevant parameters for the selection of the modulation scheme includebit-error-rate (BER) and SNR. The former indicates the probability of erroroccurrence during transmission for a given SNR. The latter defines thereceived signal quality. Hence, for a given modulation scheme, a thresholdSNR can be calculated according to a desired BER level. In general, forsmall target BER (low level of errors) a high SNR is typically required.The heuristic rate adaptation protocol from (Zawodniok and Jagannathan2005) uses the DPC scheme (Zawodniok and Jagannathan 2004) to predictthe channel state and to meet the target SNR. Thus, this scheme can selecta more appropriate rate when compared to available protocols (Hollandet al. 2001, Kamerman and Monteban 1997). In addition, DPC in rateadaptation reduces energy consumption by selecting a minimal powerneeded for successful transmission. Additionally, this scheme selects awide range of suitable rates by taking into account the demandedthroughput and the energy efficiency to accommodate the networkcongestion and to conserve energy through the selection of a backoff interval.The protocol from Zawodniok and Jagannathan (2005) uses the backoffmechanism to mitigate the impact of congestion. As a result, packet forwardingis prevented either if the next-hop node cannot buffer them or thechannel state is not conducive. Under such circumstances, the maximum
256 Wireless Ad Hoc and Sensor Networkspossible rate will be selected in the case of high congestion to free thechannel quicker. In short, the proposed protocol maximizes throughput andsaves energy by both modifying the transmission power and selecting anappropriate rate while minimizing the packet losses in the case of congestion.Thus, the inclusion of DPC in rate adaptation is extremely importantto assess the channel state to select a suitable rate and transmission power.The second scheme from Zawodniok and Jagannathan (2006) is basedon dynamic programming (DP) principle (Bertsekas 1987, Angel and Bellman1972, White 1969, Bambos and Kandukuri 2000), which utilizes aburst mode transmission to control incoming flow rate by varying admissibleburst size. This method of flow control is more precise than a backoffscheme used in the heuristic protocol, because it can specify an exactamount of data that will be transmitted to the receiver. In consequence,queue utilization can be maintained close to the target value. Moreover,the usage of burst mode transmission increases overall network efficiency,thus providing higher data rates for the end users. The IEEE 802.11 burstmode transmits a number of data packets within a single RTS/CTS/DATA/ACK exchange thereby reducing the number of transmitted RTS/CTS frames and minimizing an associated bit overhead. In the IEEE 802.11,a burst size is limited by the modulation rate because of the way the timeof a single RTS/CTS/DATA/ACK exchange is selected.The second rate adaptation scheme is an improvement of the powercontrolled multiple access (PCMA) protocol (Bambos and Kandukuri2000). The proposed algorithm minimizes energy consumption while providingrequired the QoS. This scheme, in contrast to the heuristic one, canprovide the desired level of service by selecting the appropriate targetqueue utilization. Maximizing throughput normally reduces the lifetimeof the node, overall network, and throughput while increasing congestionlevels. Therefore, a suitable outgoing rate has to be identified so that anoptimal trade-off results between the increasing modulation rate to maximizethroughput and the decreasing modulation rate to maximize energyefficiency.A quadratic cost function is introduced to obtain this trade-offbetween throughput and energy-efficiency. The analytical solution, whichis derived using a dynamic programming (Bertsekas 1987) approach, providesa performance guarantee, unlike the simplified heuristic scheme,where the performance of the rate adaptation scheme is not guaranteed.The DP-based scheme eliminates packet losses due to buffer overflows,which will result in energy efficiency due to reduced retransmissions.6.7.1 Rate AdaptationA given application requires that a BER is maintained below a certain level.For wireless networks, the BER translates into a minimum SNR for whichthe packet is considered to be successfully decoded. The relation between
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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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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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