Elimination of RLAN Interference on Weather Radars by Channel Allocation in 5 GHz Band
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Elimination of RLAN Interference
on Weather Radars
by Channel Allocation in 5 GHz Band
Zoltán Horváth Dávid Varga
Budapest University of Technology and Budapest University of Technology and
Economics, Department of Telecommunications Economics, Department of Telecommunications
Budapest, Hungary Budapest, Hungary
E-mail: horvathz@hit.bme.hu E-mail: varga.david@duvinet.hu
Abstract — Weather radars are used for short term standards. The details of DFS and its problems are
meteorological prediction all over the world. Radars discussed in Subsection 2.2.
in 5GHz band can be jammed by RLAN devices (e.g. Subsection 2.3 presents some of the solutions we
Wi-Fi routers). We introduce the background of this propose, that could possibly detect and even filter RLAN
problem, and analyze the weakness of the current interference at the radar systems. Some of these solutions
solution (DFS - Dynamic Frequency Selection). We are easier to manage, some are only theoretical, and
propose some other solutions, and introduce our could not be implemented because of the technical
channel allocation technique. We analyze it parameters of the radars.
theoretically by modeling the radar operation and As the main topic of this paper, in Section 3 we
RLAN traffic, and we also show its high efficiency in introduce a method, which does not only detect and filter
practice, based on well-known IEEE 802.11 RTS/CTS RLAN interference, but also eliminates it before it could
mechanism. actually happen. We present here a preventive solution,
which is based on channel allocation. It can occupy the
802.11a, interference, weather radar, RLAN, Wi-Fi, channel for the radar while the measurements are done,
WLAN, 5 GHz band, RTS/CTS, DFS by silencing the RLAN transmitters in direction. In
Section 3 we present the overview of the main idea and
I. INTRODUCTION some background information, and we also introduce the
allocation technique in details using traffic models and
The introduction of modern meteorological radars has estimation, and present some evaluation of it.
revolutionized accurate short-term forecasts. But at that Finally, conclusions are summarized in Section 4.
time nobody thought, that the quickly spread wireless
networks (RLAN – Radio Local Area Network, in this II. INTERFERENCE AND SOME SOLUTIONS
paper synonym for Wi-Fi and WLAN) [2] would affect
negatively the performance of radar systems – in a large A. Introduction of the interference
number of countries worldwide [4], [5], [6]. As part of the European weather forecast system,
In the beginning of the next section (Subsection 2.1) there are three working weather radars in Hungary under
we show how this interference appears on the screen of the supervision of Hungarian Meteorological Service
meteorological radars, and discuss the serious (OMSZ) and several others throughout Europe and all
consequences it may cause. We also specify the origins over the world. These radars measure the atmosphere
of the interference from a technical point of view. precipitation.
Of course, as the problem expanded, engineers tried Based on the information and pictures provided by
to come up with a solution. This led to the development the OMSZ, Figure 1 shows the influence of the strays on
of DFS (Dynamic Frequency Selection), which is a a rough radar image. Each shade means a different dBZ
standardized method introduced in IEEE 802.11h. Of level, corresponds to the intensity of the reflected signal.
course, the RLAN devices need to comply with it, so If the shade represents a larger numerical value, it means
DFS compliance tests were introduced in the ETSI a higher received signal strength.
301 893 documents. The ETSI standard is still under The jammed layers indicate significant quantity of
development. Almost every year or two a newer version rain, so their influence is rather disturbing. It is also
is revealed, trying to make the tests be more similar to dangerous when the signals reflected by precipitation are
real life events. Unfortunately, the DFS still can not combined with the ones from the strays (see in the left
provide enough protection for the radar systems; many bottom of Figure 1), and as result we may come to a false
RLAN devices don’t perfectly comply with the conclusion regarding the quantity of the precipitation.
9781-4244-3941-6/09/$25.00 ©2009 IEEEThis may cause significant problems in the weather RLAN devices will not switch the channel, and the
forecasts and pre-estimations. DFS Slave will continuously jam the radar.
The layers and sectors appearing in the images are 4. We collected more than 50 certificates of 802.11a
mostly caused by IEEE 802.11a standard RLAN devices RLAN devices on the market. Most of them only
located close to ground and operating within the radar’s complied with older, v1.2.3 or v1.3.1 [3] versions of
frequency range [4], [5], [6], [7]. One of the (and ETSI. This means, that even if the device was called
frequently used) frequency bands where the DFS compatible at the time it was designed, it would
meteorological radars may operate is between 5600-5650 not certainly pass the newer versions of ETSI. But
MHz, which overlaps with 3 of the 802.11a channels these devices are still in operation, or even can be
(No. 120, 124 and 128) [7]. bought and used.
5. There were some devices we actually tested, and some
of them let the end user enable or disable DFS or
Radar signal detection, although this function should
be automatically and always enabled.
C. Our proposed solutions
As we can see, DFS can not, and probably never will
provide a perfect solution against radar interference. We
came up with some ideas, detailed in [1]. Here we
provide a quick overview of them.
If we detect signals in the 20 MHz wide 802.11a
channel, out of the 1.25 MHz wide spectrum of the radar
at the same time of the radar echo reception, we may say
that there was RLAN interference. In this case the result
of radar measurements can be ignored.
Interference can also be detected or filtered in time
scale, if we only look for reflected radar signals in the
time period when they could have returned. This possible
time period can be calculated from the typical minimum
and maximum height of the clouds in the actual season
Figure 1. RLAN interference in the picture of the meteorological and the altitude angle of the radar.
radar Interference can also be detected or filtered, if
There are not only clouds in the picture but also strips and sectors precipitation maps are received from other sources,
are shown signed by dotted curves. These are caused by RLAN including satellites or terrestrial optical camera system,
interference, and inhibit observing of the precipitation.
which can observe without this interference.
B. DFS and its problems If we use more radars to scan a selected area, then by
Dynamic Frequency Selection (DFS) has become the comparing the different measurements we are able to
technological solution to dissolve the interference issues detect or filter the interference. This can be done by
between weather radars and RLAN devices. The IEEE specific algorithms or majority voting in case of using at
802.11h standard [2] and the ETSI EN 301 893 least three radars.
directives [3] summarize the functional requirements There is a chance to separate radar and RLAN
(including DFS) for 5 GHz RLANs. signals, if we use some kind of modulation on the radar
In practice, a device is marked DFS compatible, if it signals, and we detect the reflected signals via an
passes the DFS tests of the actual ETSI EN 301 893 appropriate demodulator. Unfortunately, this method
standard (further: ETSI). On the other hand, it is would require the modification of the radar signals in a
questionable whether this DFS compatibility provides way that current magnetron based weather radars are
enough protection for meteorological radars. We unable to provide.
examined the efficiency of DFS using ETSI v1.4.1 [3] The possible solutions mentioned above are useful
both theoretically and in practice [1], and found that the only for detecting and filtering the already existing
following problems still exist. We introduce briefly these interference. Using our proposed method discussed in
already known and those revealed by us problems here. Section 3, we may eliminate the interference before it
1. The minimum pulse width for testing against DFS is even existed. For this allocation we use the well-known
0.8 µs, but Hungarian radars also use 0.4 µs, which is RTS/CTS mechanism of IEEE 802.11 [2], which sets the
harder to detect. NAV of the RLAN stations, thus silencing them for the
2. Channel Availability Check time is only 60 seconds, time the actual measurement takes place.
but it can be shorter than the radar rotation period.
(Note that this has been changed to 10 minutes in
ETSI v1.5.1 [3].)
3. DFS Slave devices are not required to sense radar
signals. When a DFS Slave device faces the radar, and
the radar signal is too weak at the DFS Master, theThe duration between two following pulses can be
III. CHANNEL ALLOCATION: MODELING, ANALYSIS divided into two periods (see Figure 2). The first one is
AND EVALUATION between the transmission of a pulse and the theoretical
limit when its echo is received by the radar. This
A. Overview measurement time (Tmeasure [s]) is calculated from
During the operation the radar rotates at a specific maximum range of the radar (R [m]) and signal
altitude angle (elevation) or scans a given sector and then propagation speed (‘speed of light’) (c [m/s]):
raises the elevation. In the meantime it transmits radar 2 ⋅R [s] (4)
T =
measure
pulses and receives echoes, reflected by hydrometeors c
(raindrop, ice) and attenuated by absorption and free The second period is the idle time between the end of
space loss. This backscattering is limited in time by the observation and the next pulse, called Time of
attenuation and radar signal sensitivity. After each and InterMeasurement Gap (IMG) (TIMG [s]):
before the next measurement there is an idle period that 1 2⋅R [s] (5)
T =T −T
IMG PR = −
measure
will be called ‘InterMeasurement Gap’ (IMG). In our PRF c
channel allocation technique this gap is used, so the radar The pulse length is negligible compared to other
operation and functionality is not affected. (See Figure durations; therefore it is omitted in this formula. Using
2.) these parameters the utilization of the radar and the
channel is:
T 2 ⋅ R ⋅ PRF (6)
U = measure =
measure
TPR c
2) Modeling of the RLAN traffic
Not only radar operation, but also RLAN traffic
should be described in order to be able analyze and
model the proposed solution.
Scenario I: RLAN traffic without ACKs
Figure 2. Signal of the radar in time domain In Scenario I RLAN traffic consists of data frames
only without any acknowledgement (ACK), therefore
The basic idea behind channel allocation is to defer RLAN transmission contains frames and idle times. In
the transmission of the RLAN devices for the time the general distributions of frame size and arrival times are
radar faces their direction, thus we have to allocate that unknown. We use this deterministic traffic pattern for
time slot to the radar. This can be done by sending out modeling, because this is the worst case: all of the frames
information to the RLAN stations prior to the critical use the maximum time duration (with maximum size)
interval, which forces them to be silent until the radar (Tframe [s]) and minimum interframe time (IFT) (Tinterframe
turns over. These messages can be sent during the IMG. [s]), consequently this case gives the most occupied
For analyzing and evaluating our proposed preventive channel (see Figure 3).
solution building a model is indispensable.
B. Modeling of the radar and RLAN traffic
At first radar and RLAN traffic are described by their
timing and other parameters.
1) Modeling of the radar operation
As introduced in Subsection 3.1, the radar antenna Figure 3. Traffic scheme and timing for RLANs without ACKs
rotates under operation. Rotation speed is given in RPM
(Rotation per Minute) generally in most of the radar Frame time (Tframe [s]) consists of two parts: fixed
specifications. This value – denoted by ‘β’ – is needed in duration for frame initialization (Tframe_init [s]) and the other
degree/sec (°/s) measure for further calculation. part depending on frame size (Sframe [bit]) and bit rate of
RPM ⋅ 360 [°/s] (1) transmission (BRframe [bit/s]):
β= = RPM ⋅ 6
60 S [s] (7)
T =T
frame + frame
frame _ init
Another main parameter of the radars is the BR frame
horizontal beam width (α) measured in degrees (°). Channel utilization (Uframe) can be calculated with
Every radar rotation has a period, when the radar these parameters:
scans a specific point, as described in Subsection 3.1. Tframe (8)
This ‘Time-on-Target’ (TToT) is constant for each point: U =
frame
Tframe + Tint erframe
α [s] (2)
TToT =
β Scenario II: RLAN traffic with ACKs
During this period radars periodically transmit pulses. Unlike the previous scenario, RLANs mostly use
This is specified as ‘Pulse Repetition Frequency’ (PRF) acknowledgements (ACKs) for reliable transmissions.
in Hz (1/s). It has the same meaning as Pulse Repetition After sending the data frame (Tframe) RLAN devices wait
(PR) Time (TPR): (TACK_delay) for the ACK (TACK). Similarly to the ‘RLAN
1 [s] (3) traffic without ACKs’ model this one simulates the worst
T =PR
PRF case in a deterministic way. The frame and ACKtransmission periods can be grouped together (called successful allocation can be maximized by the maximum
‘Extended Frame’), supposing that the further channel rate of CAF frequency.
allocation technique can not interrupt this frame-ACK
communications (see Figure 4).
Figure 5. Scheme and timing for CAFs and RLAN traffic
Figure 4. Traffic scheme and timing for RLAN with ACKs This results a deterministic structure of channel
In acknowledged RLAN transmissions frames, ACKs and idle time allocation transmission with using short CAFs (TCAF [s])
between them (ACK delay) should be combined into ‘Extended
Frame’. and as short as possible idle time (‘InterCAF Time’)
(TICAF [s]) between them (see Figure 5). Duration of CAF
This grouping increases the channel utilization can be calculated the same way as duration of data
according to the worst case estimation. This allows a frames with the parameters: fix time for initialization
more simple way of modeling RLAN traffic with ACK, (TCAF_init [s]), size of CAF (SCAF [bit]) and transmission bit
too. rate (BRCAF [bit/s])
Duration of frames and ACKs (TACK [s]) are S [s] (12)
calculated the same way as before: T =T
CAF + CAF
CAF _ init
BR CAF
S [s] (9)
T ACK=T + ACK
ACK _ init
This channel allocation operation is used only in
BR ACK InterMeasurement Gaps of radar, as discussed in
And the ‘Extended Frame’ time (Textended_frame [s]) using Subsection 3.1.
‘ACK Delay Time’ (TACK_delay [s]) as mentioned above:
[s] (10) D. Analysis of proposed solution
Textended _ frame = Tframe + TACK _ delay + TACK
As mentioned above, CAF can block RLAN traffic,
Maximum usage of channel (Uextended_frame) can be when an RLAN device detects it. It can occur, when the
defined in this scenario, too. whole CAF is received from its beginning without
Textended _ frame (11) overlapping with RLAN frames. RLANs using CSMA
U =
extended _ frame
Textended _ frame + Tint erframe (Carrier Sense Multiple Access) do not transmit frames,
This is higher than Uframe, because ‘Extended Frames’ if the beginning of any frame (including CAF) is
are larger than original frames but ‘InterFrame Time’ is detected. Therefore this successful reception of a CAF
equal. becomes a successful channel allocation, too. Applying
RLAN traffic and channel allocation models described in
C. Modeling of the channel allocation Subsection 3.1, the number of successful CAFs during an
The overview of the channel allocation technique was interframe time (IFT), NCAF_IFT can be estimated:
given in Subsection 3.1. To achieve our goal Tint erframe (13)
N =
CAF _ IFT
(minimizing the traffic of the RLANs during radar scan) TCAF + TICAF
we use Channel Allocation Frames (CAFs) (e.g. CTS) in In this case we supposed that CAFs and RLAN
general. RLAN traffic can be blocked for a specific frames are not synchronized, and one’s periodicity is not
duration with each CAF. But this event occurs only in exactly a multiple of other’s in our deterministic model.
the case when an RLAN device receives a CAF This condition guarantees the variety of relative positions
successfully. Reception of CAF can be successful if and of CAFs and RLAN frames.
only if the beginning of the CAF is in an interframe time We supposed that CAF traffic does not affect RLAN
(IFT) of the RLAN traffic. However, detecting IFTs on traffic, only when successfully receiving a CAF. If this
the radar side and using detection-based adaptive assumption is incorrect, than CAFs can occur longer idle
transmission of CAFs can be difficult and it is periods and RLAN frame retransmission (due to frame-
unnecessary. When the radar receives signals of more CAF collision) in RLAN traffic, too. However, in this
than one RLAN simultaneously, it can detect fewer and case utilization of the RLAN channel can not exceed the
shorter idle periods due to overlapping RLAN traffics. worst case limit, as described in Scenario I and II.
However, CAFs can be transmitted successfully not only The interframe frequency (number of IFT in one
in these periods, because each RLAN has its own IFTs, second) (FIFT [1/s]) can be calculated as
when the allocation can occur. It can be difficult to 1
separate traffic of RLANs, and derivate when and which FIFT = [1/s] (14)
one has its IFT. Tframe + Tint erframe
We decided, our proposed solution use a simple Tframe can be replaced with Texteneded_frame as necessary.
deterministic RLAN-traffic-independent CAF Using both values (NCAF_IFT and FIFT), the average
transmission without using detection and a complex frequency of successful CAFs in IFT (FCAF_IFT [1/s]) can
adaptive mechanism (with difficulty above). The rate of be estimated, too:FCAF _ IFT = NCAF _ IFT ⋅ FIFT = E. Evaluation in practice
[1/s] (15)
Tint erframe 1 1 − Uframe In practice most of the parameters are defined in
= ⋅ = standards and specifications. We use weather radar
TCAF + TICAF Tframe + Tint erframe TCAF + TICAF
This result demonstrates our previous two worst case parameters as specified and generally used: RPM=2
assumptions: efficiency can be increased by minimizing (max. 6), α=1° (beam width in 3 dB), PRF= 400 Hz
both RLAN traffic utilization and CAF cycle duration. (interval 250-1300 Hz), R=240 km. The values of the
This formula (15) can be used not only in the case of RLAN traffic parameters come from IEEE 802.11,
deterministic, but also in the case of random RLAN 802.11a (including RTS/CTS) [2]. For practical
traffic, only the utilization of the channel should be evaluation of this allocation technique, the worst case or
known. default values of parameters are applied. We use
The above result is modified by usable time slot, so minimum bit rates of 6 Mbps (max. 54 Mbps) and
the more relevant value is the frequency of successful initialization time 20 µs (preamble (16 µs) + PLCP (4
CAFs in IFTs in ‘InterMeasurement Gaps’ (IMG) µs)) for all communications. We set also other durations
(FCAF_IFT_IMG [1/s]): as follow: Tinterframe=34 µs (DIFS + 1 Slot Time),
TIMG TACK_delay=16 µs (SIFS), TNAV=32267 µs (15 bit for NAV in
FCAF _ IFT _ IMG = FCAF _ IFT ⋅ = [1/s] (16) CTS in µs) and TICAF=16 µs (we can specify it freely, but
TPR
for easier implementation and compatibility we set it to
(1 − U frame ) ⋅ (1 − Umeasure )
= FCAF _ IFT ⋅ (1 − Umeasure ) = SIFS). ACKs and CAFs (CTS) are 14 bytes, as in
TCAF + TICAF standards [2]. In this worst case scenario, we use
Accordingly, the average number of successful maximum data frame size (1516 bytes), supposing
channel allocations during each IMG is: Ethernet traffic (64-1516 bytes). Using these values the
N =F ⋅T =
(1 − U frame ) ⋅ TIMG (17) parameters of our model can be calculated, see Table 1.
CAF _ IFT _ IMG CAF _ IFT IMG
TCAF + TICAF TABLE I. CALCULATED PARAMETERS
Another useful measure can be the successful channel Parameter Value Parameter Value
allocations during a radar scan (Tcont) (NCAF_IFT_IMG_ToT): Tmeasure 1600 µs TACK= TCAF 38.67 µs
N CAF _ IFT _ IMG _ ToT = FCAF _ IFT _ IMG ⋅ TToT =
(18) TIMG 900 µs Uframe 86.73 %
(1 − U frame ) ⋅ (1 − Umeasure ) α Umeasure 64 % Uextended_frame 89.06 %
= ⋅
TCAF + TICAF β TToT 83.33 ms NCAF_IFT_IMG 1.8
Each successful channel allocation protects the radar Tframe 222.1 µs NCA_ToT_min 3
from RLAN traffic for duration (TCAF_NAV), that is the sum Textended_frame 332.8 µs ρ 20.01
of the time value (NAV – Network Allocation Vector)
contained in CAF (TNAV) and the time of CAF itself (TCAF) The results of worst case calculations and estimations
(See Figure 5.): can be seen in Table 1. We find that since the radar is in
TCAF _ NAV = TCAF + TNAV [s] (19) idle state in 36 % of its time, there is a 900 µs IMG for
channel allocation. During an IMG, 1.8 successful
With this value the minimum numbers of successful channel allocations occur in average, but only 3 are
channel allocations in each scan period (TToT) (NCA_ToT) needed during a 83.33 ms ‘Time-on-Target’. With these
can be estimated: worst case parameters the proposed solution allocates
⎡ TToT ⎤ ⎡ 1 α⎤ (20) channels at least 20 times more often than needed.
N =
CA _ ToT _ min = ⎢ ⋅ ⎥ ⎢ ⎥
⎢ TCAF _ NAV ⎥ ⎢ TCAF + TNAV β ⎥ These results can be much better if the estimation is
One of the most important values that can describe based on real parameter values, not on the worst case.
the efficiency of the proposed solution (ρ) is the ratio of For example, using a real distribution of frame sizes
occurred effective channel allocations (NCAF_IFT_IMG_ToT) and gives some improvement. Supposing that the frame size
the number of needed (NCA_ToT_min). distribution is similar to as it was in 2000 in world wide
(1 − U frame ) ⋅ (1 − Umeasure ) α
networks, estimation can be much better. Based on an
⋅ earlier publication [8], we analyzed the cumulative
N CAF _ IFT _ IMG _ ToT TCAF + TICAF β (21)
ρ= = ≈ density function (CDF) and smoothed probability density
N CA _ ToT _ min ⎡ 1 α⎤ function (PDF) (or histogram) of the IP packet size. We
⎢ ⋅ ⎥
⎢ TCAF + TNAV β ⎥ can find 3 modes in it of packet size distribution. Only
TCAF + TNAV 14 % of the traffic has the maximal size, 19 % is around
≈ ⋅ (1 − U frame ) ⋅ (1 − Umeasure ) 570 bytes and almost 33% has the minimal size with 40
TCAF + TICAF
The approximation can be applied in case of bytes. Due to the payload encapsulation and framing
Tcont>>TCAF_NAV. This formula clearly shows which every packet gets 16-20 bytes additional overhead. Using
parameters can affect the efficiency of channel allocation these statistics and information, the average frame size
dominantly. This efficiency (ρ) can reach or exceed 1, if can be around 500 bytes. In this case, the efficiency (ρ)
T + TNAV (23) of the solution exceeds 35, which means that CAF occur
1 < CAF ⇔T >T NAV ICAF in the average 35 times more often than needed.
TCAF + TICAF
We can also analyze the relationship between the
efficiency and RLAN bit rate, frame size and using
ACKs. This comparison (Figure 6) shows that 20 is thelowest efficiency, but under some conditions even 115
can be reached. IV. CONCLUSIONS
In this paper we have addressed the problem of
interference between meteorological radars and RLAN
devices. We have evaluated the current solution – DFS –
and its limitations. We have proposed some new ways,
and detailed the most viable one: channel allocation
based on RTS/CTS. We have given models for radar
operations and RLAN traffic. We have shown that using
the proposed technique the interference can be
eliminated in a very efficient way, due to the mandatory
and embedded functionality of RTS/CTS and parameters
from standards.
Figure 6. The efficiency of the channel allocation technique We will try to test this solution in practice soon. We
expect this method to be implemented all over the world
F. Applicability and will solve the problem of 5 GHz interference.
We can see that the solution is more efficient than
needed under every circumstance. It can protect ACKNOWLEDGMENT
meteorological radars against RLAN interference using This work has been supported by Meteorological
simple RTS/CTS mechanism. Thus, the implementation Service (OMSZ), National Communications Authority
of this technique is not too difficult. A simple computer (NHH) in Hungary, and HSNLab, Budapest University
can send CTS frames continuously through a WLAN of Technology and Economics.
adapter, synchronized to radar measurement cycle. For
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