U.S. patent application number 15/475011 was filed with the patent office on 2017-10-05 for method for predicting a level of qoe of an application intended to be run on a wireless user equipment.
The applicant listed for this patent is THOMSON LICENSING. Invention is credited to Diego NEVES DA HORA, Renata TEIXEIRA, Karel VAN DOORSELAER, Koen VAN OOST.
Application Number | 20170288986 15/475011 |
Document ID | / |
Family ID | 55755531 |
Filed Date | 2017-10-05 |
United States Patent
Application |
20170288986 |
Kind Code |
A1 |
VAN OOST; Koen ; et
al. |
October 5, 2017 |
METHOD FOR PREDICTING A LEVEL OF QoE OF AN APPLICATION INTENDED TO
BE RUN ON A WIRELESS USER EQUIPMENT
Abstract
The present disclosure is directed toward a device and a method
for evaluating a wireless link established between an access point
and a user equipment. The device and method include determining a
level of Quality of Experience of an application intended to be run
on the user equipment using a mapping between a parameter
representative of the QoE of the application under different
wireless transmission conditions and sets of parameters
representative of said different transmission conditions of the
wireless link.
Inventors: |
VAN OOST; Koen; (Borsbeek,
BE) ; NEVES DA HORA; Diego; (Cachan, FR) ;
TEIXEIRA; Renata; (Paris, FR) ; VAN DOORSELAER;
Karel; (Edegem, BE) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
THOMSON LICENSING |
Issy les Moulineaux |
|
FR |
|
|
Family ID: |
55755531 |
Appl. No.: |
15/475011 |
Filed: |
March 30, 2017 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04W 84/12 20130101;
H04W 88/08 20130101; H04W 24/10 20130101; H04W 88/02 20130101; H04L
41/5067 20130101; H04L 41/147 20130101; H04W 24/02 20130101; H04L
41/5009 20130101 |
International
Class: |
H04L 12/24 20060101
H04L012/24; H04W 24/10 20060101 H04W024/10; H04W 24/02 20060101
H04W024/02 |
Foreign Application Data
Date |
Code |
Application Number |
Apr 1, 2016 |
EP |
16305390.3 |
Claims
1. A computer implemented method for predicting a level of Quality
of Experience (QoE) of an application intended to be run on a user
equipment, said method comprising computing said level of QoE of
said application using a set of parameters representative of
transmission conditions of a wireless link established between said
user equipment and an access point, said set of parameters
representative of transmission conditions of the wireless link
being collected by said access point being prior the transmission
of data between said user equipment and said access point.
2. The method according to claim 1 comprising, prior to computing
the level of QoE: measuring a parameter representative of the QoE
of the application under different wireless transmission
conditions, said different wireless transmission conditions being
defined by different sets of parameters representative of
transmission conditions of the wireless link, called learning sets,
computing a mapping between the different learning sets and the
parameter representative of the level of QoE of the
application.
3. The method according to claim 2 further comprising: determining
parameters of the learning sets which are significant influence on
the level of QoE of said application.
4. The method according to claim 3 wherein the application intended
to be run on the user equipment is a web-browsing application.
5. The method according to claim 4 wherein parameter representative
of the QoE of the application under different wireless transmission
conditions is the page load time.
6. The method according to claim 5 further comprising: computing a
mapping between the page load time and a mean opinion score.
7. The method according to claim 4 wherein the parameters
representative of the transmission conditions of the wireless link
of significant influence on the level of QoE of said application
are an average physical layer transmission rate, a frame delivery
ratio, and parameters representative of a business of a
transmission medium of the wireless link due to interferences from
wireless equipments located in a vicinity of the user
equipment.
8. The method according to claim 7, wherein the parameters
representative of the transmission conditions of the wireless link
are obtained by monitoring data transmission through the wireless
link.
9. The method according to claim 8, wherein computing the level of
QoE of said application is based on the mapping of the parameters
representative of the transmission conditions of the wireless link
of significant influence on the level of QoE and the mean opinion
score.
10. The method according to claim 1, wherein computing the level of
QoE of said application is based on the mapping of the parameters
representative of the transmission conditions of the wireless link
and the mean opinion score.
11. A circuit comprising a processor, a memory and a wireless node,
the memory comprising instructions, which, when performed by the
processor, performs the method according to claim 1.
12. A gateway device comprising a circuit comprising a processor, a
memory and a wireless node, the memory comprising instructions,
which, when performed by the processor, performs the method
according to claim 1.
13. A computer program comprising program code instructions for the
implementation of the method for predicting a level of Quality of
Experience (QoE) of an application intended to be run on user
equipment according to the method of claim 1 when the program is
executed by a processor.
14. A non-transitory readable medium having stored therein
instructions for causing a processor to perform the method for
predicting a level of Quality of Experience (QoE) of an application
intended to be run on a user equipment according to claim 1.
Description
REFERENCE TO RELATED EUROPEAN APPLICATION
[0001] This application claims priority from European Patent No.
16305390.3, entitled "METHOD FOR PREDICTING A LEVEL OF QOE OF AN
APPLICATION INTENDED TO BE RUN ON A WIRELESS USER EQUIPMENT," filed
on Apr. 1, 2016, the contents of which are hereby incorporated by
reference in its entirety.
TECHNICAL FIELD
[0002] The invention relates to the field of wireless nodes and
respective devices communicating with each other via a wireless
communication.
BACKGROUND
[0003] Access gateways are widely used to connect devices at the
home to the Internet or any other wide area network (WAN). Access
gateways use in particular Digital Subscriber Line (DSL) technology
that enables a high data rate transmission over copper lines or
optical lines. Residential gateways, but also other devices such as
routers, switches, telephones and set-top boxes, are understood in
this context as Customer Premises Equipment (CPE) devices.
[0004] Access gateways including wireless technology have a key
role in today's home and professional environments. A mechanism for
connecting wireless devices to a Local Area Network (LAN) is called
Wi-Fi, which is a brand name of the Wi-Fi Alliance for devices
using the IEEE 802.11 family of standards for wireless data
transmission. The IEEE 802.11 standards define two types of
wireless nodes, a general wireless device that can connect to other
devices called a station (denoted as STA) and a special type of a
STA that is in control of the network, namely an Access Point
(denoted AP). A Wi-Fi network, often called a WLAN (Wireless Local
Area Network), consists of an AP with one or several STA connected
to the AP.
[0005] Due to its flexible and "invisible" nature, a lot of LAN
equipments are utilizing Wi-Fi rather than the classical wired
Ethernet approach. This widespread usage of wireless LAN has
exposed however a serious downside of using a shared medium
technology: interference. Interference, both Wi-Fi and non-Wi-Fi
related, leads to a degraded user experience due to the nature of
IEEE 802.11. In its most common form, IEEE 802.11 networks apply a
medium access method in which collisions are avoided by sensing
that the medium is used (denoted as CSMA-CA for Carrier Sense
Multiple Access-Collision Avoidance). This uses a technique
referred to as "Clear Channel Assessment" (CCA). Clear channel
assessment determines whether a wireless communication channel is
"occupied", e.g., "busy" with another wireless communication and/or
has an amount of interference that makes the wireless communication
channel unsuitable for communication. In this way, it is determined
whether the wireless communication channel is available or not
available for communication, e.g. occupied or not occupied. The
medium access method is also commonly known as "listen before
talk", describing the essence of the method. Interference from any
nature can hence block the medium and force all nodes to remain
silent for a certain amount of time.
[0006] Another impact of interference can be packet loss at the
receiver side, leading to a reduction of the physical data rate. In
this case, the interference is not detected by the CCA of the
transmitter, but is decreasing the SINR (Signal to Noise and
Interference Ratio) of the Wi-Fi packets as seen by the
receiver.
[0007] Therefore, in certain circumstances, the Wi-Fi connection
can suffer from poor performance and even connection loss. Some of
these circumstances are obvious and easy to explain to an end user.
For example, if the distance between the station and the access
point is too large, then signal levels are low and performance will
degrade. Other circumstances are "invisible" and not understood by
the end user, e.g. a hidden node. A hidden node is invisible to
some of the nodes of a network, leading to a practical failure of
the CSMA-CA method, which can cause packet collision/corruption
over air. In many cases, the end user is not able to diagnose the
problem source and correct the issue.
[0008] With the recent development of tablets, laptops and
smartphones there is an increase in the use of Wi-Fi. As a
consequence, in-home Wi-Fi network connectivity becomes one of the
main Internet service provider support costs and causes for
help-desk calls. Indeed, as Wi-Fi connections are vulnerable to
performance problems due to the shared medium, an end user may
observe a decrease in Quality of Experience (QoE) of the
applications he/she is currently running on one of his/her wireless
equipments, such as an increase in the loading time of a website.
The end user may mistakenly assume there is an issue with the
service offered by the Internet Service Providers (ISP).
[0009] Internet service providers are therefore searching for ways
to get a better understanding of the end user's wireless
environment including link quality and performance and its impact
on the QoE of the end user.
[0010] The present invention has been devised with the foregoing in
mind.
SUMMARY OF INVENTION
[0011] According to a first aspect of the invention there is
provided a computer implemented method for predicting a level of
Quality of Experience (QoE) of an application intended to be run on
a user equipment, said method comprising [0012] computing said
level of QoE of said application using a set of parameters
representative of transmission conditions of a wireless link
established between said user equipment and an access point, said
set of parameters representative of transmission conditions of the
wireless link being collected by said access point being prior the
transmission of data between said user equipment and said access
point.
[0013] Such a method enables to accurately predict an expected
Quality of Experience (QoE) for an application intended to be run
on a user equipment, such as a smartphone, connected to the
Internet through a wireless link established between said user
equipment and an access point, such as a residential gateway, said
wireless link being for example a Wi-Fi link. Thus, such a method
enables to determine those cases where the end user expectations in
terms of QoE are not met because of the conditions of the wireless
link.
[0014] This is made possible thanks to the knowledge of parameters
representative of the transmission conditions of the wireless
link--i.e. CCA statistics and transmission scheme chosen by the
transmitter.
[0015] The method further comprises, prior to computing the level
of QoE: [0016] measuring at least one parameter representative of
the QoE of the application under different wireless transmission
conditions, said different wireless transmission conditions being
defined by different sets of parameters representative of
transmission conditions of the wireless link, called learning sets,
[0017] computing a mapping between the different learning sets and
the parameter representative of the level of QoE of the
application.
[0018] Prior to predicting the expected level of QoE of an
application intended to be run on a user device, a learning phase
is executed. During the learning phase, a parameter representative
of the QoE of the application is measured several times under
different wireless transmission conditions in order to establish a
correlation between the parameters representative of a transmission
conditions of the wireless link defining the different transmission
conditions of the wireless link and the parameter representative of
the QoE of the application. This is done, for example, by
introducing attenuation on the transmission path between the access
point and the user equipment or interferences due to different
types of wireless communications, e.g. Wi-Fi or non Wi-Fi
communications.
[0019] The method further comprises: [0020] determining the
parameters of the learning sets which are significant influence on
the level of QoE of said application.
[0021] Using all the parameters of the learning set does not
improve the accuracy of the prediction of the level of QoE to be
expected, it is thus useless to use all the parameters of the
learning set.
[0022] According to another aspect of the method, the application
intended to be run on the user equipment is a web-browsing
application.
[0023] Web-browsing is responsible for a large fraction of the
Internet traffic in local area networks and is consequently the
application for which end users tend to be demanding in terms of
QoE. It is therefore interesting to predict a level of QoE to be
expected for web-browsing.
[0024] According to another aspect of the method, the parameter
representative of the QoE of the application under different
wireless transmission conditions is the page load time.
[0025] The page load time is considered one of the main indicators
when it comes to web-browsing experience.
[0026] The method further comprises: [0027] computing a mapping
between the page load time and a mean opinion score.
[0028] Mapping the page load time and the mean opinion score avoids
costly user involvement.
[0029] According to another aspect of the method, the parameters
representative of the transmission conditions of the wireless link
of significant influence on the level of QoE of said application
are an average physical layer transmission rate, a frame delivery
ratio, and parameters representative of a business of a
transmission medium of the wireless link due to interferences from
wireless equipments located in a vicinity of the user
equipment.
[0030] During the learning phase, it is determined that among all
the parameters of the learning sets these four parameters are the
more relevant for an accurate prediction of the level of QoE. The
interferences from other wireless equipments are due to different
types of wireless communications, e.g. Wi-Fi or non Wi-Fi
communications.
[0031] According to another aspect of the method, the parameters
representative of the transmission conditions of the wireless link
are obtained by monitoring data transmission conditions through the
wireless link during normal usage of the WLAN.
[0032] According to another aspect of the method, the parameters
representative of the transmission conditions of the wireless link
are collected by the access point.
[0033] Since the access point is the master node of every wireless
local area network, it is the best location to monitor and collect
data related to wireless transmission.
[0034] According to another aspect of the method, computing the
level of QoE of said application is based on the mapping of the
parameters representative of the transmission conditions of the
wireless link of significant influence on the level of QoE and the
mean opinion score.
[0035] The method relies on the use of the correlation established
between the parameters representative of the transmission
conditions of the wireless link of significant influence on the
level of QoE and the mean opinion score during the learning
phase.
[0036] According to another aspect of the method, computing the
level of QoE of said application is based on the mapping of the
parameters representative of the transmission conditions of the
wireless link and the mean opinion score.
[0037] Another aspect of the invention is a circuit comprising a
processor, a memory and a wireless node, the memory comprising
instructions, which, when performed by the processor, perform a
method according to an embodiment of the invention.
[0038] Another aspect of the invention is a gateway comprising a
circuit comprising a processor, a memory and a wireless node, the
memory comprising instructions, which, when performed by the
processor, perform a method according to an embodiment of the
invention. Some processes implemented by elements of the invention
may be computer implemented. Accordingly, such elements may take
the form of an entirely hardware embodiment, an entirely software
embodiment (including firmware, resident software, micro-code,
etc.) or an embodiment combining software and hardware aspects that
may all generally be referred to herein as a "circuit", "module" or
"system`. Furthermore, such elements may take the form of a
computer program product embodied in any tangible medium of
expression having computer usable program code embodied in the
medium.
[0039] Since elements of the present invention can be implemented
in software, the present invention can be embodied as computer
readable code for provision to a programmable apparatus on any
suitable carrier medium. A tangible carrier medium may comprise a
storage medium such as a floppy disk, a CD-ROM, a hard disk drive,
a magnetic tape device or a solid state memory device and the like.
A transient carrier medium may include a signal such as an
electrical signal, an electronic signal, an optical signal, an
acoustic signal, a magnetic signal or an electromagnetic signal,
e.g. a microwave or RF signal.
BRIEF DESCRIPTION OF THE DRAWINGS
[0040] Embodiments of the invention will now be described, by way
of example only, and with reference to the following drawings in
which:
[0041] FIG. 1 represents an access point communicating with a
station via a wireless communication,
[0042] FIG. 2 represents data rates of a wireless communication
according to FIG. 1, and
[0043] FIG. 3 represents a flow chart illustrating the steps of a
method for predicting a level of QoE of an application intended to
be run on a station according to one or more embodiments of the
invention.
DETAILED DESCRIPTION
[0044] It should be understood that the elements shown in FIG. 1
may be implemented in various forms of hardware, software or
combinations thereof. Preferably, these elements are implemented in
a combination of hardware and software on one or more appropriately
programmed general-purpose devices, which may include a processor,
memory and input/output interfaces. Herein, the phrase "coupled" is
defined to mean directly connected to or indirectly connected with
through one or more intermediate components. Such intermediate
components may include both hardware and software based
components.
[0045] The present description illustrates the principles of the
present disclosure. It will thus be appreciated that those skilled
in the art will be able to devise various arrangements that,
although not explicitly described or shown herein, embody the
principles of the disclosure and are included within its spirit and
scope.
[0046] All examples and conditional language recited herein are
intended for instructional purposes to aid the reader in
understanding the principles of the disclosure and the concepts
contributed by the inventor to furthering the art, and are to be
construed as being without limitation to such specifically recited
examples and conditions.
[0047] Moreover, all statements herein reciting principles,
aspects, and embodiments of the disclosure, as well as specific
examples thereof, are intended to encompass both structural and
functional equivalents thereof. Additionally, it is intended that
such equivalents include both currently known equivalents as well
as equivalents developed in the future, i.e., any elements
developed that perform the same function, regardless of
structure.
[0048] Thus, for example, it will be appreciated by those skilled
in the art that the block diagrams presented herein represent
conceptual views of illustrative circuitry embodying the principles
of the disclosure. Similarly, it will be appreciated that any flow
charts, flow diagrams, state transition diagrams, pseudocode, and
the like represent various processes which may be substantially
represented in computer readable media and so executed by a
computer or processor, whether or not such computer or processor is
explicitly shown.
[0049] The functions of the various elements shown in the figures
may be provided through the use of dedicated hardware as well as
hardware capable of executing software in association with
appropriate software. When provided by a processor, the functions
may be provided by a single dedicated processor, by a single shared
processor, or by a plurality of individual processors, some of
which may be shared. Moreover, explicit use of the term "processor"
or "controller" should not be construed to refer exclusively to
hardware capable of executing software, and may implicitly include,
without limitation, digital signal processor ("DSP") hardware, read
only memory ("ROM") for storing software, random access memory
("RAM"), and nonvolatile storage.
[0050] Other hardware, conventional and/or custom, may also be
included. Similarly, any switches shown in the figures are
conceptual only. Their function may be carried out through the
operation of program logic, through dedicated logic, through the
interaction of program control and dedicated logic, or even
manually, the particular technique being selectable by the
implementer as more specifically understood from the context.
[0051] In the claims hereof, any element expressed as a means for
performing a specified function is intended to encompass any way of
performing that function including, for example, a) a combination
of circuit elements that performs that function or b) software in
any form, including, therefore, firmware, microcode or the like,
combined with appropriate circuitry for executing that software to
perform the function. The disclosure as defined by such claims
resides in the fact that the functionalities provided by the
various recited means are combined and brought together in the
manner which the claims call for. It is thus regarded that any
means that can provide those functionalities are equivalent to
those shown herein.
[0052] In the following description, example methods for predicting
a level of QoE of an application intended to be run on a station or
user equipment, are described, as well as a device performing the
methods. For purposes of explanation, various specific details are
set forth in order to provide a thorough understanding of preferred
embodiments. It will be evident, however, to one skilled in the art
that the present disclosure may be practiced without these specific
details.
[0053] A CPE device includes, but is not limited to, for example a
controller, e.g. a microprocessor, a memory, in which an operating
system is stored for the operation of the CPE device, a wireless
node for a wireless communication, and a circuit for a broadband
connection, e.g. an xDSL connection. The wireless node includes,
but is not limited to, a software driver, a physical layer with
data buffers, and an antenna. A CPE device of this kind is for
example an access gateway.
[0054] The wireless node is controlled by the software driver which
executes a number of background tasks during operation of the
wireless node, e.g. dynamic rate adaptation, packet aggregation,
channel quality monitoring, and the like. On top of signal
manipulations, the wireless driver also embeds an IEEE 802.11
protocol stack with the associated IEEE defined management and
control messaging. The wireless driver will hence inject a number
of management and control packets in the data stream, making it
difficult to analyze a link by transparently looking at the data
frame exchange only.
[0055] An arrangement illustrating a wireless communication is
schematically depicted in FIG. 1: An access point 1 communicates
with a station 2, or user equipment 2, via a wireless link 3. A
station 2 maybe for example a smartphone, a tablet, a laptop, etc.
The access point 1 includes a circuit comprising a microprocessor
10, a memory 11, a wireless node 12 for the wireless link, and a
monitor application 13. The station 2 includes a second circuit
comprising a microprocessor 20, a memory 21, and a wireless node 22
for the wireless link. The wireless node 12 includes a physical
layer 14 and a link layer 15, and the wireless node 22 includes a
physical layer 24 and a link layer 25. The access point 1 is in
particular a CPE device, for example a residential gateway
establishing with the station 2 a home network of an end user. The
monitor application 13 is included for analyzing and evaluating the
wireless link 3 and retrieves in particular parameters
representative of transmission conditions of the wireless link
3.
[0056] The monitor application 13 comprises instructions for the
microprocessor 10 and the monitor application 23 comprises
instructions for the microprocessor 20, which are included for
diagnosing the wireless link 3 and which gather an information set
about the wireless link 3. The information set includes in
particular actual data rate, physical layer data rate, number of
spatial streams, channel bandwidth, medium availability and
Received Signal Strength Indicator (RSSI). Monitor data are
gathered in a passive mode, in which a data transmission is
monitored between the access point 1 and the station 2 or vice
versa.
[0057] FIG. 2 illustrates the possibilities which have to be
considered when diagnosing the Wi-Fi performance between the access
point 1 and the station 2. A unidirectional link 3' from the access
point 1 to the station 2 is examined. The theoretical maximum data
rate 30 for this link is given by the capabilities of the access
point 1 and the station 2, called here MaxNegotiatedPhyRate or
MaxPhyRate, which is for example 130 MB/s in case an IEEE 802.11n
standard with 20 MHz channel bandwidth and two spatial streams is
selected for the transmission between the access point 1 and the
station 2. This is thus the maximum achievable link speed, 100%,
which is only a theoretical value, because for most situations
physical limitations come into play: the received signal strength
RSSI at the station side is reduced for example due to the distance
between the access point 1 and the station 2 and path loss due to
any walls or other obstacles and reflections. Also the number of
spatial streams has to be determined. The practically attainable
data rate 31, called here PhysLimitsPhyRate, is therefore less than
the data rate 30.
[0058] Further performance can be lost due to interference close to
the station 2, which is not seen by the access point 1, called here
far end interference FEIF: this can be any microwave source like RF
Babyphone, microwave oven or a hidden Wi-Fi node, and leads to a
further reduced data rate, called here TrainedPhyRate 32. Similar
interference can appear at the access point 1, called here near end
interference NEIF: This will reduce the available data rate 32 to a
data rate 33, MediumBusyOtherWiFi. Further performance can be lost
by sharing the medium with other Wi-Fi traffic, which can be caused
by WLAN traffic in the home network, but also by Wi-Fi traffic of a
neighboring network.
[0059] In order to monitor the data traffic of the physical layer,
the layer 1 of the OSI (Open Systems Interconnection Model) model,
transmission conditions of the traffic that is transmitted and
received by the Wi-Fi node of the residential gateway, the
residential gateway includes a monitor application receiving all
received and transmitted packets. The monitor application has
access to the following blocks:
[0060] Transmit (TX) packet queue, TX packets
[0061] Receive (RX) packet queue, RX packets
[0062] Transmit/Receive signal indicators (RSSI)
[0063] Although there are solutions describing a link between
network transmission conditions, such as packet loss, latency and
bandwidth and QoE, none of them teaches a link between parameters
representative of the transmission conditions of a wireless link,
such as a Wi-Fi link, Phy Rate; Wi-Fi medium business; etc, and QoE
s.
[0064] FIG. 3 represents a flow chart illustrating the steps of a
method for predicting a level of QoE of an application intended to
be run on a station according to one or more embodiments of the
invention. An application is for example web-browsing, video
streaming, voice over IP (VoIP), etc. The application is run on a
station 2 or user equipment 2, such as a smartphone, or a computer
connected to the Internet through a Wi-Fi link. In the following
example, the considered application is web-browsing.
[0065] In order to determine the influence of Wi-Fi transmission
conditions on the QoE for a given application, a plurality of
transmission conditions of the Wi-Fi link are defined and for each
of these transmission conditions, parameters representative of the
transmission conditions are collected passively by the access
point, during a leaning phase. These collected parameters are then
processed by the monitor application 13, 23. In the meantime, i.e.
during the learning phase, the station 2 performs a series of
web-browsing tasks under the different transmission conditions of
the Wi-Fi link and each time, a parameter representative of the QoE
is measured.
[0066] Then a mapping is done between the parameters representative
of the transmission conditions of the Wi-Fi link processed by the
monitor application 13, 23 and the measured parameter
representative of the QoE.
[0067] The learning phase comprises steps E1 to E6 of the method
according to an embodiment of the invention.
[0068] This mapping is then used to predict a level of QoE of an
application intended to be run on the station. In order to do so,
the parameters representative of the transmission conditions of the
Wi-Fi link are collected passively by the access point. Then using
the mapping obtained during the learning phase, an expected level
of QoE for the application is obtained.
[0069] Thus, during step E1 different transmission conditions of a
Wi-Fi link are determined. In order to do so, the wireless
transmission conditions are modified, for example, along axis:
PhyRate and medium availability.
[0070] A variation in PhyRate is realised by introducing
attenuation on the transmission path established between the access
point and the station. For example, attenuations of 6, 12, 15, 18,
19 and 20 dBs are introduced, reducing the PhyRate.
[0071] The medium may be unavailable due to interferences from both
Wi-Fi and no Wi-Fi communications. In order to emulate non Wi-Fi
communications a narrowband sinewave signal is generated to block
the access point CCA. In order to emulate Wi-Fi communications, a
second pair access point/station generates competing Wi-Fi traffic
which blocks the medium.
[0072] The different transmission conditions of the Wi-Fi link
correspond to the different combinations of PhyRate and medium
availability scenarios.
[0073] During a step E2, sets of parameters representative of the
transmission conditions of the Wi-Fi are collected passively by the
access point for each of the transmission conditions defined during
step E1 by the monitor application 13, 23.
[0074] In the meantime, during a step E3, the station 2 performs a
series of web-browsing tasks under the different transmission
conditions of the Wi-Fi link determined during step E1, and each
time, a parameter representative of the QoE is measured. In the
case of web-browsing, such a parameter representative of the QoE is
for example the page load time.
[0075] Thus during step E3, the station 2 accesses 10 times web
pages such as google.com, twitter.com, amazon.fr, etc., and each
time, the page load time is measured.
[0076] During a step E4, the page load time of a web page is mapped
with a mean opinion score (MOS) defined in ITU-T recommendation
G.1030. The MOS is an integer comprised between 1 and 5, 1
corresponding to the lowest QoE score and 5 corresponding to the
highest QoE score. Thus the longer the page load time the lower the
MOS. For example a MOS of 1 corresponds to a page load time of 10
seconds, since users usually lost focus after 10 seconds of
waiting; and a MOS of 5 corresponds to the mean page load time per
web page.
[0077] During a step E5, a mapping between the sets of parameters
representative of the transmission conditions of the Wi-Fi link and
the parameter representative of the level of QoE of the application
measured for each web page access is computed.
[0078] For example a vector representing both the transmission
conditions and the MOS is generated for each web page access. The
RRSI and average Tx/Rx PHY rate strongly correlate with variations
in the SNR of the Wi-Fi link since they indirectly measure the link
quality. Information representative of the medium unavailability
due to Wi-Fi and no Wi-Fi traffic is also reported. These vectors
then feed a predictor such as the Support Vector Regressor
(SVR).
[0079] The mapping obtained during step E5 enables to estimate an
expected level of QoE considering only Wi-Fi effects.
[0080] In a step E6, a selection is performed to determine which
parameters representative of the transmission conditions of the
Wi-Fi from the set of parameters collected by the access point are
the most relevant for predicting the level of QoE for a given
application.
[0081] These selected parameters called parameters representative
of the transmission conditions of the wireless link of significant
influence on the level of QoE of the given application are obtained
by feeding the predictor with different combinations of parameters
representative of the transmission conditions of the wireless link
and checking the accuracy of the predicted QoE with the MOS
corresponding to the set of parameters representative of the
transmission conditions of the wireless link from which the
combinations of parameters representative of the transmission
conditions of the wireless link are extracted.
[0082] For example, for web-browsing, the parameters representative
of the transmission conditions of the wireless link of significant
influence on the level of QoE are the average Tx PHY rate, the
frame delivery ratio, MediumBusy, and MediumBusyOtherWi-Fi.
[0083] In a step E7, parameters representative of the transmission
conditions of the Wi-Fi link are collected passively by the access
point on a periodic basis.
[0084] In a step E8, a level of QoE is computed for a given
application, e.g. web-browsing, by using the mapping obtained on
step 5. The parameters used for computing the level of QoE are
either the set of parameters representative of the transmission
conditions of the Wi-Fi link collected by the access point, or
depending on the application intended to be run on the station,
parameters representative of the transmission conditions of the
wireless link of significant influence on the level of QoE as
selected during step E6.
[0085] Although the present invention has been described
hereinabove with reference to specific embodiments, the present
invention is not limited to the specific embodiments, and
modifications will be apparent to a skilled person in the art which
lie within the scope of the present invention.
[0086] Many further modifications and variations will suggest
themselves to those versed in the art upon making reference to the
foregoing illustrative embodiments, which are given by way of
example only and which are not intended to limit the scope of the
invention, that being determined solely by the appended claims. In
particular the different features from different embodiments may be
interchanged, where appropriate.
* * * * *