CAN WE FIND (AND USE) “SPECTRUM HOLES”? SPECTRUM SENSING AND SPATIAL REUSE OPPORTUNIES IN “COGNITIVE” RADIO SYSTEMS Invited Paper Jens Zander Wireless@KTH, Royal Institute of Technology Electrum 418, 164 40 KISTA, Sweden
[email protected] Abstract—A main concern in spectrum overlays (“Cognitive Radio”) has been the reliability of sensing techniques to predict the performance in the primary communication link if the secondary user decides to use the spectrum. The fundamental difficulty is that sensors detect the transmissions (i.e. the transmitters), whereas the communication performance is determined by the interference environment around the (possibly silent) receivers. In previous work, specific scenarios with rather simple propagation models, mostly neglecting the correlation properties between signal paths, have been used. In this paper, more realistic propagation models are used to compare the performance of various sensing and resource management strategies. Results show that simple transmitter based sensing works well only in very flat terrains and at low frequencies. In these scenarios unfortunately, the opportunities for spectrum reuse are limited. In more rough terrains, where the potential for secondary use of the spectrum is large, simple sensing schemes on the other hand perform poorly. Even advanced sensing schemes and/or responsive primary system may not be sufficient to achieve acceptable performance Keywords-dynamic spectrum access, cognitive radio, spectrum sensing
I.
INTRODUCTION
Spectrum usage is mostly not very efficient. Recent measurement campaigns suggest that only a fraction of the spectrum allocated to different service is used at any instant[1][2]. Identifying “pieces” of instantaneously un-used spectrum, so-called “Spectrum Holes” or “White Space” that could be used temporarily by secondary users is usually referred to as overlay spectrum sharing [3]. This is one of the features that appear under the rather broad concept of “Cognitive Radio”[4][5], an area that has been under extensive investigation during the last few years. Overlay sharing is likely to be successful in areas where the spectrum utilization is poor. In spectrum segments where we already have quite efficient use, e.g. inside well planned, high-capacity cellular systems, overlay techniques are not likely to bring significant advantages [9]. Opportunities for a secondary usage of the spectrum may occur in frequency, time and in space. Most previous work has been focused on the frequency domain. A significant body of literature focuses on the frequency domain, e.g. sensing techniques that aim at reliably detecting the presence of a primary user of the spectrum in a given channel, e.g. [6]. The key problem here has been to keep the miss probability, i.e. the
probability that active primary users are not detected, low to avoid unwanted interference by the secondary transmitters. This probability can be kept low by using very sensitive detectors thus avoiding interference to the primary users. However, this strategy will cause the false alarm probability to become high, i.e. that noise or very distant primary transmitters are interpreted as a valid signal. This results in a missed opportunity to use the spectrum segment in question and causes, in turn, poor spectrum utilization. One way to lower the false alarm probability is to use multiple collaborating sensors provided either by a regional spectrum server or by cooperation between many radios in a cognitive network[12][16]. In [7] the focus is on the temporal aspects of secondary usage and the communication channel is modeled as an “on-off” model, allowing secondary communication whenever the primary user in it off-state, irrespectively of the relative location of the secondary. Although the detection the presence of primary users can be quite reliable, predicting the overall performance of such systems is not trivial, since the interference caused by various transmitters is heavily spatially dependent. The fundamental difficulty is that sensors detect the transmissions (i.e. the transmitters), whereas the communication performance is determined by the interference environment around the (possibly silent) receivers. If there is a “spectrum hole” to be found, it should be around the receiver! Some studies taking spatial effects into account have been made. In [10] the interference between secondary and primary users is model by means of a simple fading model with know fading states and with a responsive primary link (i.e. the primary link can adapt to the increase interference, e.g. by - lowering its data rate). The communication performance is expressed in terms of primary and secondary user capacity. In [11], a more realistic model of the interference using distance dependence and Rayleigh-fading is used and an algorithm to adapt the secondary transmit power to avoid interference at the primary is proposed. In this paper, we will focus on the spatial domain and the capability of various “Cognitive Radio” schemes to detect and utilize spatial spectrum opportunities, i.e. opportunities for a secondary user to spatially reuse a piece of spectrum even though that part of the spectrum is already used by a (distant) primary user. To access the performance of such schemes, realistic propagation models are of vital importance.
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secondary user transmission attempt to be successful if both the primary and the secondary links achieve their required SINR. The probability that this will occur (given than an attempt is made), is denoted Psucc. Another performance measure of interest is the probability of a missed opportunity (MOP). The is the probability that the secondary transmitter senses the activity in the primary link and refrains from starting its transmission, even though both the primary and secondary links would have been above their respective SINR thresholds, if the secondary transmitter would have opted to transmit. This corresponds to a “false alarm”. In most cases a distant primary transmitter is detected, but a short range local transmission would have been possible. The locations of the primary transmitter and receiver in our study are chosen as independent, uniformly distributed in a terrain square (Fig. 1), conditioned on the fact that a minimum Signal-to-Noise (SNR) of γ0P is achieved within the maximum
PRx
PTx
SRx STx Figure 1. Above, a synthetic terrain sample with Primary and Secondary transmitter/receiver pairs. The terrain sample size is 10x10 km, 100m resolution, height scale exaggerated by a factor of 100. Below, a schematic diagram of the connections – dashed lines unwanted signal paths.
In previous work, rather simple fading channel models have been used, mostly neglecting the correlation properties between signal paths. In this paper we will instead use models that involve (random) synthetic terrains and state-of-the-art semi-empirical propagation models which have proven quite accurate in describing “real life” propagation properties of various terrain types[13][14]. Using this methodology we will assess how well various sensing schemes will perform both with respect to the probability of the sensor(s) failing to predict harmful secondary user interference as well as the number of missed opportunities when the primary user is detected (and the secondary transmission attempt is aborted) although secondary re-use would still be possible. II.
MODELS & PERFORMANCE MEASURES
For the sake of simplicity, we will assume that all transmission activities take place on a single “channel”. Before starting its own transmissions the secondary transmitter will perform a sensing operation to detect the presence of the primary transmitter. If there are no primary transmissions ongoing (anywhere in the world), our (ideal) sensing scheme will trivially find the channel empty and secondary use will be successful. In our study however, we will look at the more interesting case where a primary link is active somewhere. We will be interested to measure the ability of the secondary user to detect an opportunity to use the spectrum for his purpose without interfering with the primary user. We consider a
transmit power PP of the primary transmitter. In the same terrain square, we now in the same fashion place a secondary transmitter and receiver - independently and uniformly - but again conditioned on the fact that a minimum SNR γ0S would have been achieved in the absence of the primary transmitter, given that the secondary transmitter has a maximum transmit power
PS . The path gains in Fig. 1 are derived using a
“synthetic” terrain model [13] that is randomly generated by filtering a 2-D white Gaussian process. The terrain heights are characterized by their height standard deviation σ and correlation distance ρ. In the numerical experiments, the terrain square 10 x 10 km with a grid resolution of 100m. The path gains (or path-losses) in Fig. 1 are computed using the Blomquist-Ladell Multiple-knife-edge diffraction model (BLM)[14] (an improved version of the Epstein-Peterson method), which is a popular propagation model in cellular planning tools. Since we in this work are not interested in the implementation details of this sensing operation, we will assume that the secondary transmitter (and subsequently any additional sensors) is capable to perform ideal sensing with threshold κ, i.e. the sensor is able to detect any signal with received power larger than κ without any misses or false alarms. If the secondary transmitter senses the channel to be clear, i.e. not power above the sensing threshold is received, it will start its transmission. The path gain on the path STx – SRx is assumed to be known to the secondary transmitter – all other path gains are unknown. III.
SENSING & SPECTRUM ACCESS STRATEGIES
Based on its available capabilities, the secondary transmitters will perform one or several sensing operation and based on their outcome, access the channel by starting its transmission. We will consider the 4 following access schemes:
A. Transmitters sensing – silent receiver In this basic case the secondary transmitter is not aware of the whereabouts of the primary receiver (which may be silent). The secondary transmitter senses the channel and if its not able to detect the primary transmitter on the path PTx – STx it will start its transmission. We will consider a constant (maximum) transmitter power mode and an adaptive secondary transmission mode where we will adjust it’s transmit power such that the SNR at the secondary receiver is kγ0S in the absence of primary transmitter interference, where k is the interference margin. B. Transmitter & receiver sensing Here we assume that the secondary transmitter is (propagation conditions allowing) able to detect the primary receiver, e.g. by sensing return channel traffic or if the primary link is a two-way system. If the secondary transmitter is sensing activity from either (or both) of the primary radios (on the paths PTx – STx or PRx – STx), it will refrain from using the channel. As in A) both a constant power and an adaptive transmit power mode are investigated. C. Responsive primary system In cases A) and B) the primary system is not able to act on the increased interference introduced by the secondary transmitter. In this scenario, we assume that both the primary and secondary transmitters adjust there power according to a distributed power control scheme. The channel access is assumed to be successful if there exists a power setting (within the maximum power limits) such that both the primary and secondary link achieve their target SINRs[15]. D. Collaborative Sensing In this case the secondary transmitter gets additional sensing information from N other sensors/cognitive radios in his network. We will model these as (uniformly) randomly dispersed over the terrain using the same sensing threshold as the secondary transmitter. If none of these sensors is detecting any signal above the threshold the secondary user will access the channel (constant or adaptive power). IV.
NUMERICAL RESULTS
The numerical results are derived using simulations using three different terrains types with various parameters as described in Table 1. Most results are presented for the medium “hilly” terrain (“Dreamland”). TABLE I.
TERRAIN CHARACTERISTICS Heigth σ (m)
Corr. dist ρ (m)
Rockland
54
1000
Dreamland
27
1000
Flatland
1
1000
City
10
200
Terrain type
1 Clear TX Succ/Clear TX Succ/Clear TX&PC Missed opp Miss opp PC Primary Success PC
0.9
0.8
0.7
0.6
0.5 Ps*
0.4
0.3
0.2
0.1
0 -120
-115
-110
-105
-100 -95 -90 -85 Sense treshold (dBm)
-80
-75
-70
Figure 2. Strategy A) Success probability (solid lines with markers) and missed opportunities (dotted lines) as function of sensing threshold with and without secondary power control. (Dreamland, k=5dB, f=800MHz), The uppermost line represents the probability of primary link success. The clear channel probability is the solid line without markers.
Changing the terrain roughness (height parameter σ), has similar effect as changing the operating frequency. If nothing else is stated the (maximum) transmission power of all transmitters is 1W, the antenna elevations are all 5 meters, the required SINRs γ0S and γ0P are both 10dB and the noise level power is -120dBm. To allow for accurate comparisons between schemes, the results shown are derived for the same realization of the terrain and with the same random primary/secondary receiver/transmitter locations. The number of topology realizations in the numerical examples varies between 1000 and 10000. Fig. 2 shows Psucc as function of the sensing threshold κ for strategy A – with a silent primary receiver. As the sensing threshold approaches the noise floor, the probability of finding the channel “clear” (i.e. not sensing the primary transmitter) at the secondary transmitter site, approaches zero. Getting this probability close to zero requires as we can see a sense threshold below the noise level. This requires longer sensing intervals and/or detecting known features in the primary signal[15]. Further, Psucc will increase as we lower the sensing threshold. This stems from the fact that we are more likely to detect the primary link and thereby avoid the interference. The uppermost curve in Fig 2, the probability that the primary link remains above the SINR target, indicates that about half of the failures stem from primary link failures For high threshold levels, the secondary transmitter is virtually “deaf” to primary transmissions and will always transmit. The
1
1
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.3
Clear TX PSucc Missed opp
0.3
0.2
0.2
0.1
0.1
0 -120
-110
-100
-90
-80
-70
Figure 3. Terrain dependence. Clear channel probability (solid), Success probability.(dashed) and Missed opportunity prob. (dotted). “Dreamland” (o), “Rockland”(+) and “Flatland”(squares). f=800 MHz
1
0 -120
-110
-100 -90 Sense threshold (dBm)
-80
-70
Figure 5. Scheme C) – responsive primary with optimum power control (primary transmitter sensing) Clear channel prob(solid), Success prob.(dashed) and Missed opportunity prob. (dotted). “Dreamland”, 800 MHz.
probability approaches zero, the MOP tends to ps* since there are no secondary transmissions at all, and all reuse opportunities become missed opportunities. It can be noted that secondary power control (not using “more power than necessary”) improves the situation somewhat but not drastically.
0.9 0.8 0.7 0.6
0.5 0.4 0.3 Clear TX&RX Succ/Clear RX&TX & PC Prim success Succ/Clear TX&PC Clear TX
0.2 0.1 0 -120
-115
-110
-105
-100
-95
-90
-85
-80
-75
-70
Sense threshold (dBm)
Figure 4. Strategy B) – detecting the primary receivers. Clear channel and Success probability for strategy B (solid lines ‘+’) compared with strategy A) (dashed lines ‘o’). Secondary power control. (Dreamland, k=5dB, f=800MHz). Uppermost curse shows primary success probability.
limiting value of the success probability denoted ps*, corresponds to the actual fraction of reuse opportunities, i.e. the probability that a randomly chosen secondary link can coexist with the primary link in the given terrain square. As we lower the sense threshold, Psucc (i.e. the conditional success probability given that the channel is sensed empty) increases only marginally. In other words, sensing does not help us very much; the success probability is only marginally higher than the one we would get by completely disregarding the sensor information. As we lower the sense threshold, the secondary transmitter will become more “timid”, avoiding more and more transmissions. This causes an increased missed opportunity probability (MOP). When the “clear channel”-
Fig. 3 shows the dependence of the performance of the terrain type. Clear channel, Success and MOP are show for strategy A. As we may expect, efficient detection is easy in “Flatland” but becomes increasingly difficult as the terrain roughness increase. Success is on the other hand more likely since terrain obstacles also provide protection against unwanted interference. This also becomes manifest in the ps*, which is much higher in the hilly terrains since shadowing provides plenty of opportunity for coexistence. Again, lower sensing thresholds have only marginal impact on Psucc. The results are show for an operating frequency of 800 MHz. Due to the nature of diffraction, lowering the frequency has a similar effect as reducing the terrain height. Increasing the frequency on the other hand will make the terrain look more “rough”. Fig. 4 shows the effect of being able to detect also the secondary receiver. As we can see this provides a dramatic improvement both in the ability to detect the primary transmissions, but also in the success probability which approaches one for very low sensing thresholds. ps* is a property of the topology and propagation models and will thus be the same for schemes A and B (a “deaf” secondary transmitter will always transmit). As can be seen from the uppermost curve, the protection of the primary link is even better. Fig. 5 shows the impact of having a responsive primary link that will adjust its power adaptively together with the
potential secondary interference, which excludes most “legacy” systems. Further, in this work, random secondary link configurations are investigated. Future work includes the study of short range (local) secondary links where reuse opportunities are more likely. Another issue is the size of the studied terrain. A larger terrain square would improve the opportunities of co-existence and increase ps*. This would on the other hand decrease the spectral efficiency measured in successful links per area unit (which should be a more relevant performance measure). Future work should investigate this spatial efficiency.
0.5 0.45 0.4 0 0.35
1
0.3 3 0.25 0.2
0
0.15 0.1
1
0.05 0 -120
VI.
3 1,3 0 -110
-100
-90
-80
-70
ACKNOWLEDGMENTS
This work has been conducted within the project MODyS, in cooperation with Ericsson AB. The financial support from VINNOVA is gratefully acknowledged. REFERENCES
Fig 6. Scheme D) – collaborative sensing for zero (secondary transmitter sensing only), 1 and 3 additional sensor. Secondary power control. Clear channel probability (solid), Success probability (dashed) and Missed opportunity probability (dotted). “Dreamland”, 800 MHz.
secondary system. Here only transmitter sensing is used. As we can see, we can now achieve similar results as with scheme B). Notably ps* increases dramatically - almost by a factor of two - as non many more link configurations are able to coexist compared to the non-responsive schemes. The performance of the collaborative sensing scheme in shown in Fig. 6. The “channel clear”-probability rapidly drops to zero already when one additional sensor is added. Very good detection and success probabilities are achieved in this case. Increasing the number of additional sensor adds very little to the performance.
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V.
DISCUSSION
Our results show that the effectiveness of sensing schemes and the probability of success is highly dependent on the terrain and link topologies. When it comes to efficiency, the key problem turns out not to be the failure to detect primary transmitters, but rather that the detection of distant primary transmitters prevents (local) secondary transmissions. In “flat” terrain, low frequencies and with highly elevated primary transmitters the schemes work reasonably. However, the resource utilization becomes (unacceptably) poor for simple distributed sensing schemes with unresponsive primary links for the more “rough” terrain types. The success probability is here only marginally higher than with “deaf” secondary users, not sensing the spectrum at all. To approach an acceptable situation where primary link performance can be guaranteed, complex sensing schemes using either multiple sensors or knowledge about/analyzing the transmission protocols of the primary systems in order to detect the primary receivers have to be employed. The situation is somewhat improved by using responsive primary links, using power and rate control to better tolerate secondary user interference. The latter on the other hand would require that primary users are aware of
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