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8/3/2019 On Enabling Cooperative Communication and Diversity
1/17
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
e-mail: [email protected]
H. Radha
e-mail: [email protected]
123
Wireless Netw (2011) 17:11731189
DOI 10.1007/s11276-011-0338-7
8/3/2019 On Enabling Cooperative Communication and Diversity
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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
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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
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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
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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
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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
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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
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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=1798/3/2019 On Enabling Cooperative Communication and Diversity
17/17
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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