MEDICAL DEVICE PERFORMANCE IN IEEE 802.11 NETWORKS

Evaluating IEEE P11073.1.1 Use Case Scenarios in Wireless LANs

Amjad Soomro and Ruediger Schmitt

Philips Research North America, 345 Scarborough Road, Briarcliff Manor, NY 10510, U.S.A.

Keywords:

IEEE 802.11, IEEE P11073, IEEE P11073.1.1, 11073, 11073.1.1, WLAN, Wi-Fi, Medical use cases.

Abstract:

We study in this paper use of IEEE 802.11 wireless technologies for medical devices. The simulated use cases

are derived from the ones speciﬁed in IEEE P11703.1.1 document. We consider the use cases where a WLAN

using IEEE 802.11 is providing connectivity to medical, voice (VoIP) and IT applications simultaneously. This

use case is interesting to hospitals because it provides potential cost savings. We model IEEE 802.11e QoS

features and we use a wireless channel model with high and stable SNR to observe MAC protocol behavior.

Our results indicate that QoS of medical and VoIP devices is met when they operate in dedicated channels, that

is, without any IT and in good channel conditions. The inclusion of background IT load, affects QoS of both

medical devices and VoIP. We quantify the performance improvement for medical devices when using IEEE

802.11 voice category and compare it with using best-effort category. The power consumption of wireless

devices is not considered in this work.

1 INTRODUCTION

Use of wireless networking technologies in medical

environments is attractive due to the beneﬁts it pro-

vides to patients, hospitals and care providers. For ex-

ample, it alleviates the need for healthcare providers

to be near patients, enable ambulation of patients for

faster recovery and regular and frequent monitoring

of patient’s vital signs. The wireless technologies

also enable integration of patient data in electronic

health records. It is attractive for hospitals to use

wireless technologies because it gives them ﬂexibil-

ity to place and use medical equipment while reduc-

ing the chances of error due to increasing wire clut-

ter around patients. In home care scenarios it pro-

vides the convenience of connecting patient moni-

toring data to care givers while providing ease-of-

use. Furthermore, ubiquitous availability of wire-

less technologies makes it possible to provide health-

care services anytime, anywhere (IEEE Std P11073-

00101/D04, 2008; Istepanian et al., 2004).

However, unlike in wired communications where

typical available bandwidths are far in excess of needs

of medical equipment, a wireless network capacity is

often much lower and dependent on the wireless sig-

nal strength and signal-to-noise ratio (SNR) within a

coverage area. The dynamic nature of wireless chan-

nels affects the quality-of-service (QoS) provided to

medical equipment and it is critical to satisfy QoS for

life-critical medical applications, such as telemetry.

Also, whereas, in the past, bandwidths for medical ap-

plication were typically isolated and reserved by us-

ing VLAN (virtual local area network) technologies

and dedicated infrastructure, the wireless channel is

often used, or desired to be used and shared, by non-

medical applications such as email and web access. A

motivation for sharing the existing installed wireless

technologies with medical applications is signiﬁcant

cost savings achieved by doing so (Soomro and Cav-

alcanti, 2007).

Due to the fact that different medical applications

have different QoS requirements and service level

agreements (SLA) requirements, the dynamic nature

of capacity/throughput of a wireless channel and va-

riety of non-medical applications with varying data

trafﬁc characteristics, it is a non-trivial task to esti-

mate whether a given network would be able to sup-

port, in terms of QoS, a set of medical applications,

with a given wireless technology and channel condi-

tions and in presence of some set of non-medical IT

applications. The theoretical analysis provides some

insight (Mangold et al., 2003), however, the assumed

network trafﬁc conditions to arrive at the analytical

results do not correspond well with the expected use

case scenarios (Cavalcanti et al., 2007). Whereas,

311

Soomro A. and Schmitt R. (2009).

MEDICAL DEVICE PERFORMANCE IN IEEE 802.11 NETWORKS - Evaluating IEEE P11073.1.1 Use Case Scenarios in Wireless LANs.

In Proceedings of the International Conference on Health Informatics, pages 311-316

DOI: 10.5220/0001552603110316

 SciTePress

an experimental setup can also provide insights, it

is costly, labor intensive and it usually takes much

longer time than simulations. For example, it takes a

large amount of effort to assemble and conﬁgure large

number of terminals to use a particular set of applica-

tions. Moreover, it is often a non-trivial task to mea-

sure QoS parameters, such as delays and throughput

from live terminals. Therefore, we study the perfor-

mance in selected scenarios through network simula-

tions and compare the results. We use OPNET Mod-

eler software to do the wireless network simulations.

In this article, we ﬁrst give an overview of the

use case scenarios considered in IEEE P11073.1.1

standard - Guidelines for the Use of RF Technology

(IEEE Std P11073-00101/D04, 2008). We focus on

802.11 (Wi-Fi) technologies and its performance, and

therefore, we will cover in greater detail the use cases

which are expected to use WLAN technology and

stress the network. In section 2 we give a summary

of uses cases described in the IEEE P11073.1.1 stan-

dard. An overview of IEEE 802.11 technology and

different features which could provide capabilities to

differentiate medical trafﬁc and provide the needed

QoS is also given in this section. In section 3 we

describe the simulation model and scenarios that we

used to study and compare the performance achieved

with different 802.11 protocol modes, the number of

devices and the simulated medical and non-medical

applications. In section 4 we present and discuss our

simulation results. Finally, we end the paper with

concluding remarks in section 5.

2 IEEE P11073.1.1 USE CASE

SCENARIOS

IEEE P11073 group has undertaken effort to develop

guidelines for the use of RF wireless technologies

for point-of-care medical devices and it will be avail-

able as IEEEP1073.1.1 document (IEEE Std P11073-

00101/D04, 2008). The goal of the document is to

provide better understanding among all stake hold-

ers, for example, hospitals, care givers and patients

by having common view of the wireless technologies.

A review of the available and emerging wireless tech-

nologies, their capabilities and limitations, the ways

to conﬁgure/specify each, the relevant medical de-

vices and applications for each technology, and costs

and drawbacks are covered in the document. More-

over, the document includes several generic models

of typical healthcare use cases which could be used

to analyze, evaluate, compare and optimize differ-

ent wireless technologies and modes, or parameters

within each, for the intended use cases.

2.1 Use Case Overview

The IEEE P11073.1.1 standard has outlined several

use case scenarios which highlight the data charac-

teristics and QoS needs of the medical applications,

the number and type of such and network conﬁgura-

tions in which they are expected to be served. The

standard lists nine use case scenarios and they are:

1) Personal (Home/Mobile) Monitoring; 2) Sub-acute

cases involving telemetry and basic vital signs moni-

toring for a single patient in a room; 3) and 4) Increas-

ing complexity compared with (2) and ambulatory pa-

tients; 5) Cardiac patient moving through three areas;

6) Critical burn patient tracked from MedEvac to ER

to ICU through recovery; 7) Rescue and MedEvac;

8) Ancillary; and 9) Maternity. The reader is referred

to Appendix A in (IEEE Std P11073-00101/D04,

2008) for more details of these scenarios.

In this article we focus on the wireless local

area networking (WLAN) technologies, that is, IEEE

802.11 wireless networking, and, therefore, would

present the use cases where this technology is ex-

pected to be used. Among the use cases given in

(IEEE Std P11073-00101/D04, 2008), the use case 4

stresses the network most and in this case it is ex-

pected that trends of performance achievable in dif-

ferent IEEE 802.11 modes of the operation would be

easily observed. Therefore, we describe the use case

4 in detail next.

In the use case 4 there are sixteen patients and

each patient has some medical devices connected to

it. A patient is outﬁtted with a ambulatory monitoring

device, PWD (patient worn device), which transmits

5 ECG vectors. In addition to ECG, episodic SpO

and blood pressure measurements are transmitted rel-

atively infrequently; 1 and 15 min intervals, respec-

tively. There are wrist RFID (radio frequency identiﬁ-

cation) tags, Nurse PDA, laptop PCs and VoIP (voice-

over-IP) phones expected to operate in the scenario

as well. Since, we consider IEEE 802.11 networks

only; we exclude RFID and other technologies using

non WLAN networking from the scenarios we have

simulated. The QoS requirement for PWD is max-

imum latency of less than 500 ms and for VoIP the

max latency should be less than 100 ms. Our objec-

tive in the simulation runs is to estimate the expected

performance and QoS when WLAN is operating in

the offered load environment. Since, applications like

episodic SpO

and blood pressure measurements have

very low throughput requirements, we do not include

these in our simulation; doing so, does not affect the

general observations we make about the performance

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312

obtained in the scenarios.

2.2 Brief overview of IEEE 802.11

The IEEE 802.11 standard (IEEE Std. 802.11, 2007),

also known as Wi-Fi, speciﬁes a single medium ac-

cess control (MAC) protocol and multiple physical

layer (PHY) modes. The 802.11 b and g modes op-

erate in the 2.4 GHz band at data rates up to 11 Mb/s

and 54 Mb/s, respectively, whereas the 802.11a PHY

mode supports up to 54 Mb/s in the 5 GHz band. The

legacy standard works by using CSMA/CA protocol

in which the stations sense the channel before trans-

mitting a packet. This is implemented by a Dis-

tributed Coordination Function (DCF) and most cur-

rent IEEE 802.11 products use this mode. If multi-

ple transmissions overlap, the stations retry after ran-

domly selected backoff periods.

Subsequently, the 802.11e amendment (IEEE Std.

802.11e, 2005) has been proposed to enable QoS

support in 802.11. The 802.11e amendment de-

ﬁnes two basic mechanisms for QoS support, namely:

Enhanced Distributed Channel Access (EDCA) and

Hybrid Coordination Function Controlled Channel

Access (HCCA). In this work we consider the

EDCA mechanism, which provides prioritized QoS

by deﬁning four access categories: voice (AC VO),

video (AC VI), best-effort (AC BE) and background

(AC BK) trafﬁc. Up to four backoff entities operate

independently in a singe station, and each has its own

MAC layer queue. Each backoff entity is associated

with an access category and contends for the channel

with different priorities. The different access priori-

ties are realized by setting the following MAC layer

parameters: i) arbitration interframe space (AIFS),

which is the interval of time the medium has to be

idle before a backoff entity initiates a frame trans-

mission or starts counting down its backoff-counter;

ii) minimal and maximal contention window (CWmin

and CWmax), which determines the initial and max-

imum range of random backoff counter, respectively;

and iii) transmission opportunity limit (TXOP limit),

which is the duration during which the TXOP holder

maintains uninterrupted control of the medium.

3 SIMULATION ENVIRONMENT

We have simulated wireless networking scenarios us-

ing a customized 802.11e OPNET Modeler simula-

tion model. Figure 1 shows the simulated wireless

network conﬁgured as in scenario 3. In the model,

the terminals ‘STA x’ represent PWDs and VoIP ter-

minals are labeled as ‘VoIP x’. The terminals repre-

sented as ‘IT x’ run IT applications, such as, email

clients, web access clients, telnet sessions and are en-

gaged in ﬁle transfers using FTP protocol. The wire-

less access point is labeled as ‘AP’ and it is connected

to the application server through an ethernet switch.

Figure 1: Simulated network conﬁgured as in scenario 3.

3.1 Applications and Scenarios

Table 1 lists the applications, the transport layer pro-

tocol used, the size of the respective transmitted ob-

jects, the objects’ inter-arrival times (IAT), the appli-

cation data rate and the trafﬁc direction (UP: client

to server, DN: server to client). As can be seen, the

medical application, PWD, which includes one uplink

trafﬁc ﬂow from the client device to a medical server,

which is connected to the WLAN through an ethernet

switch. The VoIP trafﬁc is modeled after VoIP phones

running the commonly used G.711 voice codec. For

IT trafﬁc, we have considered a mix of FTP, E-mail,

HTTP, and Telnet applications. Thus, each IT station

used in our simulations includes all four applications

that form the IT proﬁle.

There are eight different simulation scenarios

which are summarized in Table 2. A set of four sce-

narios labeled 1 through 4 is run at the 802.11b PHY

rates 5.5 Mbps, labeled ‘a’ and 11 Mbps, labeled ‘b’.

The respective PHY rates are used by all wireless

nodes in a particular scenario. Throughout the sim-

ulations the VoIP trafﬁc always uses the EDCA voice

access category (AC VO) and the IT trafﬁc always

uses best effort access category (AC BE). The medi-

cal trafﬁc uses either the EDCA voice category or the

EDCA best effort category or DCF when using legacy

IEEE 802.11. The IEEE 802.11 parameters used in

simulations are given in Table 3.

Scenario 1 serves as a baseline scenario for PWD

MEDICAL DEVICE PERFORMANCE IN IEEE 802.11 NETWORKS - Evaluating IEEE P11073.1.1 Use Case Scenarios

in Wireless LANs

313

Table 1: Simulated Applications.

APP LINK

TRANS-

PORT

OBJECT

SIZE

(bytes)

IAT*

(ms)

RATE

(kbps)

PWD UP UDP Packet 312 125 20

VoIP

G.711

UP/

UDP Packet 33 20 64

FTP

UP/

TCP File 10

80 N/A

UP/

TCP Email 2000 20 N/A

HTTP DN TCP

Page 10k+

PIC 5×

(10–4000)

10 N/A

Telnet

UP/

TCP

Cmd

60-up/

25-down

30 N/A

* IAT: Inter-arrival time.

Table 2: Simulated scenario number description.

No.

Rate PWD VoIP IT

(Mbps) Units AC Units AC Units AC

1a 5.5

16 DCF 0 - 0 -

1b 11

2a 5.5

16 VO 8 VO 0 -

2b 11

3a 5.5

16 VO 8 VO 16 BE

3b 11

4a 5.5

16 BE 8 VO 16 BE

4b 11

trafﬁc running over 802.11b without other trafﬁc con-

tending for the medium. In scenario 2 PWD shares

the spectrum with VoIP and in scenarios 3 and 4 we

add IT trafﬁc. The difference between scenario 3 and

4 is the access category used by the PWD trafﬁc.

For all simulations the wireless nodes are non-

mobile and the SNR is greater than 25 dB, the min-

imum recommended SNR for VoIP in 802.11b net-

works (Cisco Doc-ID: 70442, 2008). In addition,

Cisco (Cisco 7920 Design Guide, 2005) recommends

maximum of eight VoIP calls at 60 % of WLAN band-

width. Note, that real world WLAN deployments in-

volve many radio frequency (RF) challenges such as

physical obstructions, interference and multipath ef-

fects which impact the channel capacity. These ef-

fects are not accounted for in our simulations.

Table 3: 802.11 parameters used in simulations.

PHY Parameters

PHY rate (Mbit/sec) 5.5/11

DCF

DIFS (µsec) 50

min

AC BE

AIFS (µsec) 70

min

TXOP Limit* 0

AC VO

AIFS (µsec) 50

min

TXOP Limit (msec) 3.264

* A TXOP Limit value of 0 indicates that a single data or management

frame may be transmitted during each TXOP.

4 RESULTS

In this section, we present and discuss the simulation

results. The performance metrics selected for applica-

tions within each proﬁle are described in Table 4. The

focus of the following performance evaluation is on

the end-to-end performance of each application, and

all performance metrics are measured at the applica-

tion layer. The data loss rate and end-to-end delay

are used as performance metrics only for streaming

applications that run over the UDP protocol, which

includes PWD and the VoIP applications. The data

loss rate for each application is calculated as the dif-

ference between all transmit and receive packets for

each application type (voice and PWD). The IT ap-

plications are evaluated by their throughput and the

average response time, which is the average time it

takes to download/upload a complete object such as

an email or ﬁle.

In scenarios 1 and 2 where only the PWDs and

the VoIP phones share the network in the same ac-

cess category both 5.5 Mbps and 11 Mbps PHY rates

are able to deliver adequate QoS with the average de-

lays of below 2 ms and the maximum jitter of 0.16 ms.

Note, that the channel quality in these two scenarios

was good with a minimum SNR of 36 dB.

In scenario 3 IT trafﬁc was added and the PWD

trafﬁc operated in the voice access category. We see

that the QoS for the VoIP applications is severely

compromised when the PHY rate of 5.5 Mbps is used

(scenario 3a). The VoIP data loss rate is close to 5 %

and the average delay reaching up to 200 ms. At the

same time, although the PWD trafﬁc uses the same

access category as the VoIP trafﬁc, the PWD perfor-

mance is acceptable with no data being lost and the

maximum delay of 5.3 ms.

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Table 4: Summary of results.

METRIC APPLICATION

SCENARIO

1a 1b 2a 2b 3a 3b 4a 4b

Average delay (ms)

PWD 1.0 0.6 2.0 1.0 5.3 3.0 507.6 23.1

VoIP - - 2.0 1.27 191.3 3.8 182.7 3.7

Jitter (ms)

PWD 0.04 0.02 0.13 0.05 0.63 0.29 248.6 10.4

VoIP - - 0.16 0.03 30.74 0.5 37.0 0.35

Loss rate (%)

PWD 0.0 0.0 0.0 0.0 0.0 0.0 0.31 0.2

VoIP - - 0.0 0.0 4.9 0.0 2.4 0.0

Throughput (kbps)

FTP - - - - 0.9 987.7 0.9 721.0

Email - - - - 31.6 38.0 23.5 40.3

HTTP - - - - 62.7 97.7 64.4 93.9

Telnet - - - - 0.3 0.3 0.3 0.3

Response Time (sec) Telnet - - - - 7.7 0.3 17.4 0.3

Upload Response

Time (sec)

FTP - - - - 267.5 18.1 N/A 125.6

Email - - - - 27.0 1.2 58.2 1.6

Download Response

Time (sec)

FTP - - - - N/A* N/A N/A N/A

Email - - - - 63.3 4.51 55.1 3.36

Page Response

Time (sec)

HTTP - - - - 6.2 4.2 5.4 4.8

* N/A: Transactions did not complete in simulation time.

0 50 100 150 200 250 30

−5

−4

−3

−2

−1

Simulation Time (sec)

MAC Delay (sec)

AP (avg=387.6 ms)

PWD (avg=2.9 ms)

VoIP (avg= 2.8 ms)

Figure 2: MAC delays at AP, VoIP and PWD stations.

In scenario 3a, upon closer inspection one can see

that the high packet loss rate and delay is experienced

by the downlink VoIP trafﬁc only. Figure 2 shows that

the MAC delay for the VoIP trafﬁc transmitted by the

AP is very high (387.6 ms) compared to the MAC de-

lays of a randomly chosen PWD (2.9 ms) and VoIP

phone (2.8 ms). The AP is contending for access to

the channel with the same priority as the VoIP phones

and PWDs, however it has to deliver a disproportion-

ately high trafﬁc load of 8 downlink VoIP streams and

is unable to do so. The new automatic power save de-

livery (APSD) mechanism deﬁned in IEEE 802.11e

could reduce this problem, as the AP would deliver a

downlink VoIP packet without having to contend for

the channel. The problem could also be mitigated if

the AP voice category used a higher channel access

priority than the non AP’s voice category.

When the physical data rate increased to 11 Mbps

the network capacity increases enough to provide ad-

equate QoS for VoIP and PWD trafﬁc with no packets

lost and an average delay of 3.8 ms and 3.0 ms respec-

tively. As expected, the IT trafﬁc beneﬁts from the

higher network capacity at 11 Mbps than at 5 Mbps re-

sulting in higher throughput and lower response times

as can be seen in Table 4.

Finally, in scenario 4, the PWD trafﬁc uses the

best effort category (AC BE) while VoIP and IT traf-

ﬁc continue to use AC VO and AC BE. In scenario

4a, as we have see in scenario 3a, the trafﬁc load ex-

ceeds the channel capacity at 5.5 Mbps. As a result,

both VoIP and PWD experience severe QoS degrada-

tion. While moving the PWD trafﬁc to a lower ac-

cess category slightly improved the VoIP trafﬁc per-

formance, the average delay is still unacceptably high

at 182.7 ms and so is the loss rate at 2.4 %. Figure 3 il-

lustrates the problems of delivering 800 VoIP packets

per second (the number of packets for eight calls in

one second) in the scenarios with PWD and IT traf-

ﬁc and a PHY rate of 5.5 Mbps. The performance

of the PWD application worsened dramatically with

MEDICAL DEVICE PERFORMANCE IN IEEE 802.11 NETWORKS - Evaluating IEEE P11073.1.1 Use Case Scenarios

in Wireless LANs

315

0 50 100 150 200 250 300

100

200

300

400

500

600

700

800

900

Simulation Time (sec)

VoIP Packets Received (pkts/sec)

Scenario 3a

Scenario 4a

Figure 3: VoIP packets received in scenarios 3a and 4a.

the average delay rising to 507.6 ms and a loss rate of

0.31 %.

5 CONCLUSIONS

Our ﬁndings can be summarized as follows:

1) As a network becomes more congested the chan-

nel access category used by a node such as a PWD

becomes more important for guaranteeing the re-

quired QoS. We recommend putting the medical

trafﬁc in the highest priority access category; and,

2) When the wireless nodes experience poor chan-

nel quality and lower their transmission rate the

channel capacity is reduced and the recommended

VoIP capacity for 802.11b can no longer be sup-

ported by the network.

In this paper we have estimated the QoS lev-

els achieved by applications, speciﬁcally IEEE

P11073.1.1 use case scenarios, while sharing a wire-

less channel. The knowledge gained by this work

would help in designing an IEEE 802.11 wireless net-

work in medical environments, for example, in hospi-

tals, and estimating the QoS in the designed system.

In the scenarios that we examined good channel

conditions were assumed. However, in real-world

situations, some safety marigns are included in the

design speciﬁcations because: i) the channel is dy-

namic due to multipath fading; ii) the portable de-

vices are mobile and channel conditions deteriorate

at the fringes of the coverage areas; and, iii) there

are vendor-to-vendor and device-to-device variations.

Another interesting metric, which we did not consider

in this paper, is the power consumption of the PWD

devices. The power consumption of PWD in power

save mode will increase as the network load reaches

the channel capacity and more retransmissions oc-

cur due to contention increase. Because of the above

stated reasons and prudent safeguards for life-critical

applications, a network may have to be operated much

below the capacity obtained in our simulations.

ACKNOWLEDGMENTS

The authors would like to thank Phil Raymond, Dale

Wiggins, Jan Wittenber and reviewers for their com-

ments and suggestions.

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