Transmission power control in MAC protocols for wireless sensor networks

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TRANSMISSION POWER CONTROL IN

MAC PROTOCOLS FOR WIRELESS

SENSOR NETWORKS

RT.DCC.011/2005

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LUIZ H.A. CORREIA DANIEL F. MACEDO DANIEL A.C. SILVA

ALDRI L. DOS SANTOS ANTÔNIO A.F. LOUREIRO

JOSÉ MARCOS S. NOGUEIRA

JUNHO 2005�

UFMG - ICEX DEPARTAMENTO DE CIÊNCIA DA C O M P U T A Ç Ã O

UNIVERSIDADE FEDERAL DE MINAS GERAIS

Transmission Power Control in MAC Protocols for Wireless SensorNetworks

Luiz H. A. Correia, Daniel F. Macedo, Daniel A. C. SilvaAldri L. dos Santos, Antonio A. F. Loureiro, Jose Marcos S. Nogueira ∗

Abstract

Medium access control (MAC) protocols manage energy consumption on the network element dur-ing communication, which is the most energy-consuming event on Wireless Sensor Networks (WSNs).One method to mitigate energy consumption is to adjust transmission power. This paper presents twoapproaches to adjust transmission power in WSNs. The first approach employs dynamic adjustmentsby exchange of information among nodes, and the second one calculates the ideal transmission poweraccording to signal attenuation in the link. The algorithms proposed were implemented and evaluatedwith experiments, comparing their results with B-MAC, the standard MAC protocol in the Mica Motes2 platform. Results show that transmission power control is an effective method to decrease energy con-sumption, and incurs in a negligible loss in packet delivery rates. For node distances of 5m, the proposedtransmission power control techniques decrease energy consumption by 27% over B-MAC.

1. Introduction

Wireless Sensor Networks (WSNs) are a subclass of traditional mobile ad hoc networks (MANETs),and consist of a large number of sensor nodes, composed of processor, memory, battery, sensor devicesand transceiver. These nodes send monitoring data to an access point (AP), which is responsible forforwarding data to the users [1]. Unlike traditional ad hoc networks, in general, it is not possible toreplace or recharge node batteries due to the number of nodes deployed or inhospitable environmentalconditions. Hence, energy conservation is a critical factor in WSNs.

Severe hardware and energy constraints preclude the use of protocols developed for MANETs, whichcomparatively possess more resources. The strict requirements force networking protocols to be as muchenergy-efficient as possible. Medium access control (MAC) protocols, for example, modify transceiverparameters or even the topology of the network in order to reduce the energy consumption. One ofthose parameters is the transmission power that, besides reducing energy consumption, also provideshigher throughput, due to the reduced number of collisions and the establishment of links with lowerbit error rates [2, 3, 4]. Although an effective mechanism to reduce energy consumption, transmissionpower control is not implemented in any existing MAC protocol for WSNs. This occurs due to the highlyimprecise nature of readings provided by the transceiver, and also due to the restricted resources foundin current nodes. Those factors difficult an accurate calculation of the ideal transmission power.

∗Computer Science Department, Federal University of Minas Gerais Belo Horizonte-MG, Brazil, E-mails:{lcorreia,damacedo,daniacs,aldri,loureiro,jmarcos}@dcc.ufmg.br.

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In this paper we propose a transmission power control module for WSNs, which can be employed inany existing MAC protocol. Experiments in the Mica Motes 2 platform [5] show the efficiency of theapproaches proposed for power control, considering parameters such as energy and throughput.

This paper is organized as follows. Section 2 presents the main sources of energy consumption incommunication. Section 3 presents the related work. The methods proposed for transmission powercontrol are described in Section 4. Section 5 describes the evaluated scenarios and presents the results.Finally, Section 6 draws the conclusions and future work.

2. Energy Consumption in Communication

Among the hardware components in a sensor node, the highest energy consumer is the transceiver [1].In particular, the energy consumed by the transceiver is related to events in the communication andnetwork organization.

Communication events. Encompasses events such as overhearing (nodes listen to transmissionseven if they are not the destination of the packet), idle listening (nodes listen to the medium awaitingtransmissions) collision and transmission synchronization. Overhearing and idle listening are mitigatedby turning the radio periodically off (called duty cycles), or when incoming transmissions are not drivento the node. Collisions and transmission synchronization are avoided with the use of backoff techniques,medium reservation and the exchange of messages [6].

Network organization. Is related to the network topology and the communication pattern (single-hop or multi-hop). The topology can be modified by altering the transmission power. With shortercommunication ranges, the probability of hidden terminals [2, 7] and the number of collisions [8] issmaller, reducing energy consumption. Network organization can also be changed by topology controlprotocols, which turn off nodes producing redundant or unnecessary data to the application [9].

Transmission using power control

Transmission without power control

Collision

A B C D

Figure 1. Adjusting transmission power to avoid collisions.

Existing MAC protocols employ energy-saving techniques which operate only over communicationevents, ignoring network topology. Transmission power control techniques, however, can be very effective,as shown in figure 1. In this example, if nodes B and D, at the same time, transmit data at the typicaltransmission power (dashed lines) to nodes A and C, respectively, a collision will occur at node C. If thetransmission power is reduced to the minimum necessary to reach the destination of the packet (solidlines), no collisions occur. Besides decreasing the number of collisions, transmission power control hasother benefits, detailed below.

Transmission Power Control in MAC Protocols for Wireless Sensor Networks - DCC/UFMG - Technical Report: RT.DCC.011/2005

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Benefits of Transmission Power Control

Transmission power control allows several improvements in the operation of WSNs, such as the estab-lishment of links with higher reliability, communication with the minimum energy cost, and better reuseof the medium.

Links with higher reliability. When used in conjunction with link reliability assessment algorithms,power control techniques can be used to improve the reliability of a link. Upon detecting that linkreliability is below a certain threshold, the MAC protocol increases the transmission power, lowering theprobability of receiving corrupted data.

Communication at minimum energy cost. When communicating at a fixed transmission power,nodes waste energy since some links already have a high probability of a successful delivery. Hence, thetransmission control algorithm could decrease the transmission power to a level where link reliability isstill high, but energy consumption is lower.

Better reuse of the medium. When nodes communicate at the exact power needed to ensure asuccessful communication, signal range is nothing broader than it was supposed to. Thus, only nodeswhich really must share the same space will contend to access the medium, decreasing the amount ofcollisions in the network. This reduced number of collisions will also enhance network utilization andlower latency times.

3. Related Work

Several studies characterized channel propagation in wireless networks. Lal et al. [10] showed that it ispossible to identify link reliability using an energy-efficient algorithm. Reijers et al. [11] studied the effectof obstacles and environmental changes on link quality. Also, results showed that propagation is asym-metric and directional. RSSI (Received Signal Strength Indicator) readings were found to be extremelydependent on environmental conditions, thus should be used with caution. Given the irregularity ofsignal propagation in wireless transmissions, Zhou et al. [12] developed a new propagation model, whichclosely resembles the results obtained from experimental data.

Transmission power control is an active line of study in MANETs. Several MAC protocols employingthis technique have been proposed. PCMA (Power Controlled Multiple Access) is a MAC protocol whichprovides communication at minimum propagation ranges, allowing spatial reuse [2]. Agarwal et al.proposed a distributed power control algorithm for MANETs [7]. Pires et al. improved this algorithmby adding a table in each node, which stores the transmission power used on previous transmissions [13].In order to mitigate asymmetric links caused by transmission power variation, Jung & Vaidya proposedthat transmission power should be adjusted for every transmitted byte [3].

The transmission power control techniques developed for MANETs do not apply to WSNs. Since thecalculation performed is complex and imprecise in the transceivers employed in WSNs, current MACprotocols for WSNs do not implement transmission power control [14, 15, 16]. Our implementation oftransmission power control improves network operation by minimizing contention and decreasing theamount of energy required for communication. Our solution employs a transmission power calculationadapted to the restrictions found in WSNs. Also, we use tables to store the minimum transmission power,as in current solutions.

4. Identifying the Ideal Transmission Power

In order to identify the ideal transmission power, nodes must perform calculations based on severalreadings from the transceiver and the battery. Those are:


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• RSSI (Received Signal Strength Indicator): is the signal strength measured by the transceiver at itsinput interface. RSSI measurements are used to calculate the noise at the medium and the signalstrength when receiving incoming data.

• Sensitivity: is the least energetic power level at which the transceiver is able to detect and decodedata correctly. If any transmission is received at a power level below this limit, data will be garbled.

• Battery voltage: RSSI values read from the radio are calculated with battery voltage as a reference.Thus, in order to convert any RSSI reading to the actual reception power, the voltage at the momentof the reception must be known.

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Figure 2. Received signal strength when varying the distance among nodes.

In a successful transmission, the received signal strength is superior to the average noise at the receiver(the signal strength sampled when there are no ongoing transmissions on the medium). Communicationquality also depend on factors such as distance among the receiver and the transmitter and the existenceof sources of reflexion, refraction and dispersion. Figure 2 presents the received signal strength fortransmissions at 5 dBm, when varying the distance among the transmitter and the receiver, in the MicaMotes 2 platform. The “Nominal strength” curve shows the expected behavior of the signal, while the“Experimental data” curve shows empirical data. We infer from those curves that reception strength isproportional to the distance between the transmitter and receiver. The average noise, however, sufferedno significant alterations.

Signal propagation occurs differently for indoor and outdoor environments, thus propagation modelsare specific to each type of environment [17, 18]. Although such models can be used to provide a fairapproximation of the ideal transmission power needed to reach a node, those models are too costly to beexecuted in a sensor node. Thus, new algorithms suitable to the scarce resources found in WSNs mustbe developed. Two such methods are described below.

4.1. Assessing the Ideal Transmission Power Through Node Interaction

The ideal transmission power can be dynamically determined by the interaction of nodes. Transceiverstransmit data at only a few power levels. The transceiver used in the Mica Motes 2 platform, for example,provides 22 different levels, separated at roughly 1 dBm [19]. The switching between different power levels


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takes 20 µs. Since the number of possibilities is quite small, it is possible to iterate over the availablepower levels, increasing or decreasing the transmission power when necessary.

Figure 3. Operation of the interactive algorithm.

The algorithm proposed calculates the ideal transmission power by repeated refinements, and operatesin two phases. Figure 3 shows the operation of the algorithm. In the first phase, the ideal transmissionpower is determined, while in the second phase the transmission power is dynamically adapted to anyenvironmental change. Initially, the ideal transmission power is set to the maximum value allowed by thetransceiver. Nodes wishing to determine the ideal transmission power send a power query message (MPQ)piggy-backed in data packets at the “current” ideal transmission power, and await for a confirmationof reception, such as an acknowledgement (ACK) packet. If the reception is confirmed, the transmitterdecreases the ideal transmission power by one level, and sends another MPQ message. When the receptionof a MPQ message is not confirmed, the transmitter assumes that the ideal transmission power was found,and the second phase of operation starts.

In the second phase of the algorithm, nodes use ACKs to determine if the ideal transmission powershould be increased or decreased. If a number of consecutive transmissions are not confirmed with ACKs(this number is called the increase threshold, or LI), the ideal transmission power is increased one level.Since the noise can also decrease due to environmental changes, communication can also improve, thus thetransmission power is lowered if a certain number of consecutive messages are successfully received (thisnumber is called the decrease threshold, or LD). The values of LI and LD must be adjusted accordingto the typical throughput of the application, avoiding that the algorithm reacts too late to variations inlink reliability when the throughput is low, or that such changes are too frequent when the throughputis high. The algorithm treats node failures and transmission failures as being the same, since the use ofACKs to assess link reliability does not allow a distinction of such events. Broadcast packets are alwaystransmitted at a fixed power, since those packets are not acknowledged.


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4.2. Assessing the Ideal Transmission Power Through Signal Attenuation

The ideal transmission power can also be calculated as a function of signal attenuation. The idealpower is such that, given the attenuation in the link, data is transmitted at a signal strength that allowsthe reception at a signal slightly higher than both radio sensitivity and the noise on the receiver.

This method works as follows. Nodes periodically sample the signal strength when no transmissionsoccur, in order to determine the base noise (NB). If node A wishes to communicate with node B, ittransmits a packet to B at the standard transmission power (PTX). When B receives the packet from A,it determines the received signal strength (PRX , or reception power) and calculates the ideal transmissionpower (PTXideal)1 from A to B using equation 1. Next, B sends the calculated power to A, which willtransmit subsequent messages to B at this power level. In order to dynamically adjust the ideal powertransmission, node A always sends in its packets to B the current transmission power. B, in turn,recalculates the ideal transmission power, and sends this value to A piggy-backed in the ACK messages.

PTXideal = max

{RXthreshold

GA→B,

SINRthreshold × NB

GA→B

}(1)

The ideal transmission power is directional, that is, it depends on the direction of the communication,and must compensate the attenuation imposed by the link (RXthreshold

GA→B). Also, the reception power must

be higher than the noise and radio sensitivity (SINRthreshold×NBGA→B

) at the receiving node. The attenuationfrom A to B (GA→B, or gain) is the relation of the reception and transmission power (PRX

PTX), and is

considered to be symmetric in our calculations. The signal to noise ratio (SINR) is the ratio of thereception signal when compared to the noise, and NB is the noise in node B. The transmission powermust ensure that the signal is received in B without errors. In order to do so, some values mustbe determined empirically, such as radio sensitivity (RXthreshold) and the SINR threshold, since theyvary for each transceiver. Finally, the calculated power must lie within the maximum and minimumtransmission power allowed by the radio.

Sensor nodes provide integer values as output for RSSI readings, which must be converted to valuesin dBm. Since current sensor nodes do not perform floating point arithmetics, the calculation must bemade with integers, compromising its precision. Besides, readings from the transceiver and battery varyover time, thus the calculation must be adjusted to avoid subtle variations. The challenge of calculatingthe transmission power through attenuation resides in defining a precise, stable and efficient algorithm,which can be implemented with the operations provided by the micro-controller.

4.3. Storing the Ideal Transmission Power

To communicate at the ideal transmission power without requiring a calculation before every packettransmission, the protocol stores the current ideal transmission for each neighbor node [13]. Thus, nodesfirst query the table in order to detect if the ideal transmission power was already calculated. If it was,then data will be sent at this power. If it was not, the power transmission calculation is executed, andthe result is stored on the table for future use. Table 1 shows the fields stored in the table. Each nodestores the ideal transmission power, coded as the bit configuration that must be fed into the radio inorder to transmit at the ideal power (PotTx). A control variable (NoReduce) indicates if the ideal powerhas been calculated, while the Addr field stores the MAC address of the neighbor.

Since the noise is dynamic, and nodes may move or leave the network, entries on the table are inval-idated if no transmissions occur after some time. This avoids that nodes transmit data at the wrong

1The relation in the equation has its terms in mW.


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Field Size DescriptionPotTx 1 byte Ideal Tx. powerNoReduce 1 byte Ideal Tx. power already calculated?Addr 2 bytes MAC address of the neighbor

Table 1. Fields stored and their memory consumption in the Mica Motes 2 platform.

power after extended periods of silence.

5. Evaluation

To evaluate the efficiency of the proposed transmission power control techniques, we conducted exper-iments in the Mica Motes 2 platform, modifying its standard MAC protocol, called B-MAC, to transmitpackets at the ideal transmission power. The version employing the iterative method is called B-MAC-PCI, while the version employing the attenuation method is called B-MAC-PCA.

5.1. B-MAC Protocol

The B-MAC protocol was tailored to event-driven applications [14], and aims to be energy-efficient,avoid collisions and be simple, reducing code size. In order to broaden its applicability, B-MAC providesinterfaces to reconfigure most of its parameters.

Since B-MAC does not employ channel reservation (RTS/CTS messages), the protocol mitigates colli-sions with an heuristic called CCA (Clear Channel Assessment), which is used to identify transmissionsin the medium. This heuristic periodically samples the signal strength when there are no ongoing trans-missions, in order to determine the maximum noise level (the base noise). If the sampled signal strengthis higher than the base noise, the protocol detects an ongoing transmission.

Idle-listening is minimized with the use of a duty cycle. Nodes periodically sample the channel,using the CCA heuristic, to check for transmissions. If a transmission is not identified, nodes enter thereception mode. To ensure that every packet sent is received by all nodes, preambles must be as long asthe inactive period of the duty cycle. This asynchronous channel listening method is called LPL (LowPower Listening).

5.2. B-MAC-PC Protocols

The B-MAC-PC protocol was implemented in the TinyOS operating system [20], over the B-MACprotocol. In order to further increase energy savings, power control information is piggy-backed in dataand acknowledgement (ACK) packets. The power control information increased the data packet sizeby 3 bytes (one byte for the transmitted power, and 2 bytes for the sender address). ACK packets areincreased in 5 bytes (2 bytes for the sender address, another 2 bytes for the receiver address, and onebyte for the ideal transmission power).

Besides transmitting additional fields at each packet, B-MAC-PC employs a transmission power table,described in section 4.3. This table stores information of up to 20 neighbors. As nodes might not sendunicast messages to every neighbor, the size of the table can be reduced according to the needs of theapplication. The addition of the interactive transmission power control module increased the code sizeof B-MAC from 7650 to 8440 bytes, and the RAM memory consumed increased from 242 to 340 bytes.B-MAC-PC using the attenuation method consumed 9600 and 385 bytes in code memory and RAM,respectively. We conducted empirical measurements to determine some parameters used in B-MAC-PC.Those measurements are briefly described below.


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Interactive method (B-MAC-PCI). The ideal values for LI and LD were adjusted to minimizepacket losses, as shown in figure 4. When increasing LD, less packets are lost, but the method respondsslowly to environmental changes. For LI , the behavior is the opposite. LI should be set to a smallvalue, since it responds rapidly to variations in the noise. Figures 5 and 6 show the behavior of thetransmission power when varying LD and LI , respectively. Figure 5 shows that higher values of LD keepthe transmission power more stable, while smaller values of LI increase energy consumption, since thetransmission power is more easily and frequently increased. Figure 6 shows that the value of LI alsodefines the amplitude of the variation. For small values of LI , errors in bursts might significantly increasethe transmission power.

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LI = 1LI = 2LI = 3LI = 4

Figure 4. Average packet losses when varying LD and LI .

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Figure 5. Transmission power behavior when varying LD.

Attenuation method (B-MAC-PCA). The values of RXthreshold and SINRthreshold were definedin experiments where we varied the distance between nodes until the receiver could not decode thetransmitted data. The experiments were made in an outdoor area free of obstacles, using two nodeselevated 1.5m from the ground. The transmission power used was 5 dBm. From this experiment wedetermined SINRthreshold as 10 dBm, and RXthreshold as -85 dBm.


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Figure 6. Transmission power behavior when varying LI .

5.3. Experimental Results

We measured the behavior of B-MAC and B-MAC-PC when varying the distance between the receiverand the transmitter. Our experiment consisted of two Mica Motes 2 nodes. The first node sent 400messages destined to the second node, at a rate of four messages per second. The experiments weremade in an outdoor area, free of any obstacles. We chose to use only two nodes in order to avoidinterference with other nodes. Nodes were placed 71cm above the ground to avoid reflexion and absorptionphenomena. Node distance was varied from 5 to 20 meters. LI was set to one, and LD was set to eight.In B-MAC, we employed the standard transmission power, which is 0 dBm. All the results are presentedas an average of five independent experiments, with confidence interval of 95%.

Figure 7 shows the delivery rates for the protocols. Both the attenuation method (B-MAC-PCA) andthe iterative method (B-MAC-PCI) sustained nearly constant delivery rates when varying the distanceamong nodes. The iterative method was the most stable, yielding approximately 87.5% of packetsdelivered. The attenuation method delivered from 79% up to 86% of the packets. B-MAC results, onthe other hand, are dependent on the distance among nodes. It ranges from an outstanding 98.5%,when nodes are 5m apart from each other, to 14.2% for 20m of separation. This is mostly due to thereception power, which increases the bit error rate of the channel. For distances of 25 meters (not shown),the transmission power in B-MAC is insufficient, and no packets are received, while both B-MAC-PCprotocols kept their delivery rates intact.

Figure 8 presents the transmission power. For distances of 5 and 10 meters, B-MAC-PCI and B-MAC-PCA decrease the standard transmission power from 0 dBm to -5.7 dBm and -4.7 dBm, respectively.Meanwhile, B-MAC still transmits at the standard power, consuming more energy. The use of lowertransmission power allows energy savings of 27% and 21% over B-MAC when using B-MAC-PCI and B-MAC-PCA, for a distance of 5m. For a distance of 10m, this economy drops to 6.9% and 8%, respectively.For distances of 15m or more, the standard transmission power is barely enough to reach the nodes (asshown in Figure 7), thus BMAC’s link quality decreases. In those distances, B-MAC-PC increases thetransmission power in order to maintain an acceptable link quality, also increasing the energy consumed.However, this increase is compensated by a much higher packet delivery rate.

The causes of packet losses in B-MAC and in B-MAC-PC are shown in Figures 9 and 10, respectively.In B-MAC, for distances up to 10m, half of the packets lost are due to CRC errors, and the other half islost because the preamble is not detected. When distance increases, the most important cause of packet


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Figure 7. Average delivery rate.

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Figure 8. Average transmission power.

losses is preamble decoding. When analysing the results for B-MAC-PC (Figure 10), we identified thata lost preamble is the most significant cause of packet losses, accounting for roughly 76% of the total inthe iterative method (“I” bars), and 66% of all losses in the attenuation method (the “A” bars). Thus,both B-MAC and B-MAC-PC would benefit from a preamble seek algorithm more resilient to bit errors.

The attenuation and iterative methods showed frequent variations in the transmission power, as shownin Figure 11. This is caused by noise variations, and also due to imprecisions in transceiver readings.Ideally, the transmission power would change only when a significant variation in noise occurs, that is,the methods should be less susceptible to ephemerous variations. We plan to incorporate concepts fromsignal filtering disciplines in the algorithm, in order to avoid frequent transmission power variations.This is a challenging task, as signal filter algorithms must be small and efficient, in order to run in therestricted processors found in current sensor nodes.

5.4. Simulation Results

The precision of the attenuation calculation was evaluated in a PC, using logs from previous experi-ments. Table 2 shows that results calculated in the node are very close to the expected value, and the


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Figure 9. Cause of packet losses in B-MAC.

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No Preamble (I)CRC (I)

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Figure 10. Cause of packet losses in B-MAC-PC (interactive and attenuation).

average error is close to the error incurred in rounding. We also ran the calculation in a simulator for theprocessor found in the Mica Motes 2 platform. Results for 20,480 executions of the code with no compileroptimizations showed that the calculation takes 834.17 cycles (208.54µs) on average. We chose not touse any compiler optimization, since initial testing showed that the compiler was artificially speeding upthe calculation by storing frequently used values. Compiler optimizations, however, may be valuable ina real implementation.

6. Conclusion and Future Work

Among the tasks performed by sensor nodes, communication consumes most of the energy. Thus,medium access control protocols for Wireless Sensor Networks (WSNs) must employ energy-saving algo-rithms. Transmission power control is one such mechanism, however it was not used in WSNs due to thelimitations imposed by the sensor nodes. This article proposed and evaluated, through experiments andsimulations, two transmission control algorithms developed for WSNs. Those methods allow the defini-tion of new protocols, which improve network lifetime and performance by adjusting the transmission


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Packet number

Iterative methodAttenuation method

Figure 11. Transmission power variation in time.

Property ValueNumber of executions 7929Average error 0.2887 dBmMaximum error 0.7526 dBmMinimum error 0.0013 dBmFirst quartile of the error 0.1178 dBmMedian of the error 0.2342 dBm

Table 2. Precision of the transmission power calculation.

power to spend the minimum amount of energy needed to reach the receiver with a good communica-tion quality. Results showed that transmission power control is an effective method to decrease energyconsumption, and incurs in a negligible loss in packet delivery rates.

As future work, we intend to perfect the transmission power algorithms in order to avoid frequenttransmission power variations. Also, results showed that the use of different preamble sizes and variouspreamble identification algorithms might decrease packet losses. Finally, the transmission power controltechnique must be evaluated in MAC protocols which employ channel reservation, exploring RTS andCTS messages to improve the performance of the transmission power calculation.

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[16] Koen Langendoen and Gertjan Halkes. Energy-efficient medium access control. In R. Zurawski,editor, Embedded Systems Handbook. CRC Press, 2005.

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Transmission power control in MAC protocols for wireless sensor networks

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