=Paper=
{{Paper
|id=Vol-3646/Paper_17.pdf
|storemode=property
|title=A Method of Studying the Influence of the Performance of Wireless Computer Networks on Increasing the Accuracy of Distance Measurement
|pdfUrl=https://ceur-ws.org/Vol-3646/Paper_17.pdf
|volume=Vol-3646
|authors=Andriy Dudnik,Yurii Kravchenko,Nataliia Dakhno,Sergey Mosov,Sergey Grinenko
|dblpUrl=https://dblp.org/rec/conf/iti2/DudnikKDMG23
}}
==A Method of Studying the Influence of the Performance of Wireless Computer Networks on Increasing the Accuracy of Distance Measurement==
https://ceur-ws.org/Vol-3646/Paper_17.pdf
A Method of Studying the Influence of the Performance of
Wireless Computer Networks on Increasing the Accuracy of
Distance Measurement
Andriy Dudnik 1,2, Yurii Kravchenko 1, Nataliia Dakhno 1, Sergey Mosov 3 and Sergey
Grinenko 1
1
Taras Shevchenko National University of Kyiv, 60 Volodymyrska Street, Kyiv, 01601, Ukraine
2
Interregional Academy of Personnel Management, 2 Frometivska str, Kyiv, 03039, Ukraine
3
Institute of Public Administration and Research in Civil Protection, 21, Vyshhorodska St., Kyiv, 04074,
Ukraine
Abstract
Untimely determination of the position of an object that is part of wireless sensor networks
leads to the generation of erroneous information in the computerized system for measuring
the distance between objects. Such a shortcoming, in turn, can lead to, for example, untimely
detection of penetration, ignition source, etc. A particularly favorable environment for this
kind of negative consequences is the unfavorable environment in the conditions of the WB.
Among the various classes of computer information systems and networks, a special place is
occupied by systems and networks whose transport service is based on the use of radio air as
a data transmission medium for computerized distance measurement systems (wireless sensor
networks). Therefore, in the synthesis of methods for building computerized systems for
measuring mechanical quantities, the performance of wireless sensor networks takes an
important place. In this paper, a detailed analysis of the types of devices of wireless sensor
networks, their main differences, as well as a variant of the topology of their inclusion in the
network is considered. It is proposed to improve the principle of operation of the wireless
sensor network router by introducing an algorithm based on the redistribution of the
bandwidth of the transmission channel. The structural scheme of the device for improving the
quality of wireless data transmission in areas of unreliable reception or with insufficient
interference resistance has been developed, based on the method "Monitoring the state of the
quality of communication".
Keywords 1
Sensor network, node, anchor, localization, zig-bee, transceiver, radio pulse, time, distance,
measurement error.
1. Introduction
One of the ways to solve this problem is to modify the existing classical reference model of open
systems interaction (EM OSI/ISO). According to this model, the majority of means of transmission of
wireless sensor networks are designed, created and operated. Equally important is the theoretical
analysis and search for optimal modeling methods and increasing the productivity of data
transmission channels of computerized distance measurement systems. Thus, one of the most
problematic areas of wireless sensor networks is untimely transmission of information, as well as
errors during transmission. This, in turn, is the cause of the disturbing situation and leads to a high
probability of errors when measuring the distance [1-3].
Information Technology and Implementation (IT&I-2023), November 20-21, 2023, Kyiv, Ukraine
EMAIL: a.s.dudnik@gmail.com (A. 1); kr34@ukr.net (A. 2); nataly.dakhno@ukr.net (A. 3); gurman63@ukr.net (A. 4);
serggrinenko@gmail.com (A. 5)
ORCID: 0000-0003-1339-7820 (A. 1); 0000-0002-4188-2850 (A. 2); 0000-0003-3892-4543 (A. 3); 0000-0002-3997-2785 (A. 4); 0000-
0001-5544-2605 (A5)
© 2023 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
173
Currently, there are various technological solutions for determining the position of objects in space
or on the surface of the earth. This is due to the fact that it is impossible to implement one universal
method that is suitable for all possible cases. More precisely, it is impossible to create a device whose
characteristics would meet the requirements of all (or even most) tasks. The task of positioning
arouses great interest among developers and manufacturers of equipment, which may indicate its
demand. In addition, most solutions use a radio signal as an information carrier. Therefore, universal
devices that allow simultaneous transmission and reception of data, as well as determining one's
position in space, will have consumer value. One of the standards regulating the operation of wireless
transmission devices with a positioning function is IEEE 802.15.4 [4-5].
This approach to the formation of networks allows adapting sensor networks to solve an extremely
wide range of tasks. In particular, one of the main applications of sensor networks is the creation of
various monitoring and control systems. It should be expected that in the near future sensor networks
will occupy a much wider niche among existing telecommunication technologies that use wireless
radio communication. In connection with this, the analysis and search for methods of determining the
coordinates of sensor network objects becomes an urgent task [6–9]. The general approach to
determining the location of an object is based on measuring the characteristics of a radio signal
emitted by a transmitter located on the object and received by stationary receivers with known
coordinates. Based on these characteristics, the distance between the transmitter and each of the
receivers is estimated [10-12].
Then, taking into account geometric principles, the coordinates of the object are determined. This
paper investigates the problem of determining the distance between receivers of chaotic radio pulses.
the calculation of the distance is based on the propagation of the signal in the air. The accuracy of the
determination between the transceivers is evaluated by the signal transit time, taking into account the
interference. In further research, for the possibility of obtaining alternative results, as well as a more
detailed analysis of measurement error, laser distance measurement will be included in the sensor
network. [13-15].
2. Analysis of literature and problem statement
There are positioning technologies such as GPS, which is discussed in the work of Sichitiu M. [16-
17], Galileo, which is discussed in the work of the Federation of American Scientists [18-21],
Glonass, which is discussed in the joint work of Spanish scientists on monitoring environment [22-
25], the use of Wi-Fi [26] or ultrashort pulses, as described in the corresponding standard of the
Institute of Electrical and Electronics Engineers, or GSM cell phone positioning technology, which is
the subject of the work of He T. [27-30] and etc.
All these technologies have their advantages and disadvantages. Galileo, GLONASS, GPS, for
example, allow you to navigate the earth's surface by carrying a compact device with a set of local
maps. These are very useful technologies for moving around in open areas. The accuracy of
determining the position of such devices now reaches several meters. However, it can get worse in big
cities, in difficult terrain, or simply indoors. In the latter case, the use of satellite positioning is
unacceptable. One of the urgent tasks is to determine the location of individual network objects. An
indispensable condition for the operation of any monitoring and control systems is the linking of the
data collected by the entire system to geographic coordinates for displaying the collected information
on the map and further analysis. In addition, such a network (unlike traditional radio networks) with a
built-in subsystem for positioning individual objects can be deployed almost anywhere with minimal
costs. This can be done, for example, by scattering network objects from an airplane. In addition to
linking the data received by the network in the process of work to the map of the area, information
about the coordinates of objects will be necessary in the process of functioning of the network itself
(building efficient routing algorithms from the point of view of energy consumption, collecting the
received data).
The problem of positioning is of great interest to developers and manufacturers of equipment,
which may indicate its demand. Moreover, most solutions use a radio signal as an information carrier.
Therefore, universal devices that allow simultaneous transmission and reception of data, as well as
174
determining one's position in space will have consumer value. One of the standards regulating the
operation of wireless radio transmitting devices with a positioning function is IEEE 802.15.4.
The general approach to determining the location of an object is based on measuring the
characteristics of a radio signal emitted by a transmitter located on the object and received by
stationary receivers with known coordinates [6]. Based on these characteristics, the distance between
the transmitter and each of the receivers is estimated. Then, taking into account geometric principles,
the coordinates of the object are determined.
The following values can be used as signal characteristics:
• signal propagation time from the transmitter to the receiver;
• the difference in indicators of signal propagation time from the transmitter to different receivers;
• signal intensity;
• direction of signal arrival.
The purpose of this study is the development and research of new, as well as the improvement of
existing technological solutions to increase the performance of wireless sensor networks that are part
of distance measurement systems.
3. Description of the wireless computer network model and the method of
increasing its performance
Wireless computer network model. At the base of the ZigBee/802.15.4 technology, there are
three classes of devices: FFD-routing devices (Full Function Device - a device with a complete set of
functions - R), coordinator devices (Coordinators - FFD with additional system resources depending
on the complexity of the network - C) and RFD end devices (Reduced Function Device - a device
with a limited set of functions - E). There is only one coordinator in each ZigBee LAN. Its main task
is to set parameters and create a network, select the main radio frequency channel, and set a unique
network identifier. Therefore, the coordinator is the most complex of these three types of devices, has
a large amount of memory and increased power consumption (usually AC power is used). Routers are
used to extend the range of the network because they are able to perform the functions of relays
between devices located far away one from another. Routers support any ZigBee network topology,
can perform coordinator functions and address all network nodes (FFD, RFD). Devices with a limited
set of functions do not participate in routing, cannot perform the function of a coordinator, refer only
to the coordinator of the local network (FFD device), support "one-to-one" and "star" type topologies,
play the role of end nodes of the network. In practice, most of the network nodes are RFD devices,
and the use of FFD devices and coordinators is necessary for the formation of communication bridges
and the corresponding network topology. As soon as routers and other devices are connected to the
network, they receive information about it from the coordinator or any other existing router already
involved in the network, and based on this information, they set their operational parameters
according to the characteristics of the network. A ZigBee router obtains a table of network addresses,
which it distributes among end devices connected to it.
An FFD device uses a reduced addressing tree when making route decisions. Each router that
allows shortening must maintain a table containing pairs of the form DN, where D is the destination
address and N is the address of the next device on the path to the destination. The combination of
routing on the tree-like principle ensures flexibility of operation and gives developers the choice of
the optimal price/performance ratio. 1 [1, 2]. Next, the mathematical model for determining the
distance between any two neighboring devices of a given network will be considered. When looking
at a particular wireless network and a lower speed signal such as 900MHz compared to a 2.4GHz
signal, you can get a wavelength function attenuation for each frequency. This will give an indication
of signal strength in any band. The general form of the Friis transmission equation (1) is as follows:
2 (1)
Pr PG
t Tx GRx ,
(4 R)2
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where GTx and GRx are the gain of the transmitter and receiver, R is the distance between the
transmitter and receiver, and Pr and Pt are the power of the receiver and transmitter, respectively.
Based on this equation, the distance R between the transmitter (Tx) and the receiver (Rx) was
obtained (2):
PG
t Tx GRx (2)
R .
Pr 4
Visually, the model for determining the distance between 2 neighboring devices of a wireless
sensor network is presented in Figure 2.
Figure 1: The structure of the sensor network
Figure 2. A model for determining the distance between 2 neighboring devices based on the Friis
equation
The decibel (dB) form of the Friis equation is defined as (3):
2 (3)
Pr Pt GTx GRx 20log10 .
(4 R)2
Based on this equation, the distance R will be equal to (4):
401 G G P P (4)
R
Rx Tx t r
10 .
4
A 900 MHz signal at 10 m will have a loss of 51.5 dB, and a 2.4 GHz signal at 10 m will have a
loss of 60.0 dB. Next, the effect of power and range on signal quality will be shown. Next, the effect
176
of power and range on signal quality will be shown using a relationship called transmission loss. To
do this, you need to use the comparison of the transmission power with the level of sensitivity,
measured on a logarithmic scale (dB). It is possible to increase the power level to meet the
requirements of a particular band, but in many cases this violates regulatory requirements or affects
battery life. Another option is to improve the sensitivity level of the receiver, as implemented in
Bluetooth 5 technology of the latest specification. Signal transmission loss (FSPL) is determined by
the ratio of transmitter power and receiver sensitivity, as shown below.
PT ,
FSPL
Sx
where PT - transmitter power, S x - level of sensitivity.
FSPL is measured on a logarithmic scale in dB; therefore, adding decibels is equivalent to
multiplying numerical coefficients, the equation will have the following form:
Pr (dB) PT (dB) GTx (dB) FSPL(dB) .
If there is no factor contributing to signal amplification (for example, antenna gain), there are only
two ways to improve reception: increase transmission power or decrease loss.
When simulating the maximum range of a particular protocol, Free-Space Path Loss (FSPL) will
be used. This is the amount of electromagnetic wave signal loss in line of sight in free space (without
obstacles). The second factor in FSPL is the frequency (f) of the signal, the distance (R) between the
transmitter and the receiver, and the speed of light (c). In terms of calculating the FSPLF in decibels,
the equation will be:
4 Rf 2 4 Rf
FSPL(dB) 10log 20log10
c c
4
20log10 ( R) 20log10 ( f ) 20log10
c
20log10 ( R) 20log10 ( f ) 147,55.
Based on this equation, the distance will be equal to (5):
FSPL дБ
c (5)
R 10 20
.
4 f
The FSPL formula is a simple first-order equation. A better approximation takes into account
reflections and wave interference from the earth's surface, such as the flat-earth loss formula. Here ht
is the height of the transmitting antenna, hr is the height of the receiving antenna. k represents the
number of waves in free space and is simplified as shown. Let's convert the equation to use the dB
notation:
Pr ht2 hr2
Llosses on a flat surface k 4 ,
Pt 4 r R
Where 𝑘 = 2𝜋⁄𝜆. Based on this equation, the distance R will be equal to (6):
ht2 hr2 Pt . (6)
R4
Pr
A system for increasing the performance of wireless sensor networks. To improve the
performance of FFD devices, consider an algorithm for improving the performance of a wireless
network based on the redistribution of the bandwidth of the transmission channel [3]. The structure of
the capacity distribution system by subchannels is shown in Fig. 3.
Redistribution will take place as follows:
1. The user or group of users with the lowest priority is assigned the number 1, each subsequent
priority is assigned a number 1 higher.
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2. In the same way, priorities will be assigned to traffic classes.
3. Next, the bandwidth of the subchannel, which will be provided for sending the packet, is
calculated according to formula (7):
Pd PТ (7)
C(%) 10 .
2
where C is the bandwidth in percent, Pd is the device priority, PT is the traffic priority (this formula is
valid only in cases where the sum of the user priority and traffic does not exceed 10).
Figure 3. The structure of the transmission channel model of the sensor network using the adapted
bandwidth redistribution method
The main condition is that the user with the highest priority is never charged all 100% of
bandwidth, and the lowest is never charged with 0%. Based on this method, a structural diagram of
the router R (see Fig. 1) with dynamic redistribution of flows was proposed, which implements this
model shown in Fig. 3. This scheme is presented in fig. 4.
Figure 4. Structural diagram of router R with dynamic redistribution of flows in channels of wireless
sensor networks
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The task of this model is to improve the conditions for the passage of applications through the
serving devices of routers by means of an adapted redistribution of flows to the measuring channel.
The task is solved by the fact that a double classifier is introduced into the router with dynamic
redistribution of the flow of requests, which contains a classification block that distributes flows
according to priority, passing requests through several queues, which distributes requests according to
two classes. The introduction of a double classifier into the device favorably distinguishes the
proposed router from the prototypes, since in the prototypes only the optimal route is found and the
measurement indicators are transmitted along it. In the proposed device, optimal reconfiguration of
the parameters of the routing device itself is carried out without switching to another one. The routing
device with dynamic request flow redistribution contains a two-stage classifier unit 1, which contains
a classifier according to the priority of the device class (E, R, C and one reserve priority) 1.1-1.4 and a
classifier according to the priority according to the type of measurement parameters (GPS indicators,
data from Internet, laser rangefinder indicators and indicators based on measurements of signal power
loss or its arrival time) 1.5-1.8, service device queues 2.1-2.4 and service device (scheduler) 3. The
two-stage classification unit 1, which contains a classifier according to the device priority 1.1-1.4 and
a classifier according to the priority of the measurement parameters 1.5-1.8, distributes the flow of
applications according to the condition of formula (7 ).
Another task is to enter into the structural diagram of the wireless data transmission device a line
that would perform the function of communication between the applications of the physical and
network layers of the OSI reference model. That is, it would work on the basis of the signal quality
monitoring algorithm. It is for this reason that the signal quality analyzer 5, which is shown in fig. 5.
Figure 5. Structural diagram of the device for transmitting data in sensor networks of the IEEE
802.15.4 standard with a system for improving the quality of work in areas of uncertain reception or
with insufficient immunity to interference
When building the device, the blocks are divided into modules, according to their belonging to one
or another level of the OSI reference model. This device contains a control unit 1, a module of the
LLC sub-layer of the OSI model channel layer 2, a host interface unit 2.1, an embedded
microcontroller 2.2, a receiver/transmitter application unit 2.3, a bus interface unit 2.4, memory 3, a
module of the MAC sub-layer of the OSI channel layer 4, frequency band controller 4.1, radio
frequency receiver/transmitter 4.2, signal analyzer 5, OSI physical layer module 6, physical layer
interface 6.1, antenna 6.2., automatic frequency adjustment unit 7. The following is a description of
the operation of this device. The control unit 1 sends the command to send the packet and the packet
itself to the module of the LLC sub-layer of the channel level of the OSI model 2. In the module of
the LLC sub-layer of the channel level of the OSI model through the block of the host interface 2.1,
after passing the appropriate transformations, with the help of the applications of this module, the
packet becomes a frame. After that, the built-in microcontroller 2.2 transmits the frame to the
receiver/transmitter application block 2.3 and through the bus interface block 2.4 records the data
about the transmission status to the memory 3, where they are stored for a certain time. The
179
receiver/transmitter application block 2.3 directs the frame to the MAC sub-layer module of the OSI
channel layer 4. In the MAC sub-layer module of the OSI channel layer, the frequency band controller
4.1 selects the optimal frequency range for this frame, and directs the frame to the radio frequency
receiver/transmitter 4.2. In this module, both the conversion of the frame into electromagnetic
oscillations and their modulation according to the content of the frame takes place.
After that, the oscillations are transmitted to the OSI physical layer module 6, and the information
about the frequency range selected by block 4.1 is transmitted to the automatic frequency adjustment
block 7. Block 6.1 of the OSI physical layer module imposes electromagnetic oscillations on the
frequency that is adjusted by block 7. The oscillations are directed to antenna 6.2, which transmits the
signal to the radio air. The signal analyzer 5 constantly monitors information about the state of data
transmission. It sends appropriate requests to the physical layer 6.1 interface and receives information
about the state of data transmission from it. The signal analyzer 5 transmits information about the
state of data transmission to the control device 1, after which a decision is made to change the
conditions of data transmission as necessary. Decision-making means waiting for improvement in
signal quality (according to the rules of the algorithm).
Next, we will describe the convolutional (PBSS) coding method proposed in the previous
paragraphs as a technology for improving the quality of data transmission when the signal condition
drops. This method is recommended for use in the device of fig. Fig. 3. The idea of convolutional
coding is as follows. The sequence of input information bits will be transformed in a convolutional
encoder so that each input bit corresponds to more than one output bit. That is, the convolutional
encoder adds some redundant information to the original sequence. If, for example, two output bits
correspond to each input bit, then we speak of convolutional coding with a rate of r = 1/2. If three
output bits correspond to every two input bits, then the speed of convolutional coding will be already
2/3 [6, 7]. Any convolutional encoder is built on the basis of several serially connected memory cells
and logical XOR elements. The number of cells determines the number of possible encoder states. If,
for example, six cells are used in a convolutional encoder, then information about six previous signal
states is stored in the encoder, and taking into account the value of the input bit, we get that such an
encoder uses seven bits of the input sequence. Such a convolutional encoder is called a seven-state
encoder (K = 7). The output bits formed in a convolutional encoder are determined by XOR
operations between the values of the input bit and the bits stored in the memory cells, that is, the value
of each output bit formed depends not only on the input information bit, but also on several previous
ones bits PBSS technology uses a seven-state convolutional encoder (K = 7) with a speed of r = 1/2.
The scheme of such an encoder is shown in Fig. 6.
Figure 6. Scheme of a convolutional encoder used in PBSS coding (K = 7, r = 1/2)
The main advantage of convolutional encoders is the immunity of the sequence formed by them:
even in the event of reception errors, the initial sequence of bits can be restored without error. A
Witerbi decoder is used to restore the original sequence of bits on the receiver side.
3. Discussion of the impact of the performance of wireless computer
networks on the accuracy of distance measurement
The peculiarities of this device during its operation in a wireless computer network were studied.
With the help of a special-purpose wireless network modeling tool, we will calculate the reduction in
180
data transmission range, depending on mechanical interference, as well as the associated loss of
bandwidth. Based on the obtained results, we will construct a graph (Fig. 7).
Figure 7. Dependence of the actual transmission speed on the range
Based on this graph, it can be concluded that when switching to the PBSS coding method, 2.4 GHz
(highlighted in bold), the data transmission range increases in comparison with OFDM technology,
2.4 GHz, by approximately 15-17 m. For devices , which at the same time will continue to work on
the IEEE 802.15.4 standard, the actual speed will reach almost 18 Mbit/s. Based on this, it can be said
that the introduction of an additional block into the data transmission device is fully justified,
regarding the issue of increasing the data transmission range. Another important characteristic of data
transmission is the bit error rate (BER), which also affects the accuracy of transmission of distance
measurements. BER shows the number of bit errors received over the communication channel. BER is
a dimensionless quantity expressed as a ratio or percentage. for example: If the initial sequence is:
1 0 1 0 1 1 0 1 0 0, and the resulting sequence is:
0 0 1 0 1 0 1 0 1 0 (differences are in bold), then the BER will be 5 errors/10 transmitted bits =
50%.
BER is affected by channel noise, interference, multipath fading, and attenuation. Methods to
improve BER include increasing transmit power, improving receiver sensitivity, using less
dense/lower order modulation techniques, or adding redundant data. The latter method is commonly
referred to as forward error correction (FEC). FEC simply adds additional information to the
transmission. In the most basic sense, one could add triple redundancy and a majority choice
algorithm; however, this will reduce bandwidth by a factor of 3. Modern FEC methods include
interference-tolerant codes and Reed-Solomon error correction codes. BER can be expressed as a
function of SNR Eb/No. In Fig. 8 shows different modulation methods and their corresponding BERs
for different SNRs.
As the SNR increases, the BER naturally decreases. At this point, you need to understand the
following - you can calculate the minimum SNR required to achieve a certain data rate for a distance
measurement system. The only way to increase capacity or bandwidth for wireless service is to:
- add more spectrum and channel capacity, which increases the bandwidth linearly;
- add more antennas (MIMO), which linearly improves bandwidth;
- to improve the SNR with the help of improved antennas and receivers, which only improves the
level logarithmically;
181
- the Shannon limit is the final limit of digital transmission;
- exceeding the limits is possible, but the integrity of the data containing the measurement
indicators will be lost;
- it is not possible to simply increase the modulation levels without increasing the cost of
transmission errors and complexity.
Figure 8. Bit error rate (Pb) versus energy efficiency (Eb/No) SNR for different modulation schemes
The distance measurement method that a wireless device uses is Maximum Link Loss (MCL). The
MCL is the maximum distance at which there is a complete loss of channel between the transmitter
and the receiving antenna, but data service can still be provided. MCL is a very common way of
measuring distance or maximum data transmission radius. MCL will include antenna gain, path loss,
shadowing and other radio effects. Typically, a 4G LTE system will have an MCL of around 142 dB.
Іt should be understood that if you increase the listening time by each bit, the noise level will
decrease. If you reduce the bitrate by 2 times, then the following equality will be true: (bitrate/2) =
(bit length × 2). Also, the energy per bit increases by a factor of 2, and the noise energy increases by
sqrt(2). For example, if you reduce Bit_Rate from 1 Mbps to 100 kbps, then Bit_Duration = increases
by a factor of 10. The range improves by sqrt (10) = 3.162x .
4. Conclusions
It was determined that untimely determination of the position of an object that is part of wireless
sensor networks leads to the formation of a bit error rate (BER) in a wireless network for measuring
the distance between objects, which can be up to 50%. Such a shortcoming, in turn, can lead, for
example, to untimely detection of penetration, ignition source, etc. A particularly favorable
environment for this kind of negative consequences is an unfavorable situation in the conditions of
WB.
182
When modeling the coding methods of wireless sensor networks, it was determined that the
highest performance of measurement data transmission is achieved when using the PBSS method,
which, compared to the OFDM method, is capable of working at a distance of about 15-17 m longer
and collecting a transmission speed of up to 18 Mbit/s.
It is proposed to improve the principle of operation of a wireless sensor network router by
introducing an algorithm based on the redistribution of the bandwidth of the transmission channel. A
structural diagram of the device has been developed to improve the quality of wireless data
transmission in areas of unreliable reception or with insufficient immunity based on the
"Communication Quality Status Monitoring" technique.
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