Coverage Range Analysis of Wireless Technologies for Industrial

Automation

System Overview and Performance Evaluation

Armin Wulf, Lisa Underberg and Rüdiger Kays

Communication Technology Institute, TU Dortmund University, Otto-Hahn-Str. 4, 44221 Dortmund, Germany

Keywords:

Coverage Range, Error Rates, FHSS, Industrial Communication, PSSS, UWB.

Abstract:

Reliable wireless communication is crucial to current and future industrial applications, but is however not

yet applicable in many scenarios. Thus novel approaches are being investigated at the moment, from which

three physical (PHY) layer technologies are depicted for detailed evaluation in this paper. Preceding the

performance analysis, industrial application requirements and constraints as spatial extent, number of nodes,

cycle time, PER and user data length are summarized. Error rates and coverage ranges are calculated and

presented for Ultra Wide Band (UWB), Frequency Hopping Spread Spectrum (FHSS) and Parallel Sequence

Spread Spectrum (PSSS) assuming an AWGN channel.

1 INTRODUCTION

Currently wired ﬁeldbus systems are employed in in-

dustrial applications due to their deterministic per-

formance, although they entail high installation and

maintenance efforts. Thus wireless communication is

desirable, since it offers advantages regarding ﬂexi-

bility, mobility and retroﬁtting. Nevertheless, most

wireless communication systems do not yet meet the

applications’ requirements in determinism and qual-

ity of service. In order to overcome these challenges,

novel wireless solutions are being developed at the

moment. The applications are often categorized by

ﬁeld of operation and major requirements like num-

ber of nodes, cycle time, Packet Error Rate (PER) and

user data length. Based on the resulting categories,

wireless systems have to be scaled for each ﬁeld of

application, and the choice of the physical layer tech-

nology is an important consideration in this context.

Though the deﬁnition of application categories is

of vital signiﬁcance for a successful system design,

it is not consistent in industry, research and standard-

ization resulting in diverse speciﬁcations. Moreover,

currently no de facto standard is established. Thus in-

dustrial requirements are investigated and aggregated

in section 2. UWB, FHSS and PSSS are shortly intro-

duced as promising wireless approaches in section 3

and discussed regarding their suitability in terms of

error rates and coverage range in section 4. Summary

and prospect on further work are given in section 5.

2 INDUSTRIAL ENVIRONMENT

Summarizing industrial application categories, a sur-

vey on their requirements is given in this section.

These requirements comprise network size, environ-

ment and topology, safety as well as timing limita-

tions. Moreover, possible frequency ranges are pre-

sented and reviewed regarding regulatory aspects.

The summary reveals challenging conditions for

wireless industrial communication in all application

categories. As a result physical layer concepts must

be chosen carefully regarding reliability and coexis-

tence aspects.

2.1 Application Requirements

The requirements of industrial applications vary

broadly and are commonly classiﬁed into three cat-

egories to ease considerations: Factory Automa-

tion (FA), Process Automation (PA) and Condition

Monitoring (CM). In a factory environment the spatial

extent as well as the number of nodes are evidently

small, whereas the reliability and safety requirements

are very strong. Typically closed-loop communica-

tion systems with soft or hard real time requirements

are employed here. In contrast to this, CM has a wide

spatial extent and lower safety and timing require-

ments in its sensor network, which has no control

but only monitoring purposes. PA is typically associ-

ated with chemical processing plants, which have an

Wulf, A., Underberg, L. and Kays, R.

Coverage Range Analysis of Wireless Technologies for Industrial Automation - System Overview and Performance Evaluation.

DOI: 10.5220/0005971600740083

In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - Volume 6: WINSYS, pages 74-83

ISBN: 978-989-758-196-0

Table 1: Application requirements overview. (ETSI, 2011), (ZVEI, 2009), (VDI/VDE, 2007), (Güngör, 2013) (Frotzscher

et al., 2014).

Property FA PA CM

Maximum spatial extent 10 m × 10 m ×3 m 100 m × 100 m ×10 m 1000 m × 1000 m × 50 m

Nodes per system 30 100 1000

Nodes per m

0.3 0.01 0.001

Number of coexistent systems 10 5 5

Number of locally parallel nodes 300 500 250

Network topology Star Star/Mesh Mesh

Cycle time <1 ms >10 ms >100 ms

PER <10

−9

<10

−4

<10

−3

Battery lifetime <1 year 5 – 10 years >10 years

User data length <30 Byte 30 – 1500 Byte <1500 Byte

System data rate >7.2 Mb/s <2.4 – <120 Mb/s <120 Mb/s

intermediate spatial dimension and also intermediate

safety and timing requirements. Often PA comprises

mostly monitoring tasks with few control processes.

Depending on the very deployment, the topology is

typically either a star or a mesh network as shown in

ﬁgure 1.

In FA, a star topology provides a good basis for

the small spatial extent combined with shortest cycle

times and high data rate. A typical industrial scenario

is a production cell, in which sensors and actuators

both interact on a real time basis. In a CM applica-

tion, sensors mostly collect data, which need to be

transmitted over long distances due to the big spatial

dimension, whereas timing requirements are low.

Thus here a mesh topology with multi-hop trans-

missions is employed. In case of a star topology, the

coexistence of multiple communication structures is

required, which both means the coexistence of dif-

ferent systems (inter-system-coexistence) and the co-

existence of different star topologies employing the

same technology (intra-system-coexistence).

Table 1 shows major properties of these three cat-

egories compiled from various publications. (ETSI,

2011) lists requirements of communication in manu-

facturing cells, factory halls and on plant level. Typi-

cally FA is employed in manufacturing cells, whereas

communication on factory hall scale is congruent with

PA properties. Communication on plant level is a

subset of CM, but is generally matching CM require-

ments. Spatial extent, nodes per system, number of

Star topology Mesh topology

Figure 1: Typical topologies in industrial environments.

coexistent systems, number of locally parallel nodes

and the network topologies are taken from this report.

Nodes per m

is calculated based on these values.

Similar categories are investigated in (VDI/VDE,

2007), from where cycle time and user data lengths

values are taken. They are congruent with require-

ments speciﬁed in (Frotzscher et al., 2014), where

three closed-loop systems (machine tools, printing

and packaging machines) are listed with their require-

ments in number of nodes, packet size, cycle time

and jitter. Limits for packet error rates are deﬁned

in (ZVEI, 2009), which discusses primarily coexis-

tence issues regarding wireless industrial communi-

cation. The system data rate is calculated based on

number of nodes and user data lengths.

Today in the ﬁelds of FA and PA established wired

ﬁeldbus systems based on Ethernet are employed due

to the strict deterministic performance of these wired

communication systems. In contrast to that, CM re-

cently emerged in terms of machine-to-machine com-

munication and the Internet of Things (IoT), because

wired systems cannot yield the required ﬂexibility.

For all three categories wireless communication is de-

sirable and enables a raise of efﬁciency while reduc-

ing installation and maintenance efforts.

2.2 Frequency Ranges for Industrial

Communication

At this time there are no dedicated frequency ranges

for wireless industrial communication, thus Indus-

trial, Scientiﬁc, and Medical (ISM) bands have

to be used, which offer three relevant frequency

bands: Sub-1 GHz (868 MHz in Europe and Africa

and 900 MHz in America respectively), 2.4 GHz and

5.8 GHz (ETSI, 2010) (FCC, 2016). Especially the

2.4 GHz band is broadly employed posing a challenge

to each technology’s coexistence techniques. Since

Coverage Range Analysis of Wireless Technologies for Industrial Automation - System Overview and Performance Evaluation

coexistence of wireless communication systems is

crucial for wide usability, there are regulations in each

ISM band, which enable the inter-system-coexistence

of different technologies. Either the allowed trans-

mission power is small or users have to apply “listen

before talk” (LBT). LBT is inappropriate for FA and

partially for PA as well, since the transmission delay

is not predictable.

Due to the great interest, ETSI initiative TG41,

who aims at a regulation guaranteeing exclusive use

of 5.725 GHz to 5.875 GHz for wireless industrial

communication systems, was formed. Here the trans-

mit power is planned to be increased from 14 dBm

to 26 dBm EIRP (ETSI, 2010). An exclusive use of

a dedicated frequency band leads to less interference

between different technologies, but reinforces the im-

portance of intra-system-coexistence.

A different approach is the use of large frequency

ranges as in UWB (IEEE, 2011) technologies. Here

the employed bandwidth is equal to or larger than

499.2 MHz, which provides high interference resis-

tance owed to its spreading concept. There are three

operating bands deﬁned: sub-gigahertz band from

249.6 MHz to 749.6 MHz, low band from 3.1 GHz to

4.8 GHz, and high band from 5.8 GHz to 10.6 GHz.

3 WIRELESS TECHNOLOGIES

Since the PHY layer technology vigorously affects

the overall system performance, it must be carefully

chosen for a certain ﬁeld of operation. The range of

available technologies from wireless standards and re-

cent research projects is wide. It reaches from UWB

technologies, that promise coexistence with existing

wireless systems, to 5G cellular machine to machine

(M2M) solutions, which can cover large areas and

huge numbers of devices. With its Orthogonal Fre-

quency Division Multiple Access (OFDMA) and Sin-

gle Carrier Frequency Division Multiple Access (SC-

FDMA) schemes for downlink and uplink and the

enhancements from LTE Rel-11, 5G seems to be a

promising approach for PA and CM, but its laten-

cies are not capable of meeting the FA requirements.

Another promising technology for PA applications is

Sub-1 GHz-WLAN in IEEE 802.11ah, which shall

achieve low-cost long range connectivity (Aust et al.,

2015).

Technologies like ZigBee (ZigBee Alliance,

2012) with its star, mesh and cluster tree topologies

are rather suitable for CM purposes. A recent ap-

proach that is also based on the IEEE 802.15.4 stan-

dard and covers industrial applications in the ﬁelds

of FA and PA is WirelessHART (IEC, 2010). An-

other choice, based on the IEEE 802.15.1 standard, is

Wireless Sensor Actuator Network (WSAN), which is

designed for FA and coexistence with common tech-

nologies in the 2.4 GHz ISM band (PNO, 2012). Nev-

ertheless, these standards cover the FA requirements

insufﬁciently, so that wireless communication tech-

nologies, which meet the FA requirements, are current

research topics.

Among others, UWB, FHSS and PSSS are subject

of FA standard PHYs and recent research projects.

These three promising wireless technologies are de-

picted for further analysis.

3.1 UWB Overview

In order to realize short-haul links for data com-

munication for low power and low rate devices

in a Wireless Personal Area Network (WPAN) the

IEEE 802.15.4a standard offers several PHY trans-

mission modes (IEEE, 2011). The investigated Im-

pulse Radio (IR)-UWB PHY speciﬁcation supports

data rates from 0.11 Mb/s to 27.24 Mb/s with differ-

ent Modulation and Coding Schemes (MCS). The

IR-UWB impulses are modulated using burst posi-

tion modulation (BPM) and binary phase shift keying

(BPSK). In the BPM-BPSK modulation scheme two

bits of information are carried in each UWB symbol.

The ﬁrst bit is determined by the burst’s temporal po-

sition and the burst’s polarity indicates the second bit.

A complete burst is speciﬁed by a spreading sequence

deﬁning the polarity of it’s impulses (IEEE, 2011).

BPM

Burst positions (N

hop

)

dsym

burst

cpb

Guard interval

Burst positions (N

hop

) Guard interval

BPM

. . .

Figure 2: IEEE 802.15.4a IR-UWB PHY symbol struc-

ture (IEEE, 2011).

The structure of an IR-UWB PHY symbol is

shown in ﬁgure 2. T

dsym

is referred to as total sym-

bol duration, T

as chip duration and N

cpb

as number

of chips per burst. T

BPM

is the duration of a BPM

interval and T

burst

corresponds to the burst duration.

In table 2 the signiﬁcant parameters of selected

IR-UWB MCSs are listed including the FEC rates of

convolutional coding (CC) and Reed-Solomon (RS)

coding.

WINSYS 2016 - International Conference on Wireless Networks and Mobile Systems

Table 2: IR-UWB PHY Parameters.

MCS

Rate Rate

cpb

dsym

Data rate

CC RS [ns] [Mb/s]

1 0.5 0.87 128 8205.13 0.11

2 0.5 0.87 16 1025.64 0.85

3 0.5 0.87 2 128.21 6.81

4 1 0.87 1 64.10 27.24

With the large number of adjustable parameters, the

IR-UWB PHY is adaptable to different communica-

tion scenarios from FA, PA and CM. In order to suit

best for FA scenarios, delay requirements have to be

met, and therefore MCS 4 is investigated in this pa-

per. MCS 4 has a symbol duration T

dsym

of 64.10 ns

and reaches a data rate of 27.24 Mb/s with coherent

reception (Reinhold, 2016).

Due to regulatory aspects such as duty cycle and

power restrictions the high band with a mandatory

channel at 7.9872 GHz is depicted for performance

evaluation in section 4.3.2.

3.2 FHSS Overview

FHSS is one of the most common transmission tech-

niques for automation and sensor networks. In order

to achieve coexistence between multiple connections

and to enhance the transmissions’ robustness, the

transmission channel is changed frequently, whereby

the hopping frequency can vary among the technolo-

gies from 1600 Hz up to static channel usage. For

most frequency bands this type of frequency usage is

covered by regulations (FCC, 2016).

An established standard using FHSS spectrum ac-

cess is Bluetooth LE (Bluetooth SIG, 2014). It is

primarily designed for IoT tasks, but there are also

variations for FA available. WSAN (PNO, 2012) has

a PHY layer based on the IEEE 802.15.1 standard

(IEEE, 2005), which also serves as a basis for Blue-

tooth up to version 1.2. The system operates within

the 2.4 GHz ISM band and uses a FHSS mechanism

with 79 channels, each occupying a nominal band-

width of 1 MHz. WSAN additionally uses a hopping

scheme allowing the parallel usage of multiple base

stations and supports channel blacklisting as a coex-

istence feature.

In this work we consider a FHSS system with a

Gaussian Minimum Shift Keying (GMSK) modula-

tion scheme adopted from Bluetooth LE and WSAN

operating in the 5.8 GHz ISM band. The 150 MHz of

available system bandwidth are divided into 75 chan-

nels resulting in a channel center frequency distance

of 2 MHz (Bluetooth SIG, 2014) (FCC, 2016) (ETSI,

2010). The channel center frequencies result as

= 5726 MHz + (i − 1) · 2 MHz,

i = 1 . . . 75

(1)

with the channel number i.

3.3 PSSS Overview

In order to enhance response times due to paral-

lel access, spread spectrum techniques offer promis-

ing properties. In contrast to Direct Sequence

Spread Spectrum (DSSS)-techniques, where each bit

is spread with an appropriate pseudo noise (PN)-

sequence, PSSS is an approach based on spread-

ing with a m-sequence. It was ﬁrstly presented in

(Wolf, 2004; Schwetlick and Wolf, 2004) and is,

based on an m-sequence of length 31 chips, part of

IEEE 802.15.4-2011 (IEEE, 2011), but in general any

m-sequence is applicable. A detailed description of

PSSS en- and decoding is given in (KrishneGowda

et al., 2015), whereas a short overview is given in this

paper.

Channel

Cyclic

Correlation

c c





Mod

Demod

...

Figure 3: PSSS coding and decoding process.

The bits of the data vector d are spread each with the

same, but cyclically shifted, m-sequence of length n

as shown in Figure 3, where m

→0

denotes the basic

m-sequence. Correspondingly, m

→i

denotes the same

sequence cyclically shifted by i chips. Thus up to n bit

can be transferred in parallel in one PSSS symbol.

The transmitted PSSS symbol c is multivalent due to

the chipwise addition of the spread bits of d. An ar-

bitrary modulation scheme can be used for transmis-

sion. For the analysis in section 4.3 a Amplitude Shift

Keying (ASK) is utilized.

The PSSS decoding is performed by cyclic cor-

relation of the received multivalent PSSS sequence

with the basic m-sequence. A longer m-sequence

leads to a more reliable result of the cyclic correlation

assuming a uniform distribution of data bits. This ef-

fect is shown in section 4.3.

3.4 Technology Comparison

Though all three described technologies are promis-

ing in terms of wireless industrial communication,

their properties diverge. An overview of relevant

Coverage Range Analysis of Wireless Technologies for Industrial Automation - System Overview and Performance Evaluation

properties is shown in ﬁgure 4 based on the assump-

tions made in table 3 in section 4.3.2. UWB uses a

bandwidth of 499.2 MHz with one channel per sys-

tem, and achieves a total data rate of 31.2 Mb/s.

FHSS employs 75 channels with 1 Mb/s data rate

each resulting in a system data rate of 75 Mb/s. The

depicted conﬁguration utilizes all available channels

for a single system. For cellular coverage of the fac-

tory ﬂoor, the system can also be rescaled by reducing

the number of utilized channels, making a coexistence

of parallel systems possible. For a 3 × 3 pattern eight

channels can be utilized per system in average, when

inter-system interference is avoided.

Here, PSSS is exemplarily assumed to be em-

ployed based on a m-sequence with a length of

255 chips, which is further denoted as PSSS 255. Up-

and downlink provide a number of 255 channel occu-

pying a bandwidth of 20 MHz each. Accordingly the

total system bandwidth is 40 MHz. The link data rate

amounts to 78 kb/s resulting is a total system data rate

of 40 Mb/s. If the link data rate of a single link is too

small, multiple links can be grouped and thus a larger

data rate is achieved, but concomitantly the number

of simultaneous nodes in service is reduced. In PSSS,

the system data rate can be shared at any desired frag-

mentation.

Link

data rate

System

data rate

Channels per

system

Maximum

system bandwidth

Number of

parallel systems

0.1

100 Mb/s

100

MHz

UWB MCS4

FHSS

PSSS 255

Figure 4: System capacities.

4 SYSTEM EVALUATION

The proposed PHY technologies are investigated in

the subsequent sections regarding their applicability

for FA. Based on the Bit Error Rate (BER) analysis,

the coverage ranges are considered for typical packet

sizes based on an AWGN channel model. The tech-

nologies’ feasibility is validated as given in table 1.

4.1 Theoretical Analysis

For the purpose of the subsequent error rate and cov-

erage range analysis, the performance of the three

proposed systems in AWGN is analysed in this sec-

tion. For simplicity reasons, we assume that the sys-

tems are perfectly synchronised and have the correct

symbol clock and phase.

4.1.1 UWB Analysis

In order to evaluate the system’s performance, typ-

ical receivers have to be analyzed. Coherent UWB

receivers are often implemented as correlation re-

ceivers. Here the detection is performed by cross-

correlation between the received signal and a local

reference signal. Assuming pulse-position modula-

tion (PPM), perfect synchronization and binary sym-

bols with AWGN, the mean value u

of the received

signal results as derived from (Ge et al., 2002) in two

separable cases:

1. for a transmitted bit b

= 0

= E

{

= 0

}

= E

[

AKF (τ

) − AKF (τ

− ∆)

]

(2)

2. for a transmitted bit b

= 1

= E

{

= 1

}

= E

[

AKF (τ

+ ∆) − AKF (τ

)

]

(3)

where g

is the decision variable resulting from corre-

lation of received signal r (t) and local reference tem-

plate as given in (4).

dsym



r (t) ·

[

ν(t) − ν(t − ∆)

]

| {z }

template

dt. (4)

With AWGN, the BER results as

BER =

[

Pr(err|0) + Pr(err|1)

]

erfc

√

2σ

+ erfc

√

2σ

(5)

with σ

being the two-sided noise density (Reinhold,

2016). Equation (5) can be simpliﬁed for MCS 4 as-

suming equal transmission probabilities for each of

the binary symbols to

BER =

erfc

, (6)

which is equivalent to BER of antipodal signaling.

WINSYS 2016 - International Conference on Wireless Networks and Mobile Systems

4.1.2 FHSS Analysis

While a FHSS system with Frequency Shift Keying

(FSK) was chosen for analysis in (Reinhold et al.,

2013), a more realistic approach is chosen in this pa-

per. For the later analysis GFSK with modulation in-

dex η = 0.5 and a bandwidth time product BT = 0.5

is assumed.

For the coverage analysis, we consider limiter-

discriminator reception (LD), which is incoherent and

thus does not need phase recovery to operate. This

makes it suitable for fast FHSS systems and allows

packet communication without syncwords (Bluetooth

SIG, 2014). The receiver ﬁlter h

is chosen to be a

Gaussian ﬁlter and is given by its impulse response in

(7). For the following investigations this ﬁlter’s band-

width time product BT = 1 is assumed.

(t) =

√

2 · BT · exp



−2π(BT )

· t



(7)

The performance of the limiter-discriminator depends

on the width of the receiver ﬁlter’s frequency response

and the modulation index. The authors in (Cartier,

1977), (Simon and Wang, 1983) and (Pawula, 1988)

have evaluated its performance for FSK in AWGN.

The bit error probability sums up from two compo-

nents.

BER = P

cont

+ P

click

(8)

The error probability resulting from clicks P

click

dom-

inates for low SNR ﬁgures, whereas the continuous

error probability P

cont

dominates for high SNR. Since

the receiver’s ﬁlter leads to inter symbol interference,

the error probabilities must be averaged over all pos-

sible bit sequences d. When the receiver ﬁlter’s BT

is larger than or equal to one, a bit sequence length

of three is sufﬁcient. Assuming that every click leads

to an error, the error probability resulting from clicks

click

is equal to the average number of clicks

N av-

eraged over all possible bit sequences d (Simon and

Wang, 1983). When Gaussian impulse shaping is ap-

plied with a BT = 0.5 the length of the sequences d

has to be increased. For the investigated ﬁlter chain, a

overall sequence length of six symbols is sufﬁcient.

click

(9)

cont

can be calculated semi-analytically with (10),

where ∆ϕ is the phase difference between two sym-

bols and Ψ is the modulo 2π phase difference between

the two symbols that are superposed with correlated

complex Gaussian noise (Pawula, 2001).

cont

= Pr{∆ϕ − π 6 Ψ 6 0}

(10)

Equation (10) can be solved with the help of (20) in

(Pawula, 2001).

For extended comparison in the system evaluation

in section 4.3 we also take FSK with coherent recep-

tion (CR) into consideration. As given in (Proakis and

Salehi, 2008) in this case the BER is calculated as

BER =

erfc



1 − <

{

}



, (11)

where ρ is the correlation coefﬁcient. For orthogonal

signaling, which is given in case of MSK, the correla-

tion coefﬁcient qualiﬁes as ρ = 0.

BER =

erfc

(12)

4.1.3 PSSS Analysis

The simulative base band evaluation given in

(Schwetlick and Wolf, 2004) for 31 chips is calcu-

lated semi-analytically in this work and extended to

a general description for arbitrary m-sequences, on

which this paper’s evaluation is based. In the follow-

ing, the derivation is explained shortly. Employing a

spreading technique with orthogonal PN-sequences,

the BER is calculated by (6), which is equivalent to

BER of a BPSK (Proakis and Salehi, 2008). Since

m-sequences are not orthogonal, a penalty coefﬁcient

γ(n, p) is deﬁned to adapt the BPSK calculation for

PSSS. The cyclic autocorrelation ϕ of an arbitrary m-

sequence is given by

ϕ(τ) = m

→0

⊗m

→0

(

n, τ mod n = 0

−1, otherwise

, τ ∈ Z

(13)

The cross correlation yields the maximum at τ = i

respectively, where i denotes the cyclic shift. Thus

superposed cyclically shifted m-sequences inﬂuence

each other in their maximum value depending on the

bit values carried. The effective correlation amplitude

in the relevant shift after superposition is further de-

ﬁned as

ϕ(τ = i) =  (p) (14)

and can be calculated with respect to the number of

used sequences and the value of all other values in d.

Especially the superposition of equal bits in d is crit-

ical, since the correlations’ result is degraded due to

lacking orthogonality. Assuming a uniform distribu-

tion of the bit values in d, a binomial distribution of

the number of equal bits p results as shown in ﬁgure 5.

Coverage Range Analysis of Wireless Technologies for Industrial Automation - System Overview and Performance Evaluation

Normalized number of equal bits

0 0.2 0.4 0.6 0.8 1

Pr(n, p)

0.05

0.1

0.15

n = 31

n = 255

Figure 5: Distribution of equal data bits in d.

Taking this into account the penalty coefﬁcient can be

calculated as

γ(n, p) =



(p)

Pr(n, p) · 

(p)

. (15)

The effective correlation amplitude  (p ) is squared

since it inﬂuences E

and is normalized by the

probability of p equal bits since E

is deﬁned as

mean over all bit combinations in d. BER of PSSS is

thus calculated as a function of n as

BER = Pr(n, p) ·

erfc

γ(n, p) ·

. (16)

Caused by the averaging, the slope of the BER curve

is not falling monotonically.

4.2 Evaluation Methodology

The presented technologies UWB, FHSS and PSSS

are further compared in BER, coverage range and

PLR. In this section the evaluation principles are ex-

plained shortly.

The BER calculation based on E

is given for

each technology in (6), (8) and (16) respectively. The

relation between SNR and E

is given as

B ·T

= SNR ·

B ·T

, (17)

where B is the effective bandwidth, T the bit duration,

denotes the reception power and P

the effective

noise power. Considering PSSS and UWB, addition-

ally the spreading gain has to be taken into account.

Moreover, P

is the difference between trans-

mission power P

and path loss a

= P

− a

= P

+ SNR

(18)

Assuming free-space propagation, a

results as

= − G

− G

+ F + I

+ 20 log

4π · d · f

(19)

where G

and G

denote the antenna gains of

transmitter and receiver respectively. F deﬁnes the

noise ﬁgure, and I describes implementation losses.

is the carrier frequency and d the distance between

transmitter and receiver, which is equivalent to the

coverage range.

Finally, (19) can be solved for d, and a

can

be substituted with (18). The coverage range d

10 log



1 m



results as



+ G

− F − I + P

− SNR

− P

− 20 log

1 GHz

− 32.44



(20)

For an reasonable system comparison in terms of

Packet Loss Rate (PLR), Forward Error Correction

(FEC) and physical layer overhead have been ne-

glected for this analysis. The PLR thus is calculated

PLR = 1 − (1 − BER)

bit

. (21)

where N

bit

denotes the number of bits per packet.

4.3 Evaluation Results and Discussion

In the subsequent section the three suggested systems

are compared with each other considering the key re-

quirements for FA resulting from section 2.1. Ini-

tially a bit error evaluation is performed based on sec-

tion 4.1, before the systems are collated in a coverage

range comparison for the AWGN channel model. Af-

terwards the results are discussed regarding their suit-

ability for FA.

4.3.1 BER versus SNR

Figure 6 illustrates the BER performance versus

of the described PHY layer technologies in

AWGN. Under the described preliminaries, the IR-

UWB performance is congruent with the performance

of binary antipodal signaling. In the scope of FHSS

we observe the expected performance difference be-

tween MSK with coherent reception (CR) and GMSK

with limiter discriminator reception (LD). While the

performance of the FSK reference with CR is con-

gruent with binary orthogonal signaling, the LD re-

ception loses around 4 dB in the range of practically

relevant BERs. Regarding PSSS demodulation, we

observe the inﬂuence of the length of the utilized

PN-sequence. The PSSS 31 system loses about 5 dB

compared to antipodal signaling. By increasing the

sequence length by a factor of approximately 8 to

WINSYS 2016 - International Conference on Wireless Networks and Mobile Systems

[dB]

0 2 4 6 8 10 12 14 16 18

BER

−6

−5

−4

−3

−2

−1

UWB MCS4

FHSS LD

FHSS CR

PSSS 31

PSSS 255

Figure 6: Bit error rate versus E

PSSS 255 this performance loss reduces to less than

0.5 dB.

As presented in ﬁgure 7, by changing the scale to BER

versus SNR, the effect of the different concepts of fre-

quency spreading are clariﬁed. While FHSS spec-

trum spread effect arises from frequency changes,

UWB and PSSS originate their wideband character-

istics from impulse or sequential spreading. Here, for

PSSS the signal power refers to only one of the uti-

lized sequences, while all sequences are in use.

SNR [dB]

-30 -20 -10 0 10

BER

−6

−5

−4

−3

−2

−1

UWB MCS4

FHSS LD

FHSS CR

PSSS 31

PSSS 255

Figure 7: Bit error rate versus SNR.

4.3.2 Coverage Range Analysis

In order to determine realistic coverage ranges, a set

of reasonable values describing the transmission char-

acteristics has to been chosen. Table 3 summarizes the

parameters that are used in (18) for reasonable cover-

age range estimation in AWGN for the three depicted

technologies.

Due to interoperability with existing communication

systems in the 2.4 GHz ISM band, for the FHSS and

the PSSS system the 5.8 GHz ISM band is chosen for

coverage range analysis. For UWB, the 7.9872 GHz

Table 3: Parameters for Range Calculation.

Parameter UWB FHSS PSSS

[GHz] 7.9872 5.825 5.825

B [MHz] 499.2 1 20

[dBm] 10 14 14

[dBm] -86.99 -113.98 -100.97

bit

8 · 60 Byte

0 dBi

F 5 dB

I 10 dB

channel is selected as deﬁned in section 3.1. While

the parameters f

, B and P

differ among the three

technologies, the system parameters, which include

antenna gains G

and G

, noise ﬁgure F and im-

plementation losses I, are chosen identically for a rea-

sonable system comparison.

As a result, ﬁgure 8 is obtained from (20). Ob-

viously the sequential spreading concepts are able to

stand harsher SNRs as depicted in ﬁgure 7, but cer-

tainly suffer from higher P

(see table 3). The abso-

lute EIRP transmission power is the same for FHSS

and PSSS, but IR-UWB is subject to a regulatory lim-

itation of 0 dBm per 50 MHz bandwidth in the 6 GHz

to 8.5 GHz range (ETSI, 2013).

d [m]

0 200 400 600 800 1000

BER

−6

−5

−4

−3

−2

−1

UWB MCS4

FHSS LD

FHSS CR

PSSS 31

PSSS 255

Figure 8: Bit error rate versus coverage range.

Next, the evaluation results in terms of PER ver-

sus coverage range are shown in ﬁgure 9. The PLR

considerations are calculated with (21) and 60 Byte

packet size. The proposed 60 Bytes include user data,

which is up to 30 Byte for FA (see table 3), packet

overhead and FEC overhead. In order to attain an rea-

sonable system comparison without MAC layer eval-

uation, the packet size is kept the same for all three

PHY technologies.

Coverage Range Analysis of Wireless Technologies for Industrial Automation - System Overview and Performance Evaluation

4.3.3 Discussion

As displayed in ﬁgure 9, the PSSS 31 system does not

meet the FA coverage range requirement and turns

out as impractical for this application ﬁeld. The in-

homogeneity in the PLR curve’s slope for low error

rates from about 10

−7

to 10

−8

results from the averag-

ing over binomially distributed bits per PSSS symbol

as indicated in section 4.1.3. The UWB system and

the PSSS 255 system are comparatively low range,

but both match the range requirements for FA un-

der ideal free-space conditions. Other communication

scenarios are only applicable using FHSS leading to

its higher ﬂexibility.

While the UWB PHY reaches a coverage range of

43 m for PLR of 10

−9

, the PSSS 255 system covers up

to 75 m and the FHSS LD system up to 156 m. For the

PSSS coverage range it is assumed that the maximum

data rate is utilized, thus all codes are in use. When

the number of utilized codes is reduced, the coverage

range for the remaining codes is increased depend-

ing on the coding gain factor, which is up to 255 for

PSSS 255. Furthermore, the BER degradation coef-

ﬁcient γ is inﬂuenced by less concurrent codes (see

section 4.1.3).

As depicted in section 3.4 the considered systems

vary in their parameters and so does the link data rate.

Regarding the latency requirements, the achieved data

rate is vital. While FHSS and UWB have a ﬁxed chan-

nel data rate, which is equal to the link data rate, the

PSSS system can adapt the channel data rate depen-

dant on the speciﬁc application data rate. In case of

FHSS the ﬁxed channel data rate can only be adapted

d [m]

0 100 200 300 400 500 600 700

PLR

−9

−8

−7

−6

−5

−4

−3

−2

−1

FA limit

PA limit

CM limit

UWB MCS4

FHSS LD

FHSS CR

PSSS 31

PSSS 255

Figure 9: Packet loss rate versus coverage range.

within restricted limits by parallel reception on mul-

tiple FHSS frequencies as realized for WSAN (PNO,

2012). For serving multiple clients in a star topology

the UWB system is dependent on Time Division Mul-

tiple Access (TDMA), thus cycle times for scenar-

ios with large numbers of connected nodes are high

(Reinhold, 2016). For FHSS, besides TDMA, a Fre-

quency Division Multiple Access (FDMA) channel

access scheme is possible with advanced transceiver

concepts, but on the other hand abrogates the advan-

tage of simple transceivers. With PSSS a combination

with Code Division Multiple Access (CDMA) is pos-

sible, allowing very low latencies and novel and ﬂex-

ible resource management strategies, which are cur-

rently being investigated.

5 CONCLUSION

In this paper, requirements for industrial applications

have been discussed. These requirements are critical

for realization with wireless technologies in at least

the one of the application categories. Focusing on FA,

the performances of IR-UWB, FHSS and PSSS phys-

ical layers have been analyzed. The system analysis

and comparison have been performed under regula-

tory aspects and assuming realistic reception concepts

in AWGN. The systems have been discussed consid-

ering the delay requirements for FA and the systems’

potential with respect to appropriate medium access

strategies is assessed.

Since the presented evaluation bases on an AWGN

channel model, future work focuses on advanced

performance evaluation with more realistic channel

models for industrial environments like presented in

(Molisch et al., 2004). Consecutively, a delay analysis

with appropriate MAC layer concepts for each tech-

nology is possible and reasonable. Apart from that, a

coexistence analysis, including both inter- and intra-

system-coexistence, contributes a vital piece on the

feasibility of the presented PHY concepts.

ACKNOWLEDGEMENTS

Part of the research leading to these results has re-

ceived funding from the German Federal Ministry

of Education and Research under grant agreement

no. 16KIS0223 also referred to as ParSec, as well as

under grant agreement no. 16BU1222 also referred to

as KUSZ.

WINSYS 2016 - International Conference on Wireless Networks and Mobile Systems

REFERENCES

Aust, S., Prasad, R. V., and Niemegeers, I. G. M. M. (2015).

Outdoor Long-Range WLANs: A Lesson for IEEE

802.11ah. IEEE Communications Surveys & Tutori-

als, 17(3):1761–1775.

Bluetooth SIG (2014). BLUETOOTH SPECIFICATION

Version 4.2.

Cartier, D. E. (1977). Limiter-Discriminator Detection Per-

formance of Manchester and NRZ Coded FSK. IEEE

Transactions on Aerospace and Electronic Systems,

AES-13(1):62–70.

ETSI (2010). EN 300 440-1 V1.6.1, Electromagnetic com-

patibility and Radio spectrum Matters (ERM); Short

range devices; Radio equipment to be used in the 1

GHz to 40 GHz frequency range; Part 1: Technical

characteristics and test methods.

ETSI (2011). TR 102 889-2 V1.1.1. Technical report, Eu-

ropean Telecommunications Standards Institute.

ETSI (2013). EN 302 065-1 V1.3.1, Electromagnetic com-

patibility and Radio spectrum Matters (ERM); Short

Range Devices (SRD) using Ultra Wide Band tech-

nology (UWB) for communications purposes; Harmo-

nized EN covering the essential requirements of arti-

cle 3.2 of the R&TT directive; part 1: Common tech-

nical requirements.

FCC (2016). CFR Title 47: Telecommunication, Part 15,

Subpart C – Intentional Radiators.

Frotzscher, A., Wetzker, U., Bauer, M., Rentschler, M.,

Beyer, M., Elspass, S., and Klessig, H. (2014). Re-

quirements and current solutions of wireless commu-

nication in industrial automation. In Communications

Workshops (ICC), 2014 IEEE International Confer-

ence on, pages 67–72.

Ge, L., Yue, G., and Affes, S. (2002). On the BER per-

formance of pulse-position-modulation UWB radio in

multipath channels. 2002 IEEE Conference on Ultra

Wideband Systems and Technologies, UWBST 2002 -

Digest of Papers, (1):231–234.

Güngör, V. Ça

gri; Hancke, G. P. (2013). Industrial Wireless

Sensor Networks: Applications, Protocols and Stan-

dards. CRC Press.

IEC (2010). 62591 Ed. 1.0: Industrial communication net-

works - Wireless communication network and com-

munication proﬁles - WirelessHART.

IEEE (2005). IEEE Std 802.15.1-2005, IEEE Standard

for Information technolog - Local and metropolitan

area networks - Speciﬁc requirements - Part 15.1a:

Wireless Medium Access Control (MAC) and Phys-

ical Layer (PHY) speciﬁcations for Wireless Personal

Area Networks (WPA.

IEEE (2011). IEEE Std 802.15.4-2011, IEEE Standard

for Local and metropolitan area networks, Part 15.4:

Low-Rate Wireless Personal Area Networks.

KrishneGowda, K., Messinger, T., Wolf, A. C., Kraemer,

R., Kallfass, I., and Scheytt, J. C. (2015). Towards

100 Gbps Wireless Communication in THz Band with

PSSS Modulation: A Promising Hardware in the

Loop Experiment. In Ubiquitous Wireless Broadband

(ICUWB), 2015 IEEE International Conference on,

pages 1–5.

Molisch, A. F., Balakrishnan, K., Cassioli, D., Chong, C.-

c., Emami, S., Fort, A., Karedal, J., Kunisch, J.,

Schantz, H., Schuster, U., and Siwiak, K. (2004).

IEEE 802.15.4a Channel Model - Final Report. IEEE

P802, 15(04):1–40.

Pawula, R. F. (1988). Reﬁnements to the Theory of Error

Rates for Narrow-Band Digital FM. IEEE Transac-

tions on Communications, 36(4):509–513.

Pawula, R. F. (2001). Distribution of the phase angle

between two vectors perturbed by Gaussian noise

II. IEEE Transactions on Vehicular Technology,

50(2):576–583.

PNO (2012). WSAN Air Interface Speciﬁcation Technical

Speciﬁcation, Version 1.0.

Proakis, J. G. and Salehi, M. (2008). Digital Communica-

tions. McGraw-Hill, New York, 5th ed. edition.

Reinhold, R. (2016). Concepts for Reliable and Time-

critical Industrial Communication Based on IR-UWB

Systems. Dortmunder Beiträge zur Kommunikation-

stechnik, Prof. Dr.-Ing. Rüdiger Kays, Dortmund.

Reinhold, R., Schaefer, F., and Kays, R. (2013). Perfor-

mance Evaluation of an Enhanced Frequency Hopping

Transceiver in 5 GHz Band for Wireless Sensor Net-

works. The Tenth International Symposium on Wire-

less Communication Systems 2013, pages 823–827.

Schwetlick, H. and Wolf, A. (2004). PSSS - Parallel Se-

quence Spread Spectrum a Physical Layer for RF

Communication. In Consumer Electronics, 2004

IEEE International Symposium on, pages 262–265.

Simon, M. K. and Wang, C. C. (1983). Differential Ver-

sus Limiter-Discriminator Detection of Narrow-Band

FM. IEEE Trans. on Communications, 31(11):1227–

1234.

VDI/VDE (2007). VDI/VDE Guideline 2185: Radio Based

Communication in Industrial Automation.

Wolf, A. (2004). Verfahren zum Übertragen eines Daten-

worts, Document DE 103 01 250 A1.

ZigBee Alliance (2012). ZigBee Speciﬁcation, Document

053474r20.

ZVEI (2009). Coexistence of Wireless Systems in Automa-

tion Technology - Explanations on reliable parallel op-

eration of wireless radio solutions. Technical report,

ZVEI - German Electrical and Electronics Manufac-

turers’ Association, Automation Division.

Coverage Range Analysis of Wireless Technologies for Industrial Automation - System Overview and Performance Evaluation