A Novel Scheme with Adaptive Sampling for Better Spectrum Utilization in Cognitive Radios

doi:10.4236/cn.2009.11007

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Communications and Network, 2009, 46-50

doi:10.4236/cn.2009.11007 Published Online August 2009 (http://www.scirp.org/journal/cn)

A Novel Scheme with Adaptive Sampling for Better

Spectrum Utilization in Cognitive Radios

Qun PAN, Xin ZHANG, Ruiming ZHENG, Yongyu CHANG, Dacheng YANG

Beijing University of Posts and Telecommunications, Beijing, China

Email: [email protected]

Abstract: In cognitive radio (CR) networks, cognitive users need continuously monitor spectrum to decrease

or avoid interference to primary users, yet attain a reasonable throughput. In this paper, we exploit a scheme

to dynamically change the detection time duration to gain maximum throughput. Meanwhile the average de-

tection time is kept as small as possible. The advantages of our approaches are approved by the deductions.

Also the simulation results enable us to recognize the improved performance of our scheme over those ones

with fixed detection time assignment.

Keywords: cognitive radio, cooperative sensing, average detection time, channel utilization ratio

1. Introduction

With the rapid development of wireless communication

technology, the demand of spectrum resource is growing.

The spectrum resource becomes rare due to the popular-

ity of various new wireless applications. However, the

recent survey shows a low spectral efficiency in the li-

censed band. The spectral holes in licensed band can be

sensed and used to transmit information by employing

cognitive radios technology [1]. The extra system

throughput can be provided by cognitive radios without

additional spectrum resource allocation. So the Federal

Communications Commission (FCC) has recommended

cognitive radio (CR) as the candidate for enhancing

overall spectral efficiency. Cognitive radio [1] enables

CR users (unlicensed users) to obtain the frequency

bands with minimal interference to active primary users

(licensed users) when they observe the bands allocated to

the primary user are vacant and meanwhile detect the

continuous spectrum sensing in CR networks. Therefore,

as the heart of the cognitive radio techniques, the spec-

trum sensing is so critical that it determines the through-

put and the agility of the CR networks.

One of the challenges of CR system’s application is

how to detect the primary user’s signal quickly and cor-

rectly in order to avoid interference to the licensed net-

work. The other is how to fully occupy the spectrum re-

sources acquired by CR network. In this paper, a novel

scheme is proposed to use the spectrum holes more effi-

ciently. Meanwhile the interference to licensed network

is controlled within an acceptable range. Our proposed

scheme could increase spectrum efficiency in full extent

in an applicable CR network. We consider the detection

performance in the more practical scenario based on

IEEE 802.22 WRAN system which uses cognitive radio

technology as its key feature. The fast sensing and fine

sensing process which utilize energy detection technol-

ogy and feature detection technology respectively are

both considered in our study. The cooperative sensing

technology which can increase the sensing performance

significantly is also involved in. The approaches of co-

operative sensing technology [2-5] all use diversity tech-

nologies to improve effective SNR for essential.

The rest of this paper is written as follows. In Section

2, we model the conventional detection scheme in ma-

thematic way. In Section 3, we analyze the influence to

channel utilization ratio made by time scheduling, and

we propose a novel scheme of maximizing the channel

utilization ratio. At last, we will conclude our study in

Section 4.

2. System Model

A practical sensing scheme is shown in Figure 1 [6].

There are two types of detection in the figure: the fast

sensing (energy detection) and the fine sensing (feature

detection). During these two types of detection time, all

the CR users should cease their transmission in order to

achieve high definition detection. Therefore, these detec-

tion periods are also called quiet periods.

The fast sensing processes are triggered periodically,

and all the detection information from all CR users is

summarized to give a final judgment. If the detection

indicates that no primary user exists, the CR users will

wait for next fast sensing process. On the other hand, the

fine sensing process will be triggered. Usually, the time

duration of fine sensing is much longer than that of fast

sensing. Also the veracity of fine sensing is much better.

Without loss of generality we assume the veracity of fine

sensing is 100% all through the rest of the paper.

A NOVEL SCHEME WITH ADAPTIVE SAMPLING FOR BETTER SPECTRUM UTILIZATION IN COGNITIVE RADIOS 47

2.1 Modeling Individual Detection

The binary hypothesis model is adopted in the study of

spectrum sensing.

(1)

where is the receive signal by CR user at time t.

is the Additive White Gaussian Noise (AWGN),

and we assume nt follows a standard normal distribu-

tion, which means the expectation is 0 and the variance is

1. ()

()yt

()nt

()

t is the pary user’s transmitting signal. H0 de-

notes the null hypothesis, which means there is no pri-

mary user signal in a certain spectrum band. H1 is the

alternative hypothesis, which indicates that there exists

primary user signal in that band. h is the channel coeffi-

cient.

rim

First, we consider local spectrum sensing (energy de-

tection) at an individual CR user. We assume each en-

ergy detection interval contains M samples. j denotes the

sampling index. Then the statistic characteristic of the

i-th CR user is given by:

(2)

We can see is the sum of

independent Gau-

ssian random variables’ square, whose deviation is unit.

So follows a central chi-square distribution with

degree freedom when H0 becomes true, or else fol-

lows a non-central chi-square distribution.

(3)

We defined the as the instantaneous SNR of the

i-th CR user.

jhs



  (4)

The non-centrality parameter .

Mh=G

If M is large enough, the will approximately fol-

low Gaussian distribution according to the Central Limit

Theorem as follows:

(5)

2.2 Modeling Cooperative Detection

Individual detection is not sufficient in a practical sce-

nario due to the lower receive SNR of CR users. Hence,

cooperative technology is involved in spectrum sensing

as in [2-5]. We adopt a linear combine scheme which

sums the different CR users’ samples with weights in

Channel Detection Time

Fast sensingFine sensing

CR User

CRUser

Fast SensingData

Transmission Fine Sensing

…… ……

CR User

…… ……

Figure 1. Detection process in cognitive radio network

48 A NOVEL SCHEME WITH ADAPTIVE SAMPLING FOR BETTER SPECTRUM UTILIZATION IN COGNITIVE RADIOS

our cooperative sensing process. The weight coefficient

corresponding to the i-th CR user is , then the

weighted summation is given by:

(6)

(7)

Let be the decision threshold of energy detection.

Therefore the probability of false alarm

P, and that of

detection

P are:





















(8)



-1

PM w

























(9 )

So the decision threshold and the optimal weight coef-

ficient can be given by (10) and (11) respectively [7]:



-1 2











(10)









 (11)

3. System Performance Analysis and

Proposed Scheme

3.1 Detection Performance

The performance of the cooperative sensing is evaluated

by receiver operating characteristics (ROC) which is

composed of probability of false alarm and that of detec-

tion in plenty of bibliography [7][8]. But these two pa-

rameters can only indicate the system performance under

some special conditions. Our analysis is shown as fol-

lows.

Excellent CR system should exit when the primary us-

er is working on the target channel band, besides suffi-

ciently use the spectrum when primary user is idle.

Therefore the two objectives in CR system design are

interference avoidance to primary user and full utilization

of spectrum holes respectively. In order to decrease or

avoid interference to the primary user, the detection sen-

sitivity must be high enough for CR system, i.e. the exis-

tence of primary user’s signal must be discovered as

quickly as possible. If the detection process finds holes in

spectrum, the time duration for detection must be as short

as possible to leave more resource for data transmission.

We define channel utilization ratio (CUR) as the pro-

portion of time used for data transmission accounting for

the whole time when the primary user is idle [9].

x and

x indicate the probabilities of energy detec-

tion, transmission and feature detection. The Markov

state transition diagram is shown in Figure 2. So the cor-

responding Equation (12) is demonstrated as below.





1(2)

TFFE EF

TF FTF

(2)

TFF FF



 

 

 











 



(12)

So the CUR can be expressed by (13)

ETT FF

TTT

hxxx

=++ (13)

where

T, and

T are the time duration of the

three states. Let

TTT=+. We define the sampling

proportion (SP) as E

TTa=. So (13) can be trans-

formed to (14).

()

TT PTha=-+ (14)

From (14) we can see it is the CUR that not only de-

pends on

P, but also T and α.

()

(15)

The average detection time (ADT) [10][11] indicates

the average time interval from the primary user’s pres-

ence until it is found by CR users. We assume the prob-

ability of detection in each sensing period is equal to

when the primary user is present. The final H1 decision

must be after feature detection, so the ADT required by

CR user to detect the primary user can be given by (16):



DD F

TTkP PTT







 (16)

Figure 2. State transition diagram of CR system when no

primary user is active

A NOVEL SCHEME WITH ADAPTIVE SAMPLING FOR BETTER SPECTRUM UTILIZATION IN COGNITIVE RADIOS 49

3.2 Maximizing the Channel Utilization Ratio

The interference provided by CR network should be

firstly small enough, so that primary user can work nor-

mally. In order to limit the interference to primary user,

the ADT should have a maximum target. So we will dis-

cuss the scheme which can maximize the CUR, and at

the same time the target of ADT can be realized.

The sampling number E

WT WTa== according

to the Nyquist sampling Theorem, where W is the sensing

bandwidth. (17) is acquired in terms of (9) and (16):



2-1

Q12Q





Pw WTw

ii ii

Fi i



 













(17)

The CUR can be given by (18) which is combine

d by

4) and (17).







2-1

Q12Q

ii iiF

wWT















 









(18)

(18) shows that there are too many parameters w

hich

uld influence the CUR. The bandwidth W is fixed

and it depends on the spectrum specificationf primary

network. The SNR i

G of each CR user depends on the

radio scenario and the receive equipment of CR user. The

time duration of feature detection

T depends on the

character of primary user’s signal. Conventionally the

frequency of the fast detection 1T is predefined.

Therefore, the only parameter which can be adjusted is

the , i.e. the time duration of each fast sensing can be

changed to optimize the CUR.

Intuitively if the sensing duration is too short, and si-

multaneously the ADT can be guaranteed, the probability

of false alarm will be raised. As a result, the unnecessary

feature detection will be frequently triggered. The unnec-

essary feature detection will waste a large amount of time

which can be used for information transmission. But if the

sensing duration is too long, the spectrum resources

would be wasted by fast sensing process. Hence, there

must be an optimal sensing duration which can maximize

the CUR. From all above, it is obvious that the optimal

scheme is to integrate information from all CR users, and

then calculate the optimal sensing duration to inform each

CR user.

To prove the existence of optimal sensing duration, the

numerical simulation is brought about in our study. The

simulation parameters are shown in Table 1. [6].

In Figure 3 the maximum CUR can be achieved when

the sampling number M is at an appropriate value. How-

ever, the optimal sampling number is not fixed among

Table 1. The simulation parameters

Parameters Value

Average Detection Time0.5s

Sensing Interval 10ms

Feature Detection Time 100ms

Instantaneous SNR -24dB, -20dB,-16dB, -12dB, -8dB

Sensing Bandwidth 6MHz

CR User Number 5

-5

-4

-3

-2

-1

0. 7

0. 75

0. 8

0. 85

0. 9

0. 95

Sampling Proportion

Channel Utilization Ratio

S NR= -24dB

S NR= -20dB

S NR= -16dB

S NR= -12dB

S NR= -8dB

Figure 3. The channel utilization ratio vs. sampling proportion

50 A NOVEL SCHEME WITH ADAPTIVE SAMPLING FOR BETTER SPECTRUM UTILIZATION IN COGNITIVE RADIOS

-24 -22 -20-18 -16 -14 -12 -10-8 -6-4

0.75

0. 8

0.85

0. 9

0.95

average SNR(dB)

Channel Utilization Ratio

Propoesed Scheme

Conventional Scheme SP =0.1%

Conventional Scheme SP =4%

Conventional Scheme SP =16%

Figure 4. The channel utilization ratio vs. average SNR

ifferent SNR scenarios. Although the optimal sampling

At CR BS side:

e SNRs of all CR users.

culate the sampling

num

gy detection u

equa

ast the sampling number M to all the CR users.

At C

ber M to determine

sensi

number M cannot be calculated easily, the One-dimen-

sional Search Method can deal with the problem. It is clear

that in order to utilize the spectrum resource more effi-

ciently, the sampling number must be dynamically adjusted

according to the SNRs of CR users. Therefore, we propose

a novel sensing time schedule for CR system, which is

called dynamic adaptive sensing duration scheme:

1. Update th

2. Considering the target of ADT, cal

ber M which can maximize the CUR.

3. Calculate the threshold l of enersing

tion (10)

4. Broadc

R User Side:

ampling number M. 1. Update the s

2. Use the updated sampling num

ng duration and send the sampling results back to BS.

In Figure 4 we compare our proposed scheme wit

on how to maximize the CUR

produce interference small enough to primary network.

We deduce the relationship between conventional ROC

radio: Making

software radios more personal. Personal Communications, IEEE,

ree conventional ones whose sampling numbers are

different from each other but not dynamically changed. It

is obvious that the conventional scheme can gain a high

CUR only when the SNRs are at an appropriate level.

However the proposed scheme can always maximize the

CUR, in other words the proposed scheme reaches the

upper bound of the CUR for detection in CR system.

4. Conclusions

We have focused and

[8] TAHERPOUR A, KENARI N M, and JAMSHIDI A. Efficient

cooperative spectrum sensing in cognitive radio networks. In

which is composed by Prob. of detection and that of false

alarm and our proposed ROC which contains CUR and

ADT. Our proposed scheme shows that the CUR can be

maximized by optimizing time duration of energy detec-

tions according to different SNR conditions.

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