1
On Opportunistic Spectrum Access in Radar Bands:
Lessons learned from Measurement of Weather
Radar Signals
Zaheer Khan, Janne J. Lehtomäki, Risto Vuohtoniemi, Ekram Hossain, and
Luiz A. DaSilva
Abstract
The need for extra spectrum and the fact that a large amount of spectrum below 6 GHz is allocated to radar
systems has motivated regulatory bodies and researchers to investigate the feasibility of Dynamic Spectrum Access
(DSA) in radar bands. To design efficient wireless communication schemes that co-exist with radar systems, it is
essential that the wireless community understand well the operations of these systems in different bands. This paper
studies incumbent operations and usage patterns in the 5 GHz band, where weather radar systems dominate, dynamic
frequency selection (DFS) is employed as a sharing mechanism, and recent works have explored the possibility
to temporally share the spectrum with weather radars. We present a measurement based study of spectrum usage
by a weather radar in Finland. Our measurement results show that the weather radar’s scan patterns are quasiperiodic, and that use of sensing may not reliably detect radar signals due to its quasi-periodic scanning patterns,
and different vertical scanning angles. Finally, we present a framework for a database-assisted temporal sharing
co-existence mechanism, that takes into account the real occupancy behavior of the radar.
Index Terms
Spectrum sharing; radar bands; measurement; temporal sharing; weather radar; opportunistic access; database.
I. I NTRODUCTION
With the clear need for additional spectrum to support next generation mobile networks, regulatory
bodies in the US and Europe have set in motion several new initiatives that aim at identifying underutilized
portions of the licensed spectrum and exploring new models for spectrum sharing [1], [2]. In this context,
Z. Khan, Janne J. Lehtomäki, and R. Vuohtoniemi are with University of Oulu, Finland; L. A. DaSilva is with Telecommunications
Research Centre, Ireland, and Virginia Tech USA; and E. Hossain is with University of Manitoba, Canada.
This work was funded by Academy of Finland, National Science Foundation, USA, Natural Sciences and Engineering Research Council
of Canada (NSERC), and Science Foundation Ireland.
2
the proposals that deal with spectrum sharing in radar bands have generated particular interest, as radars and
radio-navigation infrastructure occupy a considerable amount of spectrum (roughly half of the spectrum
from 225 MHz to 3.7 GHz) and their usage efficiency is generally low [3]. Radar bands that are potential
candidates for spectrum sharing are between 960-1400 MHz (L-band), 2700-3650 MHz (S-band), and 5.05.850 GHz (C-band), as different wireless technologies such as LTE, WiMAX and WLAN can support
operation in one of these bands [1], [4], [5].
Different radar systems, such as meteorological radar, air surveillance radar, and several different military
radar systems, operate in the L, S and C bands. Radar systems have different operation characteristics
and interference protection criteria, due to which some radar systems may require complete protection
from harmful interference and have exclusive rights to operate in a given area and frequency band, and
others may allow opportunistic spectrum sharing in their bands [3]. Spectrum sharing may be supported by
different dynamic spectrum access techniques or a combination of these techniques, such as geolocation
databases, sensing (individual or cooperative), beaconing, etc. A discussion of tradeoffs among these
techniques is provided by [5].
Use of large geographical exclusion zones as a means for spectrum sharing with radar systems in
3550-3650 MHz has been proposed in [1]; however, this approach may not yield increased spectrum
utilization as most of the radar systems operate in or near dense urban areas. Dynamic frequency selection
(DFS) enabled devices currently share spectrum with radars in the 5 GHz band. DFS allows low power,
unlicensed communication devices to share spectrum with high power radar systems, using a detect and
avoid function. Differently from DFS, the recent work in [6] proposed an opportunistic temporal sharing
mechanism. This mechanism divides the area around a weather radar into three geographic zones and
allows temporal sharing of spectrum in the second geographic zone.
Efficient sharing between wireless communication systems and radars requires the wireless community
and the policy makers to better understand radar system operations, to determine their spectrum usage
patterns and know their protection requirements in a particular band in which they operate. Spectrum
measurement campaigns in radar bands are crucial for obtaining reliable spectrum occupancy results and
also for the design of appropriate spectrum sharing models. In this paper, we investigate the spectrum usage
pattern of radar systems and the potential use of opportunistic temporal spectrum sharing in radar bands.
In particular, we focus on approximately 400 MHz of spectrum in the 5 GHz band which was allocated for
the implementation of wireless access systems (WAS), including Radio Local Area Networks (RLANs),
on a co-primary basis, by the International Telecommunication Union (ITU) world radiocommunication
conference in 2003. The type of radar system that predominates in many parts of the world in this band
is a weather radar. Several recent studies have shown that exploiting temporal opportunities derived from
3
Fig. 1: Schematic diagrams of three different models for spectrum sharing in radar bands.
the weather radar antenna rotation can significantly increase the number of users that can utilize spectrum
sharing in the 5 GHz band. We first provide a review of the existing spectrum sharing methods in radar
bands, and highlight the merits and demerits of the existing techniques. Different from other works, we
present real spectrum measurements of a weather radar spectrum usage in the 5 GHz band. The weather
radar station is located near the town of Utajärvi, Finland, and the real spectrum usage data of the radar
is collected at two different locations. Using our measurement results we show that: 1) A weather radar’s
scan patterns are quasi-periodic, not periodic as claimed in some existing theoretical sharing models. 2)
Use of sensing may not be reliable for the detection of radar signals due to the use of quasi-periodic
scanning patterns. Finally, we also propose a framework for a database assisted opportunistic temporal
sharing of spectrum with weather radars. Our proposed framework takes into account the real spectrum
usage of a weather radar.
The rest of the paper is organized as follows. Section II presents an overview of the main methods
for spectrum sharing with radars. In Section III we present our measurement strategy, set up and results
relating to spectrum usage of a weather radar. Section IV presents our proposed framework. Finally, in
Section V we conclude with a discussion of some future directions for spectrum sharing with weather
radars.
II. S PECTRUM S HARING IN R ADAR BANDS : BACKGROUND
AND
C HALLENGES
Spectrum related to radar systems usage represents a significant portion of spectrum that has the potential
to be shared with wireless communication systems [1]. Different radar systems are designed for specific
4
TABLE I: A summary of challenges in the design of spectrum sharing techniques in the radar bands
Challenges
Various kind of radar systems
Reasons
The modern usage of radars is highly diverse, including navigation, defense and surveillance, and
each radar system tends to be distinctive in its spectrum usage. As a consequence there cannot be a
single spectrum sharing policy in different radar bands.
Sensitive receivers of radars
Radar receivers are extremely sensitive as they need to amplify tiny echoes at levels down to 10−2
of a picowatt. This requires some geographical exclusion zones as a means for spectrum sharing
with radar systems. Moreover, traditional radar receivers are designed with a focus on mitigating
interference from other radar (pulsed, low duty-cycle) emissions which are different from typical
wireless communications transmissions.
Mobile radar systems
Many radar systems include ground-based mobile, air and ship borne operations. Such operations
make challenging to come up with ways of detecting these radars and also avoiding interference with
them.
Security constraints
Parts of the radar frequency spectrum are used for military applications. Military radar systems are
in general classified. To know their operational characteristics such as spectrum usage patterns may
not be possible as such systems try not to be identified to avoid jamming.
Mission critical events
Urgent opportunistic access network muting may be required to enable full-band radar operations for
rare mission-critical events.
Sensing complexity
Sensing radar signals can be more complex than sensing communication signals as a radar’s operating
characteristics are different from a wireless communication system.
aa
applications and tend to be different in operation from one model to another. A radar system can be: 1) a
fixed ground-based (FGB) system; 2) a shipborne mobile system; 3) an airborne mobile system, each of
which may require a different spectrum sharing strategy. Moreover, radar systems are used for applications
such as: 1) weather surveillance; 2) navigation/surface search; 3) air/maritime surveillance; 4) defense and
security, and each of these applications requires different modes of operation. A qualitative evaluation of
the opportunities and challenges of spectrum sharing in radar bands is performed by [3], [5]. Although
different characteristics make it difficult to develop a unified spectrum sharing policy for communication
systems to co-exist with radar systems across the different bands, there are spectrum bands where some
types of radars do predominate and a large number of these radars are fixed ground-based (FGB) systems.
For these reasons, there is hope that some of the radar bands can be efficiently utilized for spectrum
sharing by wireless communication systems.
Before presenting the real spectrum usage of a weather radar in the 5 GHz band, it is worth looking at
some of the models that are proposed in the literature for spectrum sharing with radar systems. In Figure
1, we also summarize three main spectrum sharing models.
•
Geographic exclusion zone (GEZ) model: In this spatial spectrum sharing model, a spectrum
5
management entity called spectrum access system (SAS) manages all users (except the radar
incumbents) on the fly, in real time. Every user registers with the SAS before initiating the
transmission. Each user reports its own location, requests permission to transmit, and waits to be
assigned a specific frequency. The SAS’s job is to keep every user off the incumbent spectrum in the
exclusion zones. The radii of these exclusions zones vary, depending on the specific site, between 72
and 121 kilometers. These distances are based on the specific radar system and on the specific wireless
system that shares the spectrum. This model may guarantee 100% protection to the radars; however,
different works and reports have shown that fixed geographic exclusion zones are unnecessary and
counter-productive to the goals of spectrum sharing in the radar bands [7], [8]. For instance, it has
been estimated that the using the GEZ model would prevent 60% of the US population from spectrum
sharing access in the 3550 MHz band.
•
Dynamic frequency selection (DFS) model: Dynamic frequency selection (DFS) enables devices to
currently share spectrum with radars in the 5 GHz band. A DFS-enabled device listens and performs
processing to detect a radar, and upon detection it moves to another channel and the device is not
allowed to scan the channel again for 30 minutes. If a radar is not detected, the device can use
the channel but it is still required to periodically scan the channel. In this method, it is challenging
to detect with close to 100% probability in a way that also minimizes the DFS false alarm rate.
DFS is also not an efficient mechanism in the search for spectrum opportunities, as it requires long
channel availability check time periods, and long non-occupancy periods. Moreover, it also ignores
the possible exploitation of quasi-periodic scan patterns of weather radars in the 5GHz band.
•
Temporal sharing (TS) model: Unlike DFS, the TS-based opportunistic access model allows users to
exploit temporal access opportunities. In [6], the authors propose a beacon signal from the radar that
helps WLANs access the spectrum temporally while the main beam of radar antenna does not face
the WLANs. The work in [9] presents a method using which transmissions are interrupted whenever
the main beam is directed to the user. For the cases when the main beam is not directed at it, the
user only interrupts its transmission when its transmission power is above a defined threshold value.
In [10], the area around a weather radar is divided into three zones based on the comparison of the
radar’s received power and a threshold value. In Zone 1, opportunistic secondary operation is strictly
forbidden as it can cause interference on the incumbent radar. In Zone 2, temporal sharing takes place,
in which the users can transmit every time the radar’s main beam is pointing in another direction.
Finally, in Zone 3, the users are free to use the spectrum, as they are outside the interference area
of the radar.
All the above mentioned TS-based methods assume that a radar in the 2.7-2.9 GHz and/or 5 GHz
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Fig. 2: Details of the two measurements and the radar location. a) The first measurement point and the
radar location. b) The second measurement point and the radar location.
band rotates in a regular manner. However, in this work, using the real measurement results we show
that the rotation pattern of a weather radar in the 5 GHz band is quasi-periodic.
In [11], the authors consider the feasibility of secondary LTE use in the 2700-2900 MHz band. They
consider spatial separation of LTE systems and radar, and present some system level simulation results,
suggesting some required separation distances for coexistence. They do not consider temporal sharing.
Many recent works have considered the joint design of radar and communication systems in order to
co-exist. Several papers, for example, have examined using MIMO radar to project the radar signals into
the null space of the channel between radar and communication basestation [8], [12]. This requires perfect
channel knowledge at a cognitive radar system, and in [12] through simulations the authors demonstrate
that their proposed technique enables coexistence between radar and communication systems, while
maintaining good radar performance in terms of target identification capabilities. However, modifications
in the design of radar systems across different bands may be not be likely soon as in general, radar
system lifecycles are multiple decades. Moreover, existing systems are relatively low-cost to operate and
their replacement costs would be substantial. In Table I, we summarize key challenges in the design of
spectrum sharing techniques for in the radar bands.
7
−40
−50
dBm
−60
−70
−80
−90
−100
5605
5610
5615
5620
MHz
Fig. 3: Logarithmic two-dimensional spectogram of the recorded power values during the measurement
study at the first measurement point.
III. D OPPLER WEATHER
RADAR IN THE
5 GH Z BAND : M EASUREMENT S ETUP AND R ESULTS
A. Background
The weather radars that operate in the 5 GHz band are Doppler radars. A Doppler radar emits pulses of
microwave energy from a transmitter into the atmosphere. When these beams collide with objects in the
atmosphere, such as raindrops, cloud droplets, and birds, some of the energy bounces back towards the
radar, which is collected at the receiver co-located with the transmitter. Doppler radars rotate horizontally,
and from time to time they may also tilt vertically. In fact, they may scan horizontally 360 degrees at
anywhere from four to fourteen different vertical angles. A Doppler radar transmits a narrow beam, and
three basic properties characterize the transmitted beam: 1) pulse repetition frequency (PRF), the number
of pulses of radiation transmitted per second; 2) transmission time, the duration of each pulse; and 3)
beam width, the angular width of the emitted beam. As the beam travels at the speed of light, one can
calculate pulse length from the transmission time. The beam width and the pulse length enable one to
calculate the pulse volume. A radar has certain radial and angular resolution of data, where the radial
resolution is defined by the pulse length and the angular resolution is defined by the beam-width.
B. Measurement Strategy, Setup and Results
In this subsection, we describe the measurement strategy, setup and results of our spectrum usage study
of a Vaisala Weather Radar WRM200 weather radar operating at 5610.7 MHz in the 5 GHz band. The
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2nd measurement point
1st measurement point
45
40
Band occupancy [%]
35
30
25
20
15
10
5
0
300
350
400
Seconds
450
500
Fig. 4: Overlaid band occupancy measurements from the two different measurement locations (red = first
location, blue = second location).
WRM200 is a dual polarization C-band magnetron Doppler weather radar. Measurements were performed
with an Agilent RF Sensor connected to a wideband, omnidirectional antenna (ARA CMA-118/A). The
RF sensor continuously measured (without any time-domain gaps) the 5605-5620 MHz band by using
peak-detection for each frequency bin. Time-resolution was 1.83 ms and resolution bandwidth was 60.69
kHz. Measurements were performed at two different locations near Vaisala Weather Radar WRM200.
Measurement duration was more than 45 minutes at each location. In Figure 2, we present the details of
the two measurements and radar locations.
1) Spectogram, potential spectrum holes, and the sensing challenge: In Figure 3, we present a
logarithmic two-dimensional spectogram of the recorded power values of the radar signal at the first
location, which is 3.6 kilometers south of the weather radar. The red line shows the maximum power
during the whole measurement for each frequency bin (out of more than 1.5 million measurements for
each frequency bin). The green dashed line is the threshold used for detecting the presence of signals.
For band occupancy results, threshold levels -88 dBm are applied to the entire data set. The threshold
was chosen so as to lead to essentially zero false alarm probability. During noise-only conditions, no false
alarms were present in more than 500 million samples spectrogram.
In Figure 4 we also illustrate the overlaid signal band occupancies from the two different measurement
locations (red = first location, blue = second location, which is farther away than the first one). The y-axis
9
represents band occupancy, which is defined as the fraction of the time-frequency domains bins that are
detected to have signal present. Each band occupancy is calculated for 574 frequency bins at 8 time
elements, so the band occupancy is simply the fraction of the 8 × 574 = 4592 time-frequency elements
that have signals.
It can be seen in Figure 4 that there are pauses in the received signal from the radar, due to its
antenna rotation, which offers the potential of temporally sharing the spectrum with the radar. When the
rotating radar’s main beam points to the measurement locations a signal peak is received. Since the two
measurement locations are at different angles with respect to the radar’s location (see Figure 2) there is
some time lag between the two signal peaks (shown in red and blue colors, respectively). It can be also
seen that the band occupancy is not constant over a period of time. The reason for this band occupancy
variation is that the radar scans horizontally 360 degrees at different vertical angles. The highest band
occupancies in the figure are produced by the radar when it directs its beam downward to the measurement
location. This significant variation in received signal strength of the radar poses a challenge for sensingbased techniques. For instance, between 380 and 500 seconds in the Figure 4, the band occupancy for the
first measurement location can be as low as 5 %, whereas for the second location the band occupancy
can be essentially zero.
2) Quasi-periodic and vertical angle scans: In Figure 5 we present three examples of radar main
beam pulse interval measurement. It can be seen from the figure that some of the radar-pulse intervals
are longer than the others. This means that the radar scan speed changes over time and its rotation is not
regular as supposed in [6]. This finding is confirmed by the radar’s operator which tells that the radar has
two scanning modes: 1) The normal-mode with PRF 570 Hz, pulse duration 2 µs, rotation speed 16.9
degrees/s, lowest elevation angle 0.3 ast. 2) The Dual-model: At highest angles and dual-PRF 900/1200
Hz, pulse duration 0.8 µs, rotation speed 26.7 degrees/s, lowest elevation angle 0.4 ast. Both normal and
dual-polarization measurements are carried out by the radar, leading to varying rotation period, making
secondary spectrum use more challenging then for fixed rotation speed radars. Moreover, our measurement
data shows that the radar may change its scan speed from fast scan to slow scan or from slow scan to
fast scan at arbitrary angle. Change of rotation speed at arbitrary angle is common for a weather radar as
it may need to react to changes in weather, such as changes in wind direction and cloud movement.
In Figure 5, we also compare the ideal pulse interval, where the radar always changes its scan speed
at a fixed angle, with the real measurement data. Under the ideal pulse interval, the next radar pulse will
arrive at one of two time intervals, which are marked in the figure with ◦, for slow scan pulse arrival,
and ∗, for fast scan pulse arrival. However, it can be seen from the measurement data that in example
a) the radar pulse does not always arrive at one of the two time intervals. This is due to the radar does
Band occupancy [%]
10
Transition period
from slow to fast
20
10
0
Band occupancy [%]
1340
1360
1380
a)
1400 1420
Seconds
10
1440
1460
1480
No transition period
from slow to fast
5
0
2580
2560
2600
b)
2620
Seconds
2640
2660
2680
25 21.08
Band occupancy [%]
20.95
Time [s] till next
peak (next blue rectangle)
20
15
20.83
10
21.11
5
0
Transition
from slow to fast
13.15
2240
2260
2280
c)
20.79
2300 2320
Seconds
17.36
2340
13.12
2360
Fig. 5: a) and b) Examples of transition and no transition periods from slow rotation speed to fast rotation
speed. c) Examples of pulse length intervals. The blue rectangles denote the peaks and above each blue
rectangle is a number which tells the time in seconds till the next peak.
not changing its speed at the same angle, resulting in a pulse time interval which is a mixture of two
rotation speeds, somewhere between fast and slow scan speed intervals. Part c) of Figure 5 shows pulse
interval length examples for transition from slow rotation speed to high rotation speed. The blue rectangles
denote the detected peaks. It should be noted that around the peaks there are also signals present (they
are not false alarms), due to radar antenna sidelobes and/or multipath propagation (such as from trees)
from different azimuth angles to the observer at a given angle. It can be seen from the figure that there
are pauses between the scan pulses that vary from 13.2 seconds to 21.08 seconds.
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IV. A F RAMEWORK FOR T EMPORAL S HARING WITH W EATHER R ADARS
A. General Concept
Weather radar systems have highly directional rotating antennas and are deployed in a way that over
a large area (say they cover a range of 200 kms) there is in general one operating radar per 30 MHz
channel. Moreover, our measurement study shows that the weather radar’s main beam pulse interval varies
between 13 seconds to 21 seconds (see different examples of our measurement results in Figure 5). From
a temporal sharing perspective, there is a possibility that a considerable amount of spectrum opportunities
can be exploited by allowing users inside exclusion zones to transmit when the radar antenna’s main beam
is pointing in another direction. However, there are technical challenges in implementing temporal sharing
with weather radars. Based on the measurement observations we identify the following four critical issues
in implementing opportunistic temporal sharing with weather radars.
•
The quasi-periodic scanning patterns observed in our measurements make synchronization of the
users with these antenna scan patterns a technically challenging task.
•
While the co-located transmitter and receiver of a radar facilitates incumbents’ protection from
interference through monitoring based DFS techniques, due to vertical scans there can be large
variations in the received signal strength at a given location. In certain time intervals, the user may
not sense the presence of the radar due to almost invisible signal (see Figure 4); in such scenarios if
the secondary user accesses the channel while the main beam of the radar is directed to the user’s
location then it may interfere with the radar.
•
The radar does more listening than talking. It emits a pulse for 0.000002 seconds then it listens
for approximately 0.002 seconds. Any secondary user transmission scheme needs to take this into
account.
•
Our measurements also show that a weather radar not only scans its environment by transmitting a
focused high-power beam of radiation and then receiving it back, but it also performs periodically
(every hour) some special measurements during which there are long pauses (lasting few minutes) in
the received signal at a particular user’s location. It remains an open question whether a secondary
user should be allowed to communicate during these intervals.
Currently proposed temporal spectrum sharing solutions do not take into account the above mentioned
critical issues related to spectrum sharing with weather radars. To address these issues, we next provide
a framework for temporal sharing with weather radars.
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Fig. 6: a) A schematic diagram explaining the proposed framework. b) Illustrative examples of radar scan
speed change. c) and d) Examples of the virtual frame based temporal sharing access.
B. Proposed Framework
In the proposed framework, the radar’s surrounding area is divided into three geographic zones and
several slices (see Figure 6 for an illustrative example). Each zone defines a different operating mode for
a network, and each slice S is defined by its angular width θS , which in turn has the same value as the
radar beamwidth. Let Ns represent the total number of slices which is given by ⌈Ns = 360/θS ⌉. The time
the radar’s main beam spends on each slice is Ts = θS /R, where R is the scan speed in degrees/sec. The
schematic diagram of the proposed framework is illustrated in part a) of Figure 6 and is explained as
follows.
•
Before initiating the secondary network a spectrum sharing database is informed about the network’s
estimated position (estimated through) a GPS or another localization mechanism, and is queried about
the zone information. This information exchange can be achieved using the concept of anchoring
the control channel which is recently proposed in [13]. In this approach, through aggregation, the
connectivity on the opportunistic access spectrum always comes with the connectivity on the more
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reliable spectrum. The control signaling always happens on the reliable channel such as a licensed
or an unlicensed channel with no incumbent.
•
Any network located in Zone 1 avoids the band 15 MHz below, and 15 MHz above the centre
frequency (in total 30 MHz) of the radar’s channel. Zone 1 is the exclusion zone as it can always
cause interference on the incumbent.
•
A network located in Zone 3 is free to use the spectrum, as it is outside the incumbent’s keep-out
region.
•
A network located in Zone 2 is allowed temporal sharing with the radar. In this zone, a virtual frame
structure based access (as illustrated in parts c) and d) of Figure 6) is employed to temporally share the
spectrum with the weather radar. A network is not allowed to transmit during the time when the radar’s
main beam is pointing to the slice in which it is located, and is also not allowed during the guard
interval before and after that time period. This is done to ensure interference protection to the radar,
as it can arbitrarily change its scan speed from fast to slow and vice versa. Due to the arbitrary change
in scan speeds there is some uncertainty in when the radar will direct its main beam to the secondary
network’s location. To address this issue the database signals the network whenever the scan speed
is changed and the network calculates the next pulse arrival as follows: When there is no change in
the scan speed and the radar is in fast scan mode then the next pulse arrives approximately after 16.9
seconds. This is calculated based on our measurement observations for the considered radar, and the
value may change for other radars. With no change in the scan speed and the radar is in the slow scan
mode then the next pulse arrives approximately after 26.3 seconds. When there is a change from fast to
slow or slow to fast scan speed the next pulse arrives after (|Si − Sc | × Rp )+(360 − |Si − Sc | × RN )
seconds, when Sc > Si , or after (|Si − Sc | × RN ) + (360 − |Si − Sc | × Rp ) seconds, when Sc < Si ,
where Si is the slice index in which the ith network is located, Sc is the slice index in which the
speed change occurs, Rp is the previous scan rate, and RN is the scan rate now used by the radar.
The use of a guard interval (say an interval of 0.5 seconds before and 0.5 seconds after the calculated
main beam arrival time) ensures that the user does not interfere with the main beam pulse or also
with it side lobes. Figure 6 provides illustrative examples of this mode of operation.
•
As the density of users sharing the radar channel increases, the aggregate interference on the
incumbent may also increase, which can lead to an increase of the radius of Zones 1 and 2. To
keep the radius of the two zones fixed, a distance-varying fixed number of users per unit pulse
volume (explained in Section III-A) should be allowed to share the channel. This can be easily
implemented, as each user is required to check with the database before initiating the network. When
the number of users increases above the specified threshold then new users are not allowed to access.
14
V. C ONCLUSIONS AND F UTURE D IRECTIONS
In recent years proposals for coexistence of wireless communication users with radar systems have
been made. Careful measurements of radar spectrum usage are required to test these proposals. In this
paper, we present results relating to spectrum occupancy measurement of a weather radar in Finland that
operates at 5 GHz. Our results show that long pauses between radar pulses, due to its low duty cycle
signal emissions and horizontal scanning patterns, allow the possibility of opportunistic spectrum access.
However, arbitrary scan speed changes, vertical scan angles, and special measurements, make the scanning
patterns quasi-periodic. This makes opportunistic spectrum access technically challenging as a secondary
user cannot reliably identify spectrum holes (pauses between radar pulses). Moreover, we also observe
that due to vertical scanning angles of the radar, at certain vertical angles, a user cannot sense the presence
of the radar’s main beam. To address these challenges, we provide a database-assisted temporal sharing
framework.
There can be several directions in which this research can be extended. First, it will be important
to study the effects, if any, of temporally sharing users on weather radars as the distance between the
users and the radar varies. Secondly, as aggregate interference increases with the increasing number of
transmissions, it is equally important to investigate how many secondary users can be allowed to operate
in a weather radar channel in a given location. Finally, as the 5 GHz band is part of the radio spectrum
used by unlicensed wireless devices it will be also interesting to develop a unified channel access strategy
that enables these devices to utilize different channels where a radar may or may not be present.
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