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On enabling cooperative communication and diversitycombination in IEEE 802.15.4 wireless networks using

off-the-shelf sensor motes

Muhammad U. Ilyas Moonseong Kim

Hayder Radha

Published online: 21 April 2011

Springer Science+Business Media, LLC 2011

Abstract This paper presents the Generalized Poor

Mans SIMO System (gPMSS) which combines twoapproaches, cooperative communication and diversity

combination, to reduce packet losses over links in wireless

sensor networks. The proposed gPMSS is distinct from

previous cooperative communication architectures in

wireless sensor networks which rely on a relay channel,

and also distinct from implementations in 802.11 networks

that require a wired infrastructure or hardware changes for

cooperation. gPMSS foregoes the need for any changes to

mote hardware and it works within the current IEEE

802.15.4 standard. We describe the gPMSS protocol that

governs the cooperation between receivers. Three variants

are evaluated including selection diversity, equal gain and

maximal ratio combining. First, we demonstrate gPMSS on

bit error traces in a fully reproducible manner. This is

followed by an implementation of gPMSS in C# on the

.NET Micro Framework edition of the recently released

Imote2 mote platform. We demonstrate by means of

experiments an increase in the packet reception rate from

2230% to 7376%, a relative increase of 150245%. We

also analyzed the power consumed by the transmitter per

delivered packet and observe a reduction of up to 68%.We also take into account the retry limit of the IEEE

802.15.4 protocol and demonstrate that gPMSS is able to

provide 99% packet delivery at the protocols default retry

parameters against 6575% without it.

Keywords Wireless sensor networks Receivercooperation Diversity combining IEEE 802.15.4

1 Introduction

Channel fades and interference effects limit the throughput,

useful communication range and (in case of battery pow-

ered devices) lifetime of nodes. In this chapter we describe

the generalized Poor-Mans-SIMO-System (gPMSS), a

readily deployable low-cost, low-power, protocol centric

approach that enables cooperative communication in IEEE

802.15.4 [1] wireless sensor networks (WSN). We dem-

onstrate that gPMSS reduces the fraction of packets that are

received with bit errors or not received at all by an order of

magnitude, thus reducing the number of retransmissions. It

makes the use of long range links that are unfeasible due to

high packet loss and retransmission rates feasible again.

We also show that even in instances where gPMSS is not

able to correct all errors from a packet it still succeeds in

reducing the number of bit errors. At the receiver side

gPMSS uses diversity combining methods adapted from

their analog domain counterparts of the same name [6] for

digital signals. What makes the application of single-input

multiple-output (SIMO) diversity combining principles

novel from traditional use is that they are applied to the

demodulated version of received packets, after Physical

layer processing. We demonstrate the efficacy of gPMSS

The preliminary version of this paper titled Reducing Packet Losses

in Networks of Commodity IEEE 802.15.4 Sensor Motes Using

Cooperative Communication and Diversity Combination waspublished in the proceedings of the IEEE Conference on Computer

Communications (Infocom), Rio de Janeiro, Brazil, Apr. 1925, 2009.

M. U. Ilyas (&) M. Kim H. RadhaDepartment of Electrical and Computer Engineering,

Michigan State University, East Lansing, MI 48824, USA

e-mail: [email protected]

M. Kim


H. Radha


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DOI 10.1007/s11276-011-0338-7


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by applying it to bit error traces collected from IEEE

802.15.4 channels that allow detailed analysis and precise

reproduction of results. We also demonstrate gPMSS

effectiveness under real-world conditions by implementa-

tion on Crossbows Imote2 .NET Micro Framework sensor

platform [12].

Enabling the use of long range links (that would other-

wise not be used) makes gPMSS a viable protocol due tothe benefits and utility of such links by several applications

in wireless sensor networks.

Network lifetime extension Funneling is the effect of

network traffic from multiple sources flowing to a small

number of sink nodes [26]. This traffic surge produces

congestion in the region around the sink nodes/base station,

forcing nodes near sink nodes to relay more traffic than

other nodes and consume power at correspondingly higher

rates. Since nodes in WSNs have only limited power

resources this means that the sink nodes neighbors will run

out of power sooner, leaving the sink node disconnected

from the rest of the network. Load balancing techniqueslike [15] attempt to distribute the burden of relaying traffic

to increase the lifetime of sensor networks. Employing

gPMSS in such a scenario will grow the set of neighbor

nodes of the sink node and allow load balancing among

more nodes.

Small-world networks Several attempts have been made

at building small-world network [27] topologies in wireless

networks to simplify resource discovery and reducing

average path length to facilitate data dissemination. Pro-

posed architectures required hardware modifications such

as adding a secondary RF interface [25, 26] or building

hybrid networks by augmenting wireless networks with

wired shortcuts [9, 22]. Since gPMSS is a protocol centric

approach it does not require any hardware modifications

which adds to its appeal as a low-complexity and low-cost

solution.

Network connectivity Long range links can be used to

add links between two components of a network that are

only sparsely connected with one another.

gPMSS adopts well-understood diversity combining

methods for analog signals and applies them to digital

signals (packets). Specifically, gPMSS implements selec-

tion diversity, equal gain diversity combining and maxi-

mal-ratio gain diversity combining. The latter relies on a

model of the instantaneous bit error rate (BER) driven by

channel state information (CSI) [16], i.e. received signal

strength indication (RSSI) and link quality indication

(LQI). We provide proof of concept by applying gPMSS to

bit-error traces and demonstrate one order of magnitude

reduction in packet losses. Applying gPMSS to traces

allows more detailed analysis and reproducibility that is

not possible in a live setup, i.e. the event when receivers

are not able to reconstruct an error-free version of the

transmission. We show that even then we are able to sig-

nificantly reduce the average BER of incorrigible packets.

Finally, we implement gPMSS on Imote2 sensor motes

[12] using C# and demonstrate a clear reduction in packet

losses. Experimental results from IEEE 802.15.4 links

indicate that using diversity combining raises packet

reception rate (PRR) by up to an additional 130% over

those in a single receiver.Our contributions are threefold;

1. gPMSS is a protocol centric, cross-layer approach

which means it can be used in presently deployed

wireless sensor networks by making software changes

only. It does not require any modifications to hardware

but runs on networks of commercial off-the-shelf

(COTS) single antenna sensor motes.

2. gPMSS is non-intrusive in the sense that it does not

require changes to the pre-existing IEEE 802.15.4

standard.

3. gPMSS is able to reduce power consumed at thetransmitter per packet delivered by up to 68%.

This represents a significant increase in the lifetime

of sensor node.

Figure 1 illustrates the difference between routes tra-

versed by a packet sent by transmitter T to a distant node

R1 when gPMSS is used (dotted arrows represent long

range links, solid lines represent links between R1, R2, R3

that form a fully connected graph), and the multi-hop path

from node T to R1 when it is not used (solid arrows).

The remainder of this chapter is organized as follows:

Section 2 reviews some related works. Section 3 describes

the three diversity combining techniques for packet

recovery. Section 4 describes the gPMSS that enables

cooperation between multiple receivers. Section 5

R1R2R3

T

Low packet losscommunication range

High packet losscommunication range

Fig. 1 Application of generalized gPMSS in a wireless sensor

network with mesh topology. Path from transmitter T to receiver R1

marks the multihop path that would be taken in a network without

gPMSS. Dashed line links between T and receivers R1, R2 and R3

denote the longer range but high loss links that are used under

Generalized gPMSS

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describes the trace collection setup and demonstrates a

proof of concept of gPMSS in a manner that can be

reproduced. Section 6 describes the gPMSS implementa-

tion on Imote2 and its results. Section 7 discusses our

results in terms of PRR, retransmission attempts and

energy consumption per packet. Section 8 concludes this

chapter.

2 Related work

The concept of spatial receiver diversity is not new and has

been studied extensively in the analog signal domain.

Chakraborty et al. proposed the Extended ARQ scheme [7]

that recombines spatially diverse versions of a received

packet to detect bit errors and an exhaustive search to

correct them if their number is less than a threshold value.

Extended ARQ has a lot in common with the version of

gPMSS that uses equal gain combining and is agnostic of

what MAC standard is used, but the results provided in [ 7]are based on theoretical analysis only. Miu et al. [19]

proposed a system that used transmitter diversity to

increase packet reception rate in IEEE 802.11 [13] net-

works with multiple access points (AP) as senders. The

scheme roughly corresponds to gPMSS with selection

diversity, without diversity combination for error correc-

tion. Miu et al. generalized this approach in [21] for

applications beyond streaming video. Miu [20] extended

the idea further to reduce packet losses on the uplink

(mobile device to AP). However, this required modifica-

tions to IEEE 802.11b AP hardware or deployment of more

APs, and uses a dedicated frame combiner connected to all

APs through a wired network. It used the equal gain

method for detecting bit errors and, like Extended ARQ,

relied on an exhaustive search of the correct bit values.

Cheng and Valenti [8, 24] extended the idea for improving

throughput on uplinks in IEEE 802.11a networks by using

maximal ratio combining based on CSI measurements.

However, like Mius system it still required a dedicated

combiner connected to all APs. Ji et al. [17] proposed an

approach for improving the throughput of downlinks by

scheduling transmissions to multiple receivers in IEEE

802.11a/b networks based on explicit feedback from

receivers while maintaining fairness. Bahl [2] made the

case for multi-radio transceivers, but as Fig. 4 in his paper

showed, collaboration between network interfaces is pos-

sible only when they are all located on the same device.

More recently, Woo described SOFT [28] which also

exploited receiver diversity for the uplink in IEEE 802.11

networks similar to Mius [20], but with diversity com-

bining being performed using maximal ratio combining.

Therefore, it too requires a centralized combiner on the

wired network that all APs are connected to. The most

recent and most relevant work using cooperative receiver

diversity is Bletsas and Lippman [5] and Bletsas et al. [4].

However, this paper offers several improvements over

Bletsas et al. approach:

Bletsas et al. rely on selection diversity alone, i.e. a

transmission can be received successfully only if at

least one of the cooperating receivers has an error-freereception. No attempt is made at correcting packets that

are received with errors. gPMSS fills this gap by

supplementing selection diversity with various diversity

combining methods.

Bletsas protocol relies on the exchange of IEEE

802.11x like request-to-send/clear-to-send (RTS/CTS)

packets prior to the actual data transmission to clear the

channel and inhibit interference. Since the gPMSS

protocol presented in this paper is based on IEEE

802.15.4, it forgoes use of RTS/CTS packets which

reduces power consumption.

Bletsas uses a pilot signal transmitted by the sender toselect a relay node prior to data transmission based on

network conditions. In gPMSS, as long as any one

candidate relay node has received a transmitted packet

free of errors, the selection of the relay node is

performed without any packet transmission overhead,

on a packet-by-packet basis.

Bletsas et al. used COTS hardware for their cooper-

ating receivers. However, their definition of COTS is

very broad in the sense that they use the term to

describe custom built mote platforms using COTS

components. We use the term COTS in a stricter sense

that includes only commercial mote platforms andprecludes any specially designed or modified systems,

even if built from commercially available compo-

nents. This paper demonstrates gPMSS on unmodified

Crossbow Imote2 [12] platforms [12], a truly COTS

platform.

To summarize, the gPMSS system presented is distinct

from all these prior works on cooperative communication

and diversity combining in wireless networks because it is

(1) designed for IEEE 802.15.4 networks, (2) is purely

implemented in software and commercial-off-the-shelf

motes without modifications to mote hardware, (3) is tested

on bit error traces collected from real IEEE 802.15.4

channels, (4) as well as actual implementation on motes.

3 SIMO diversity combining techniques

The solution that is described in this section is dubbed

the Generalized Poor-Mans-SIMO-System because it

uses receiver side diversity combining techniques and is

built using commercial-off-the-shelf components, without

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customized or reconfigured hardware. Receiver diversity

improves link quality of wireless channels with high losses.

This way we reduce losses and retransmissions and

increase throughput and channel utilization. This subsec-

tion describes linear diversity combining techniques. All

these techniques are derivatives of the techniques by the

same names presented by Brennan [6]. Brennan describes

scanning diversity, selection diversity, equal gain diversityand maximal-ratio diversity combining. Although the

methods described by Brennan were meant for analog

signals, we have suitably modified and adapted them for

use with demodulated, digital signals. We have included

the last three, selection, equal gain and maximal-ratio

diversity combining. Readers should know that even when

the diversity combining method used is either equal gain or

maximal-ratio combining, selection diversity is used

whenever at least one receiver possesses an error-free

version of a transmissions. Equal gain or maximal ratio

combining are only used when none of the gPMSS

receivers was able to receive error-free (i.e. the situationdescribed in Fig. 3c). The purposes of diversity combining

are twofold.

1. Select an error-free version of a received transmission

from among all received versions.

2. If the first goal is not achievable, obtain another

version of the transmission, with fewer errors than any

of the individual received versions.

3.1 Selection diversity

Selection diversity is the simplest diversity combining

technique. Figure 2a is an equivalent system diagram of the

selection diversity process. The basic idea in is to select

from all received packets the one that is expected to have

the fewest errors. This is advantageous when it is used in

conjunction with forward error correction (FEC) because

fewer bit errors are easier to correct than more bit errors.

When all received versions have errors, the best selection

diversity can hope to achieve is pick the version with the

fewest bit errors. We define the bit error rate (BER) of the

nth packet in a sequence as,

BER bn #of error bits in nth

recvd pkt# of bits innth recvd pkt

: 1

Thus the underlying random process producing the

sequence of BER observations b[n] is called the BER

process and is denoted by B. The term BER is not used in

its strict traditional sense where it denotes the long term

average probability of bit errors, such as in a binary sym-

metric channel (BSC). Instead the BER is computed over

each received packet. Unfortunately, under ordinary cir-

cumstances the BER process is not directly observable.

A packets failure to pass the cyclic redundancy check

(CRC) test only tells us that the number of bits with errors

is non-zero (b[ 0), but it does not give any information

about the number of errors. Therefore, we must rely on

estimates of the BER. The performance of selection

diversity will be determined by the accuracy of the model

used to predict the BER of packets that fail the CRC test.

We have used Ilyas and Radhas [16] CSI measurement-

based model of the BER process on IEEE 802.15.4 links. It

models the BER of packets with errors by a random vari-

able with an exponential distribution whose parameters are

estimated using maximum likelihood estimation (MLE).

Packets are first classified according to CSI measurements

and separate BER distributions are generated for each.

Parameters for Ilyas and Radhas CSI measurement-based

model is based on an extensive set of bit error traces. For

each received packet the model relies on two CSI param-

eters, i.e. LQI and RSSI. Measurement of both RSSI and

LQI is mandated by the IEEE 802.15.4 LR-WPAN stan-

dard for every received packet. The RSSI random process

is denoted by P, and RSSI measured by a receiver R for the

nth packet in a sequence is denoted by qR[n].

We used the MICAz [11] to demonstrate proof-

of-concept and the Imote2 [12] to demonstrate the

BERModel

BERModel

BER

Model

BER

Model

BER

Model

BERModel

(a)

(b)

(c)

Fig. 2 Illustration of logical functioning of various diversity com-

bining techniques. a Selection diversity. b Equal gain diversity.

c Maximal ratio gain diversity

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functioning gPMSS protocol implementation, both of

which use the Chipcon CC2420 radio transceiver [23].

Note that almost all commercially available wireless sensorplatforms with IEEE 802.15.4 RF interfaces currently use

the either the Chipcon CC2420 or its newer variant the

CC2430 radio transceiver. Therefore, we expect the results

and conclusions drawn to hold across a wide range of

different mote platforms. Technically, the CC2420 does

not measure the LQI directly. Instead, it measures the

correlation C between the first 8 received symbols (of the

PHY header) and the corresponding 8 known symbols

(Preamble). IEEE 802.15.4 uses 16-ary Offset-Quadrature

Phase Shift Keying modulation which encodes 4 bits in one

symbol. The first 8 symbols, 4 bytes, of the PHY header

comprise of the Preamble sequence consisting of 32 binaryzeros. The LQI is then defined as,

LQI C c1 c2: 2

In the Chipcon CC2420 c1 and c2 are functions of the

packet error rate (PER) measured over an extended period

of time and are determined experimentally. c1 and c2 scale

the 7 bit value of the correlation to the range of an 8 bit

number. Since equation 2 is merely a shifting and scaling

of the measured C we take c1 = 0 and c2 = 1. The LQI

random process is denoted by K, and LQI measured by a

receiver R for the nth packet in a sequence is denoted by

k

R

[n].Coming back to our description of the CSI-driven BER

model of [16], each pair of LQI and RSSI inputs produces a

probability density function (PDF) of the BER of packets

received with those particular CSI measurements. To be

useful in the current context, the output of the CSI-driven

BER model has to be mapped to a single value. We use

bX% to denote the Xth percentile of the BER process PDF

(b50% is Bs mean). The instances of the BER model return

BER estimates denoted as b(R1), b(R2) and b(R3). The output

selector in Fig. 2a receives as input the estimated BERs

b(R1), b(R2) and b(R3). Based on these estimates it selects the

receiver with the lowest BER estimate as the least error-prone one and accepts its received copy as the best one and

outputs it as D(Sel), i.e.

DSel DRr : r arg minibRi: 3

3.2 Equal gain diversity

The equal gain diversity combining method described here

is depicted by an equivalent system diagram in Fig. 2b.

D(T)

ACK

Time

T0

(a) (b)

(c)

Fig. 3 gPMSS protocol

operations. a Reception of an

error free packet by a gPMSS

cluster. b gPMSS message

exchanges when parent receiver

R1 receives message with errors

but child R2 receives error-free.

c gPMSS message exchanges

for recovery of data when

neither parent R1 nor children

R2 and R3 receive error-free

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Recall that like D(T), the three received copies eDR1; eDR2and eDR3 are vectors of binary numbers (representing bits)obtained after demodulation of the received carrier signal.

Essentially, equal gain diversity combining uses received

data

eDR1;

eDR2 and

eDR3 to vote on the value of each

output bit. In the example in Fig. 2b performs vector

addition of eDR1; eDR2 and eDR3, stores the sums inintegers and then adjusts the gain by dividing by thenumber of receivers N, where N = 3 in this example. The

result will be an array of rational numbers in the range

[0,1]. These numbers are thresholded such that values less

than 0.5 are remapped to binary zeros, and values greater

than (or equal to) 0.5 to binary ones. The output of the

thresholder is D(EG). If S is a function representingthe operation of the binary decision thresholder, then for an

N-receiver gPMSS cluster the equal gain diversity com-

bining process can be represented as;

D

EG

S

1

NXN

i1 D

Ri !: 4Equal gain diversity combining has two advantages over

the preceding selection diversity combining.

1. It has lower complexity because it does not rely on a

BER model.

2. The diversity combining procedure may output a copy

of the transmitted packet that has fewer errors or

is completely error-free, even when all individual

received copies are not.

3.3 Maximal ratio diversity

The maximal ratio diversity combining method described

here is depicted by an equivalent system diagram in

Fig. 2c. It combines elements from selection and equal

gain diversity combining. Maximal ratio combining can be

described as equal gain diversity but with weighted addi-

tion. eDR1; eDR2 and eDR3 are each multiplied by weightsw1, w2 and w3 computed as,

wi 1 2bRi 81 i N 5

and added. The sum is then re-normalized by dividing by

the number of receivers N (in this case N = 3) and

thresholded which returns the output D(MR) of the maximal

ratio combining process;

DMR S1

N

XNi1

wi DRi

!: 6

In the following subsection we proceed to describe the

gPMSS protocol that enables cooperation between

receivers.

4 gPMSS protocol

This section describes the operation of the gPMSS proto-

col. Assume a WSN consisting of a large number of single-

antenna COTS receivers communicating over multiple

hops with the base station collecting data. According to

some topology construction algorithm, a node R1 is chosen

as an upstream end-point of a link. To use R1 as part of aset of multiple receivers we propose the gPMSS protocol

that defines the message exchange between cooperating

receiver nodes to handle transmissions that are received

with errors or not received at all. The following subsection

provides a brief overview of gPMSS protocol message

exchanges for four important operations. For illustrative

purposes we assume a scenario in which there is a distant

transmitter Tand a receiver R1 with two neighbor nodes R2

and R3 that are located close enough to communicate with

R1 with few losses.

4.1 gPMSS cluster creation

The Poor Mans SIMO System (PMSS) described by

Ilyas, Kim and Radha [14] differs from gPMSS in the way

clusters of receivers are formed. In PMSS, cluster creation

is explicit, and involved an exchange of messages between

R2 and R1 and also between R3 and R1 after which R2 and

R3 would become associated with R1 to act as cooperating

receiver. In gPMSS nodes take advantage of CSI of over-

heard messages. The assistance rendered by neighbors to a

node R1 is now ad-hoc. The decision by a neighbor node

whether it is in a position to assist R1 is based on historical

link conditions between it and R1. Link conditions can be

simply assessed by tracking historical packet retransmis-

sion rates on a link, or LQI/RSSI measurements. Links

exhibiting performance a certain threshold level may be

classified as good.

Figures 7 and 8 density functions of LQI and RSSI of

packets originating from R1, R2 and R3. Nodes in a network

with the gPMSS protocol will maintain such histograms for

all neighbors from which they overhear traffic. A high mean,

median or mode of LQI and RSSI density functions is

indicative of a link with high PRR. In this way, once a node

determines it enjoys good link conditions with a neighbor it

will act as a member of that neighbors cluster of receive

nodes. Also, in PMSS cooperating nodes would communi-

cate withR1 in a scheduled, round-robin fashion. In contrast,

in gPMSS once it is determined that cooperating receivers

need to communicate withR1, transmission times are chosen

randomly. For more details about PMSS we refer the reader

to [14]. For the following discussion we will assume that this

way two nodes R2 and R3 placed close to R1 make the

assessment that they enjoy a reliable wireless channel with

R1 and volunteer to assist it as cooperating receivers.

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4.2 Error-free reception by at least one recipient

This section describes the exchange of messages under the

gPMSS protocol that occurs when at least any one of the

receiving nodes receives a transmitted packet without

errors. Figure 3a depicts the simplest case. The solid lines

represent the transmission and reception of a message

between source and destination node. The dotted linesrepresent communication that occurs implicitly as a result

of a receiver operating in promiscuous mode, (deliberately)

eavesdropping on messages exchanged between other

nodes (marked by solid lines). Here Tsends a data message

D(T) to R1 at time 0 that is overheard by R2 and R3. R1 will

promptly responds to T with an ACK within time T0 from

the initial transmission. R2 and R3 overhear the ACK from

R1 back to T within time T0 and recognize that the packet

was successfully received by R1 and acknowledged, and no

further action is required.

Figure 3b depicts the case where R1 is not the final

destination. In addition, let us also assume that R1 receivesthe transmission D(T) with errors (marked by a zigzagged

arrow), whereas R2 and R3 receive the same error-free.

After the initial timer T0 expires, all receivers that receive

D(T) error-free choose a random wait-time t1 from an

exponential PDF limited to the range [0,T1]. Let t1(R2) and

t1(R3) denote R2 and R3s random wait-times, respectively.

Let t1(R2)\ t1(R3), then R2 will transmit ACK back to

T before R3. R3 will overhear R2s ACK and cancel

transmission of its own ACK. At any time, if an ACK

packet is lost and not received by T within time TT of

transmitting data packet D(T), Ts fallback behavior will be

to retransmit D(T) (although it may already have been

received and ACKed). This way the power consumed in

nodes forming the gPMSS cluster to relay packets will be

more evenly distributed.

4.3 Erroneous reception by all recipients

This section describes the exchange of messages under the

gPMSS protocol that occurs when all nodes that form a

gPMSS cluster receive a transmission with errors. Figure 3c

depicts this entire transaction. Here Tsends a data message

D(T) toR1 that is overheard by R2 and R3. Since all receivers

R1, R2 and R3 receive with errors none of them is able torespond to T with an ACK within time T1. Let eDR1; eDR2and eDR3 denote the different versions of D(T) as they arereceived by R1, R2 and R3, respectively. Thus, there is no

error-free copy of the transmitted message at any receiver.

Nodes R1, R2 and R3 all wait for one another to respond to

Twith an ACK. When none of the receivers R1, R2 and R3

overhear an ACK going back to T within T0 ? T1 time of

receiving, they infer that none of them received D(T) error-

free. At this point, the lack of an ACK packet from the

receiver informs Tthat the receivers are about to collectively

attempt to recover the packet by means of diversity com-

bining. That process will involve the exchange o multiple

packets between R1, R2 and R3 which can be overheard by

T and will, if the RF transceiver is left active, result in

consumption of significant amounts of energy. Therefore,

Twill disable itsRF transceiver for the time period T2 during

which receivers attempt diversity combining. At the receiverside, instead of requesting a retransmission from T, R1

collects the error-prone versions of D from cooperating

receivers, acknowledging each one as it receives them. R2

will transmit eDR2; kR2;qR2, which denotes the concate-nation of eDR2, the LQI k(R2) and RSSI q(R2) with which itwas received from T, to R1 in time interval [T0 ? T1,

T0 ? T1 ? T2] after it received eDR2. Similarly, R3 willtransmit eDR3; kR3;qR3 between [T0 ? T1, T0 ? T1 ?T2] after it received

eDR3. Once R1 has received

f eDR2; kR2; qR2g and f eDR3; k

R3;qR3g it executes one

of the diversity combining algorithms described in the pre-ceding section in an attempt to recover D(T). If the CRC

computed from the recovered packet matches the appended

CRC the attempt is successful. On the receiver side Twaits

for an ACK, any ACK from any of the receivers R1, R2 or

R3, for a timeout period ofTTuntil it attempts retransmission

ofD(T). Note that TT[ T0 ? T1 ? T2.

It should also be noted that the reduction in retrans-

missions by T is achieved at the expense of an increase in

the time between when a data packet is transmitted and a

matching ACK is received. However, it should be noted

that IEEE 802.15.4 protocol explicitly forgoes the use of an

IEEE 802.11-like exchange of request-to-send(RTS)/clear-to-send(CTS) packets. Therefore, any delays experienced

by the transmitting node T in receiving an ACK do not

unduly hold up the communication of other nodes not

participating in the above described exchanges. However,

other nodes are affected by the transmissions between

receiver nodes that happens when diversity combining

is attempted. Most current environmental monitoring,

infrastructure monitoring, surveillance and other systems

enabled by WSN try to keep packet transmission rates low

to maximize the lifetime of power constrained sensors.

Therefore, the reduction in capacity that results from

diversity combining is assumed to be of little consequence

for most applications. When selection diversity is used to

avoid a retransmission by T capacity does not decrease.

5 Trace based proof of concept

In this section we provide proof of concept of gPMSS by

testing its performance on bit error traces. We collected

several different sets of bit error traces totaling a few

Wireless Netw (2011) 17:11731189 1179

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million packets in a way that provides, to the authors best

knowledge, the BER a packet is subjected to and the LQI

and RSSI with which it is received. The results shown in

this section are generated from one of those traces.

5.1 Experimental setup

The trace-collection setup is depicted in Fig. 4 and consistsof a Crossbow MPR2400 MICAz mote [11] transmitter and

another three MICAz motes mounted on Crossbow

MIB600 Ethernet gateways [10] as receivers. The three

receivers R1, R2 and R3 are connected to a host PC running

three instances of Xlisten (a data logging application), one

for each receiver. The link between transmitter and recei-

ver was non-line-of-sight, with a wall, a door and several

furniture items in the direct line between them. The

receivers were separated by a distance of 0.25m. The

transmitter was configured to transmit at 0 dBm. This way

a data collection session produces three traces. All traces

were collected while operating in channel 26 in the 2.480GHz band. The reason for choosing channel 26 was that it

is least prone to interference from any 802.11b/g frequency

channels. Our own experience shows that selecting chan-

nel 26 does not completely eliminate interference from

co-located 802.11b/g WLANs, but reduces it significantly.

5.1.1 Packet payload

TinyOS [18] is one of the most widely used open source

operating system in WSN devices. TinyOS v1.1 allows

various packet formats to be transmitted. We suitably

modified code to enable the standard 802.15.4 frame for-

mat which TinyOS v1.1 labels CC2420 Frame Format

(after the Chipcon CC2420 chipset [23] used in MICAz

devices). Strictly speaking, the term packet refers to the

Protocol Data Unit (PDU) exchanged between network

layers of the transmitter and receiver while the term frame

is used for PDUs exchanged between MAC layers.

However, since our analysis is restricted to the MAC layer

there is little cause for confusion and we use these terms

interchangeably to refer to MAC layer PDUs. The exact

MAC frame format used is shown in Fig. 5. The size of the

frame is 41 bytes and comprises of a 1 byte Length Field, 2

byte Frame Control Field (FCF), 1 byte Sequence Number,

2 byte Destination PAN ID, 2 byte Destination Address, 1

byte Type field, 1 byte Group field, 29 bytes of data fol-

lowed by a 2 byte Frame Check Sequence (FCS) contain-ing a CRC. The contents of the payload field are of our own

choosing and consist of 3 unused bytes, the Source

Address, the Destination Address and 6 copies of a 32 bit

sequence number. The sequence number in the payload is

used to keep track of lost packets. If the sequence number

between two consecutively received packets skips one or

more numbers that is indicative of a packet loss. The

sequence number field alone proves too small for this task

in the face of long fades. Note that transmitted packets

differ only in the 1 byte sequence number in the header and

the six 32 bit sequence numbers in the payload, and the

CRC. For a particular trace all remaining bits remain

unchanged. However, since the wireless channel will

introduce bit errors the copies of the sequence number used

to track packet losses in the received packet may differ. For

this purpose we use a majority vote of the received

sequence numbers to reconstruct the transmitted sequence

number and from it the entire packet.

5.1.2 Trace generation

Bit-level error traces can be generated by comparing a

transmitted packet with its received version. A simple bit-

wise XOR operation of the transmitted and received packets

yields a bit pattern in which a zero (0) signifies a bit that is

received without error while a one (1) represents an

inverted bit. We observe that in some cases the length of the

received packet is shorter than the transmitted packets. This

constitutes a partial loss and we use the term partially lost

packets to refer to such packets. Partially erased packets are

logged when bits in the MAC headers Length Field are

inverted and the receiver stops listening to the wireless

channel prematurely. It has also been observed that if bits in

MICAz MoteMICAz MoteEthernetGateway

Transmitter

Host PC

IEEE 802.15.4

Channel 26(2.480 GHz)

MICAz MoteEthernetGateway

Receiver 1

Receiver 2

MICAz MoteEthernetGateway

Receiver 3

Chan

nel3

Channel 2

Channel1

Fig. 4 Equipment setup for trace collection

LenFrameControl

SqNo

DestPAN ID

DestAddr

Typ Grp FCSData /

Payload

2Octets:

11221 921 2

0x8401

2

SrcAdr

1

0x00

1

SeqNo(1)

4

SeqNo(2)

4

SeqNo(3)

4

SeqNo(4)

4

SeqNo(5)

4

SeqNo(6)

4

DstAdr

1

Fig. 5 CC2420 MAC frame format used for experiments

1180 Wireless Netw (2011) 17:11731189

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the Length Field are inverted in such a way that the length of

the incoming packet appears longer than actual the length of

the logged packet still equals that of the transmission.

Although the Length Field in the received packet may fal-

sely indicate a longer packet, the absence of a carrier signal

allows the receiver to detect the end of transmission.

5.2 Channel state information

Each received packets logged entry is accompanied with

three pieces of packet level CSI parameters. The first is the

FCS status of the packet modeled by random variable U

with the nth packets FCS status is represented by /[n].

Ordinarily receivers only distinguish between two states,

i.e. FCS Pass (denoted / = 0) if the CRC value in the FCS

field matches the CRC of the received packet, and FCS

Fail (denoted / = 0) if it does not. Since we have

knowledge of packet erasures and size of transmitted

packets we extend the definition of FCS status to accom-

modate the reason for failure. We restrict the definition ofFCS Fail BE (denoted / = 1) to mean that the size of a

received packet matches the size of the transmitted packet

and the CRC failure is due to Bit Errors (BE). Furthermore

we classify a packet as being FCS Fail PL(denoted / = 2)

and FCS Fail CL (denoted / = 3), where PL and CL are

abbreviations for Partial Loss and Complete Loss respec-

tively. Packets that are partially lost cannot pass the CRC

test and are marked FCS Fail PL. Packets that are not

received at all, i.e. when the decoded Sequence Number at

receiver skips, are marked FCS Fail CL.

Among other CSI there are RSSI and LQI which we

described in earlier sections. Completely lost packets, with

/ = 3, are assigned q = -128, k = 0, and b = 1. Thus

each received packet is characterized by its FCS Status,

LQI, RSSI and BER processes.

5.3 Implementation results

Using the above detailed setup we collected . The partic-

ular trace used to demonstrate proof of concept of gPMSS

consists of 891,070 data packets collected from 7:12:42

p.m. on November 21, 2007 to 7:23:02 p.m. on November

22, 2007 in the Engineering Building at Michigan State

University. This particular data set was collected in an

office environment. The gPMSS cluster consisted of three

receivers, also Crossbow MICAz motes mounted on

MIB600 Ethernet gateways. Figure 6 is a cropped portion

of the PDF of BERs observed in packets at gPMSS

receivers R1, R2 and R3 that excludes b = 0 for enhanced

visibility. Figure 7 depicts the PDF of the LQI of all

received packets at R1, R2 and R3. Figure 8 depicts the

PDF of their RSSI. These three figures clearly show that all

three receivers experience different channel conditions.

5.3.1 PER and PLR analysis

We define two quantities based on the FCS status, the

packet error rate (PER) and the packet loss rate (PLR);

PER #of rcvd packets with/ 1; 2

# of transmitted packets; 7

PLR # of rcvd packets with/ 3

# of transmitted packets; 8

The packet reception rate (PRR) as PRR = 1 - (PER ?

PLR). In Fig. 9 the first three entries on the horizontal axis

plot the PER, PLR and the sum of the two, PER?PLR, for

R1, R2 and R3. For individual receivers PER?PLR hap-

pens to be approximately 7, 17 and 12%. These figures are

followed by plots of these same quantities for the three

diversity combining techniques. The simplest technique,

selection diversity, appears to track the PER?PLR of the

best performing receiver, in this case R1. Equal gain and

maximal ratio diversity combining both perform better than

0.02 0.04 0.06 0.08 0.1 0.12 0.14

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

BER

pB

()

R1

R2

R3

Fig. 6 PDF of BER experienced by receivers R1, R2 and R3

(pB (b = 0) is cropped out for better view of non-zero range

40 60 80 1000

0.02

0.04

0.06

0.08

LQI

p

()

R1

R2

R3

Fig. 7 PDF of LQI experienced by receivers R1, R2 and R3

Wireless Netw (2011) 17:11731189 1181

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any individual receiver and selection diversity. This was to

be expected. Recall that selection diversity merely tries to

pick out the least corrupted version among a set, whereas

equal gain and maximal ratio actually attempt to correct

errors in received messages by un-weighted and weighted

voting, respectively. This is adequately reflected in the plot

of PER, PLR and PER?PLRs. Both are able to reduce the

PER.

5.3.2 BER analysis

In Fig. 10 we plot the histogram (not PDF) of packets with

non-zero BER as experienced by individual receivers R1,

R2 and R3 without any diversity combining, as well as with

different diversity combining methods. Again, the trends

exhibited by diversity combining methods are the same

across all traces. Figure 10 shows that the histogram of the

selection diversity combining closely matches that of thebest receiving individual receiver, i.e. R1. The close match

of the histogram of selection diversity with that of R1

shows it manages to bring a gPMSS BER performance up

to that of the best receiving node. Thus, the BER model

that is at the heart of this diversity combining technique

delivers good performance. The result of equal gain and

maximal gain diversity combining are even better. For

every BER bin in the histogram, both equal gain and

maximal-ratio combining are able to reduce the number of

corrupt packets. Both are very close in their performance,

but equal gain is consistently beating maximal-ratio com-

bining across all BER bins in Fig. 10, and is also able to

maintain this performance across different trace sets.

6 gPMSS protocol implementation

This section describes our implementation of the gPMSS

protocol for motes and analyzes its performance. For the

mote platform, we selected the Crossbows Imote2 with the

pre-installed .NET Micro Framework edition [12]. Using

this edition of the Imote2 enabled us to implement gPMSS

in the C# programming language which simplified and

accelerated development. At this point we would like to

clarify that although the Imote2 used for the actual

implementation in this section is different from the MICAz

we used for trace collection in Sect. 5, both use the same

Chipcon CC2420 radio transceiver [23] which makes them

equivalent for the purpose at hand. As the description of

the gPMSS protocol above showed, in a situation when a

transmission is received correctly by at least one recipient,

gPMSS implements selection diversity described in

Sect. 3.1. But when a transmission is received with errors

95 90 85 800

0.1

0.2

0.3

0.4

0.5

0.6

RSSI (dBm)

pP

()

R1

R2

R3

Fig. 8 PDF of RSSI experienced by receivers R1, R2 and R3

R1 R2 R3 Select Equ Gain Maxratio0

0.05

0.1

0.15

0.2

Receiver

PER

PLR

PER + PLR

Fig. 9 PER, PLR and PER?PLR experienced by receivers R1, R2

and R3 without gPMSS diversity combining and with selection, equal

gain, and maximal ratio diversity combining

0.02 0.04 0.06 0.08 0.1 0.12 0.140

10,000

20,000

30,000

40,000

50,000

60,000

BER

#ofPackets

R1

R2

R3

SIMOSelection Div.

SIMOEqual Gain Div.

SIMOMaximal Ratio Div.

Fig. 10 Histogram of BERs observed by receivers R1, R2 and R3

without gPMSS diversity combining and with selection, equal gain,

and maximal ratio diversity combining

1182 Wireless Netw (2011) 17:11731189

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by all receivers, gPMSS either implements the function-

ality of an equal gain diversity or maximal ratio diversity

combiner. We have implemented both in C# for Imote2.

Using the Imote2, we conducted three experiments to

collect performance data that would enable us to evaluate

various gPMSS variants (selection diversity, selection

diversity with diversity combining). The three experiments

were conducted on August 16, 17 and 18, 2008 in a resi-dential environment on the campus of Michigan State

University. Receivers were arranged in a linear array with

inter-receiver separation of 0.25m. Each experiment span-

ned a period of approximately 7 hours. The transmitter was

placed at a distance of 8 m outside of the line-of-sight of

the receivers.

The maximal ratio diversity combiner depends on the

CSI-driven BER model by Ilyas and Radha [16]. Since the

BER model takes as input an LQI, RSSI pair k, q we still

need to map it to a probability value. In the first instance we

find the 90th percentile value of the BERs predicted PDF,

i.e. the BER for which the value of the cumulative distri-bution function (CDF) is 0.9. In the second instance we map

PDFs of the BER to their corresponding 50th percentile. We

analyze the performance of the gPMSS protocol in a setting

with one transmitter and N = 3 receivers. The receivers run

a complete implementation of the gPMSS protocol descri-

bed in Sect. 4. For the experiment the timeout constants

were set to T0 = 2 sec, T1 = 10 sec, T2 = 12 sec and

TT = 30 sec. We deliberately chose large values for T1, T2and TT to avoid synchronization issues and justify them by

the low-rate nature of target applications for IEEE 802.15.4.

For the time being we have not attempted to optimize them

to maximize throughput while still avoiding synchronization

problems. The experiment was conducted at a residence with

moderate Wi-Fi network interference.

7 Results and analysis

This section analyzes and compares PRR, energy per

packet and effect of retransmission limits on packet

delivery rate with and without gPMSS.

7.1 Packet reception rate

We denote the total number of transmissions made from

transmitter T by CT, and the number of retransmissions

among them by CR. Similarly, the number of transmitted

packets that are received at R1, R2 and R3 without errors

are denoted by C1, C2 and C3, respectively. Finally, CS

denotes the number of packets for which diversity com-

bining was attempted and succeeded, and CF the number

of packets for which it failed. All these values are tabulated

in Table 1. Each row in the table corresponds to a trial

experiment using a variant of gPMSS specified in the first

column. The results presented here are for three variants,

(a) Maximal-ratio combining using b90% for the BER point

estimate, (b) Maximal-ratio combining using the b50% for

the BER point estimate, and (c) equal gain combining. To

make sense of the packet counts in Table 1 and quantita-

tively assess the benefits of using only selection diversity,

and using selection diversity in conjunction with maximal-ratio/ equal gain combining we look at PRRs, denoted by h.

Columns (1), (2) and (3) in Table 2 contain the PRRs of the

baseline configuration in which receivers R1, R2 and R3 do

not cooperate. Column (4) contains the PRR when gPMSS

is used with the diversity combination method in column

(0). Some of the packets received using gPMSS will have

been received as a result of selection diversity, while others

will have been recovered as a result of diversity combining.

The following columns separate the gain in PRR over that

in the baseline configuration by providing the additive

increase in PRRs of individual receivers. Columns (5), (6)

and (7) are additive contributions of selection diversity inhgPMSS to the PRRs of individual receivers. Thus,

DhSD;R1;DhSD;R2 and DhSD;R3 are the increments in the PRR

with respect to their respective baseline performances hR1,

hR2 and hR3 in non-cooperating mode. Finally, column (8)

is the additive contribution of diversity combining DhDC to

the PRR hgPMSS of the system with gPMSS. Thus, since the

PRR gains in columns (5), (6), (7) and (8) are all additive

the relationship between the terms in Table 2 is,

hgPMSS hR1 DhSD;R1 DhDC

hR2 DhSD;R2 DhDC

hR3 DhSD;R3 DhDC: 9

7.2 Channel capacity

In this section we compute the channel capacity of using a

single hop to R1, R2 or R3, use selection diversity as well

as the full implementation of gPMSS. Capacity is denoted

by K and computed as,

Capacity K # of information bytes transferred

#of bytes transmitted by all nodes: 10

This way the channel capacities KR1, KR2 and KR3 observed

when R1, R2 and R3 receive can be computed from thepacket counts in Table 1 as,

Table 1 Packet counts

Div comb CT CR C1 C2 C3 CS CF

Exp1: max-ratio b90% 3,170 855 937 893 957 597 0

Exp2: max-ratio b50% 4,167 1,039 1,254 1,322 1,198 739 0

Exp3: equal gain 3,683 879 819 844 825 497 0

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KR1 C1 LDAT

CTLDAT C1LACK;

KR2 C2 LDAT

CTLDAT C2LACK;

KR3 C3 LDAT

CTLDAT C3LACK:

11

Here, LDAT and LACK denote the lengths (in bytes) of

data (51 bytes) and acknowledgement packets (5 bytes).

When selection diversity is used the channel capacity KSDis computed as,

KSD CT CR CS LDAT

CTLDAT CT CR CS LACK: 12

When selection diversity is used in conjunction with

diversity combining the channel capacity KgPMSS is

computed as,

KgPMSS CT CR LDAT

CT CR LACK CS2LDAT 2LACK:

13

Table 3 displays the channel capacities for 1-hop,

selection diversity and gPMSS. Clearly, channel capacity

is significantly higher than the 1-hop communication

configurations for both selection diversity and gPMSS.

The channel capacities can be better evaluated by plotting

each against the corresponding PRR in Table 2. This isshown in Fig. 13. This figure shows the tradeoff that

comes with using selection diversity and gPMSS. The

cluster of data points produced by selection diversity

increases both channel capacity as well as PRR. Adding

further complexity and using gPMSS increases PRR

further, but at the cost of a slight drop in channel

capacity. Data points for the same mechanisms (SISO, SD,

gPMSS) are clustered together, demonstrating consistency

across experiments.

7.3 Energy per packet

In this section we compute separately the energy expended

by the transmitter T as well as the receiver cluster R1, R2

and R3 per error free packet communicated to any one

receiver. We begin by computing the power consumed

in transmitting and receiving data packets (DAT) and

acknowledgement packets (ACK). Most of the additional

power consumption during transmission/reception opera-

tions in an Imote2 occurs in the TI Chipcon CC2420 RF

transceiver. The bulk of the remaining power consumption

occurs in the Intel PXA271 XScale processor. According

to measurements performed by Barton-Sweeney at Yale

Universitys ENALAB [3], the power management IC

(PMIC) on the Imote2 operates at approximately 90%

efficiency, supplying on-board devices (XScale processor,

CC2420 RF transceiver) approximately 4.0 V. When the

processor operates at 104 MHz, the total current drawn by

the Imote2 is reported to be 68.70 mA when the radio is

active, and 48.10 mA when it is idle. The difference of

20.60 mA is the current drawn by the CC2420 RF trans-

ceiver when it is transmitting/receiving. The Imote2 data-sheet reports that the current drawn by the Imote2 with

processor running at 104 MHz and active radio to be 66

mA, which is in close agreement with the measured value

[12]. Furthermore, the CC2420 RF transceivers datasheet

states that current drawn during transmission is 17.40 mA

and during reception is 19.70 mA [23]. These two values

are very close to each other and are also in close agreement

with the measured value of 20.60 mA. Since the Intel

XScale processor is not put into any low-power mode at

any time its power consumption remains constant. The

variations in power consumption due to gPMSS are due to

variations in power consumption by the CC2420 RFtransceiver produced by transmit/receive operations.

Although Barton-Sweeneys measurements do not distin-

guish between transmit and receive operations of the RF

transceiver, they are made in the configuration it is used by

the Imote2, whereas the numbers provided in the CC2420

datasheet are for a wide range of supply voltages. For this

reason, after verifying Barton-Sweeneys reported mea-

surements with [12] and [23], we rely on them for the

remainder of the paper. Thus, the Imote2 consumes 274.80

Table 2 PRR of individual nodes without gPMSS, PRR with gPMSS protocol, PRR gain for individual receivers R1, R2 and R3 due to selection

diversity, and the PRR gain due to diversity combining

(0) (1) (2) (3) (4) (5) (6) (7) (8)

hR1 hR2 hR3 hgPMSS DhSD;R1 DhSD;R2 DhSD;R3 DhDC

Exp1: max-ratio b90% 0.29 0.28 0.30 0.73 0.25 0.26 0.24 0.19

Exp2: max-ratio b50% 0.30 0.31 0.29 0.75 0.27 0.26 0.28 0.18

Exp3: equal gain 0.22 0.23 0.22 0.76 0.40 0.39 0.40 0.13

Table 3 Channel capacity

Div comb KR1 KR2 KR3 KSD KgPMSS

Exp1: max-ratio b90% 0.285 0.272 0.291 0.508 0.483

Exp2: max-ratio b50% 0.290 0.305 0.278 0.536 0.504

Exp3: equal gain 0.217 0.223 0.218 0.582 0.546

1184 Wireless Netw (2011) 17:11731189

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mW power when the RF transceiver is active (and 192.40

mW when it is inactive).

We denote the energy consumed by the RF transceiver

in transmitting/receiving a single DAT packet by EDAT.

Similarly, the energy consumed in transmitting/receiving a

single ACK packet is denoted by EACK. Although IEEE

802.15.4 supports multiple data rates, in the Imote2 it is

fixed at the maximum 250 kb/s. That means, to transmit orreceive a data packet that is 41 bytes long, the RF trans-

ceiver expends approximately,

EDAT 274:8 103 W

250 103 bits=s 418 bits

360:54lJ

14

Similarly, the energy expended in transmitting or

receiving a 5 byte ACK packet is,

EACK 274:8 103 W

250 103 bits=s 58 bits

43:97lJ

15

More generally, the per bit energy consumed by the RF

transceiver is 1.099 lJ/b. Then the energy ET spent by the

transmitter T to transmit CT data packets during the course

of an experiment is CT 9 EDAT, and the energy expended

to acknowledge C1 acknowledgements from R1 is C1 9

EACK. The energy spent by receivers R1, R2 and R3 in

acknowledging these are ER1 = C1 9 EACK, ER2 = C2 9

EACK and ER3 = C3 9 EACK. Note that although energy is

consumed by motes in tasks other than radio transmissions,

the power consumed by computations is orders of magnitude

less. Since the gPMSS protocol has computationalcomplexity of O(N). We compute the energy per packet

consumed at the transmitter PT and the sum of energy

consumed by all receivers together PR as,

PT ET

# of packets recvd wo errors: 16

PR ER

# of packets recvd wo errors: 17

Thus, PTand PR are energy consumption rates of transmitter

and receivers obtained by normalizing by number of suc-

cessfully delivered packets. The number of successfully

delivered packets isR1for1and2hopSISO, CT - CR - CS

for selection diversity, and CT - CR for diversity combining.

Table 4 lists PT, the per decodable packet energy at the

transmitter, and PR, the per decodable packet energy at all

receivers (R1, R2 and R3) combined for all three experiments

(listed in column (0)) . In normal operating mode, RF trans-

ceivers receive all packets transmitted by nodes within com-

munication and interference range. Motes inspect the MAC

address in received packet headers to match its own. If it is

determined that it is theintended recipient thepacket is passed Table4

Energyconsumedbytran

smissionsattransmitterandreceiversidepererror-freereceivedpacket

(0)

(1a)

(1b)

(2a)

(2b)

(3a)

(3b)

(4a)

(4b)

Divcomb

PT

PR

PT

PR

PT

PR

PT

PR

Exp1:max-

ratiob90%

3.3

83EDAT

?

EACK

=

1263.6

8lJ

10.1

49EDAT

?

3

EACK

=

3791.0

3lJ

4EDAT

?

4

EACK

=

1618.0

4

lJ

6EDAT

?

6

EACK

=

2427.0

6

lJ

1.8

45

EDAT

?

EACK

=

709.1

7

lJ

5.5

35EDAT

?

3

EACK

=

2127.5

0

lJ

1.3

69

EDAT

?

EACK

=

537.55

lJ

3.7

74EDAT

?

4.5

48

EACK

=

1560.6

5lJ

Exp2:max-

ratiob50%

3.3

23EDAT

?

EACK

=

1242.0

4lJ

9.9

69EDAT

?

3

EACK

=

3726.1

3lJ

4EDAT

?

4

EACK

=

1618.0

4

lJ

6EDAT

?

6

EACK

=

2427.0

7

lJ

1.7

44

EDAT

?

EACK

=

672.7

5

lJ

5.2

32EDAT

?

3

EACK

=

2018.2

6

lJ

1.3

32

EDAT

?

EACK

=

524.21

lJ

3.7

08EDAT

?

4.4

16

EACK

=

1531.0

5lJ

Exp3:equal

gain

4.4

97

EDAT

?

EACK

=

1665.32

lJ

13.4

91EDAT

?

3

EACK

=

4995.9

6lJ

4EDAT

?

4

EACK

=

1618.0

4

lJ

6EDAT

?

6

EACK

=

2427.0

4

lJ

1.5

96

EDAT

?

EACK

=

619.3

9

lJ

4.7

88EDAT

?

3

EACK

=

1858.1

8

lJ

1.3

14

EDAT

?

EACK

=

517.72

lJ

3.5

31EDAT

?

4.0

62

EACK

=

1451.6

7lJ

Columns(1a)and(ab)correspondtothe

baselinescenariousingonlyretransmissions.Columns(2a)and(2b)areforthescenariowherethe

singlehoplinkfromTtoR1isreplacedbya2ho

plink,

i.e.

fromTtoT0

toR1.

Columns(3a)and(3b)correspondtothecasewhenonlyselectiondiversityisusedbyreceivers.

Columns(4a)and(4b)correspondstothecasewhereafullimplementationofgPMSSisusedthatemploysdiversity

combining(equalgainormaximal-ratio

)inadditionwithselectiondiversity

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on to higher layers. Otherwise it is discarded. Therefore,

unless otherwise noted, RF transceivers receive all transmis-

sions within communication range. Thus, they expend energyto receive a packet, even when they are not the intended

recipient.

1-hop SISO Columns (1a) and (1b) in the table corre-

spond to the baseline case when gPMSS is not used and

packets received by R1 are retransmitted.

Lossless 2-hop SISO Columns (2a) and (2b) assume a 2

hop link from Tto R1 with an intermediate node acting as a

relay. This scenario is an alternative basis for comparison

of gPMSS. It is assumed that both links (from T to relay,

and from relay to R1) are perfect, i.e. no retransmissions

are needed. Obviously, as the number of hops on the multi-

hop path used to replace a gPMSS link increases so does

the consumed energy. Energy consumed by the T and the

relay node are lumped together into PT.

Selection diversity Columns (3a) and (3b) correspond to

the case when only selection diversity is used by cooper-

ating receivers.

Diversity combining ? selection diversity Columns (4a)

and (4b) corresponds to the case where a full implementation

of gPMSS is used that employs diversity combination (equal

gain or maximal-ratio) in addition to selection diversity.

To keep the relationship general the tabulated values arein terms of EACK and EDAT. Figure 12 plots PT and PR (in

Joules) expended in experiments 1, 2 and 3 when using

maximal-ratio combining with b90%, maximal-ratio com-

bining with b50% and equal gain combining, respectively.

As in Table 4 we also evaluate energy for the cases when

1-hop SISO, 2-hop SISO and only selection diversity were

used. The ordering of transmitter power consumption rate

PT and receiver power consumption rates PR remains of

schemes remains mostly the same across experiments

across experiments and gPMSS variants. However, there is

significant variation in PT and PR when gPMSS is not used

versus selection diversity versus gPMSS. For all threeexperiments PT is highest when gPMSS is not used while

the corresponding receiver power consumption rate PR is

lowest. Opting to use selection diversity alone significantly

reduces PT for maximal ratio gain variants (Exp 1 and 2) by

about 42% and about 64% for equal gain variant (Exp 3). PRremains unchanged. Note from the previous section that this

is accompanied by a 25% (for Exp 1 and 2) and 40% (for

Exp 3) increase in PRR. Thus selection diversity is able to

provide significant power savings while increasing PRR at

the same time. When gPMSS is employed PT is reduced by

about 58% (for Exp 1 and 2) and 68% (for Exp 3) over the

baseline configuration not using gPMSS. However, this is

accompanied by an increase of approximately the same

amount of energy on the receiver side. Thus, it appears that

0 20 40 60 80 1000

5

10

15

20

m

g (%)

Exp1: w/o gPMSS

Exp1: MaxRatio 90%

Exp2: w/o gPMSS

Exp2: MaxRatio 50%

Exp3: w/o gPMSS

Exp3: Equal Gain

Fig. 11 Maximum number of transmission attempts m versus

delivery guarantee g(%)

Fig. 12 The energy in lJ

consumed by transmitter and

receivers per successfully

delivered packet

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gPMSS shifts some of the power consumption from the

transmitter side to the receiver side.

7.4 Packet transmission attempts

The number of times the IEEE 802.15.4 MAC will retry

transmitting a packet is controlled by the maxMaxFrame-

Retries attribute whose default value is set to 3 but can be

varied from 0 to 7 (refer to IEEE 80215.4 standard [1]). This

limit on the number of transmission attempts m for a packet

limits the maximum PRR that can be guaranteed to g. Con-

versely, we may ask what is maximum number of trans-

mission attempts m that the MAC must be allowed in order

to ensure that at least g% of packets are received without

errors? Figure 11 plots m against g for all three experiments.Clearly, to achieve any delivery guarantee g%, fewer

transmissions are required with gPMSS, regardless of

whether maximal-ratio or equal gain diversity combination

is used, compared to the case where gPMSS is not enabled.

For example, Fig. 11 shows that to achieve a 95% delivery

guarantee we have to allow 9, 9, 13 transmission attempts for

the channel conditions observed in experiments 1, 2 and 3.

Using gPMSS, however, the maximum number of trans-

mission attempts required to achieve the same delivery

guarantee g = 95% are 3, 3, and 3, respectively. Clearly, the

values of m required to achieve g = 95% without gPMSS

exceeds IEEE 802.15.4s capabilities. From the plot in

Fig. 11 we see that at IEEE 802.15.4s default value of

m = 4 the maximum achievable delivery guarantee for the

three experiments lies in the range 6575%.

8 Conclusions

We presented the gPMSS, a protocol-centric approach

to enable receiver cooperation and diversity combining

without requiring any changes to mote hardware or the IEEE

802.15.4 LR-WPAN standard. We described three principal

mechanisms enabled by gPMSS, namely selection diversity,

equal gain and maximal-ratio gain diversity combination.

We provide proof-of-concept and demonstrate gPMSS

efficacy by applying these diversity combining techniques

on bit error traces collected from a network of IEEE

802.15.4 motes. We demonstrate gPMSS by implementing iton the Intel Imote2 sensor mote running the .NET Micro

framework. We analyze the performance of gPMSS in terms

of PRR, retransmission attempts and power consumption per

delivered packet. We saw that gPMSS raises the PRR from

2230% to 7376%, a relative increase of 150245%. Since

gPMSS is a protocol-based solution it implies a messaging

overhead. We observe that power consumption by the

transmitter per correctly delivered packet is reduced up to

68%. We evaluated the effect of retry limit imposed by the

IEEE 802.15.4 standard of the on the packet delivery rate

that can be achieved. At the default retry limit of 3 ( m = 4),

gPMSS can achieve delivery rates of greater than 99%,against only 6575% when gPMSS is not used. Thus we

demonstrate that gPMSS is capable of raising PRR, making

use of highly lossy links feasible, thus reducing the number

of required retransmission attempts and reducing the energy

consumption rate of the transmitter per packet delivered.

gPMSS has direct application in the design of small-world

topologies in wireless networks to reduce the characteristic

path length and diameter of networks which facilitates ser-

vice discovery and the routing of high priority data in a

network. This has the advantage of not needing any addi-

tional hardware [25, 26], or adding wired connections [9,

22]. The extension of the effective communication range

also has applications in extending the lifetime of nodes

surrounding the base station in wireless sensor networks

subject to the funneling effect. The larger communication

range allows more nodes to communicate with the base

station directly and reduces the traffic load from nodes

positioned closer to the base station. More generally, gPMSS

can be used to connect weakly connected components of a

network by adding more links between nodes farther apart.

Acknowledgments This work was supported in part by NSF Award

CNS-0721550, NSF Award CCF-0728996, NSF Award CCF-

0515253, and an unrestricted gift from Microsoft Research.

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Author Biographies

Muhammad U. Ilyas received

his Ph.D. and MS degrees in

Electrical Engineering from

Michigan State University

(MSU), East Lansing, MI in

2009 and 2007, the MS degree in

Computer Engineering from the

Lahore University of Manage-

ment Sciences (LUMS), Lahore,

Pakistan in 2004, and the BE

(Honors) degree in Electrical

Engineering from the National

University of Sciences & Tech-

nology (NUST), Rawalpindi,

Pakistan in 1999. He is currently

Associate Professor in the Department of Electrical Engineering of the

School of Electrical Engineering & Computer Science (SEECS) at the

National University of Sciences & Technology (NUST), Islamabad,

Pakistan. Prior to that he was a Post-doctoral Research Associate

appointed jointly by the Department of Electrical & Computer Engi-

neering (ECE) and the Department of Computer Science & Engi-

neering (CSE) at MSU where he worked under the joint supervision of

Prof. Hayder Radha (IEEE Fellow) and Prof. Alex X. Liu.

1188 Wireless Netw (2011) 17:11731189

123
http://www.xbow.com/Products/productdetails.aspx?sid=179http://www.xbow.com/Products/productdetails.aspx?sid=179http://www.xbow.com/Products/productdetails.aspx?sid=164http://www.xbow.com/Products/productdetails.aspx?sid=164http://www.xbow.com/Products/productdetails.aspx?sid=164http://www.xbow.com/Products/productdetails.aspx?sid=164http://www.xbow.com/Products/productdetails.aspx?sid=179http://www.xbow.com/Products/productdetails.aspx?sid=179


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Moonseong Kim has received

the M.S. degree in Mathematics

from Sungkyunkwan Univer-

sity, Korea in August 2002, and

the Ph.D. degree in Electrical

and Computer Engineering from

Sungkyunkwan University,

Korea in February 2007. He was

a research professor at Sung-

kyunkwan University in 2007

and a visiting research associate

in Department of Computer

Science and Engineering,

Michigan State University, USA

in 20082009. Currently, he is a

patent examiner, Information and Communications Examination

Bureau, Korean Intellectual Property Office, Korea. His research

interests include wired/wireless networking, sensor networking,

mobile computing, and simulations/numerical analysis.

Hayder Radha received the

B.S. degree (with honors) from

Michigan State University

(MSU), East Lansing, in 1984,the M.S. degree from Purdue

University, West Lafayette, IN,

in 1986, and the Ph.M. and

Ph.D. degrees from Columbia

University, New York, in 1991

and 1993, respectively (all in

electrical engineering). He

joined MSU in 2000 as Associ-

ate Professor in the Department

of Electrical and Computer

Engineering. From 1986 to

1996, he was with Bell Laboratories. From 1996 to 2000, he worked

at Philips Research USA and became a Philips Research Fellow in

2000. His research interests include wireless and multimedia com-

munications and networking, stochastic modeling, and image and

video coding and compression. He has more than 25 patents in these

areas. He served as co-chair and editor of the ATM and LAN Video

Coding Experts Group of the ITU-T in 19941996. Dr. Radha is a

member of the IEEE Signal Processing Multimedia Technical Com-

mittee. He is a recipient of the Bell Labs Distinguished Member of

Technical Staff Award (1993), the Withrow Distinguished Scholar

Award (2003), and the Microsoft Research Content and Curriculum

Award (2004).

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on enabling cooperative communication and diversity

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