CDMA Based Cognitive Radio
Cellular Network
by
Sanjay Dhar Roy
[email protected]
ECE Department
National Institute of Technology, Durgapur, India
Introduction on Cognitive Radio (CR) and CR Network
Outage Analysis in Frequency Planned Cognitive Radio Network
Spectrum Sensing in CR-CDMA Networks with Co-located BSs
On the Data Services of Secondary User with Primary Exclusive
Region
INTRODUCTION
Cognitive Radio (CR): “Cognitive radio (CR) is a form of wireless
communication in which a transceiver can intelligently detect which
communication channels are in use and which are not, and instantly move
into vacant channels while avoiding occupied ones. This optimizes the use
of available radio-frequency (RF) spectrum while minimizing interference to
other users.”
WHY COGNITIVE RADIO?
•Demand for wireless communication capacities continuously growing
•Bandwidth is expensive and good frequencies are taken
•Occupancy of spectrum (below 1 GHz) is around 6~10%.
• Spectrum holes
CRN: A network that has CR as the main technology. CRN is mostly used
in association with a PRN. Present and future generation heterogeneous
networks use CR technology for efficient spectrum utilization.
INTRODUCTION
 Spectrum Sensing: Monitoring spectrum usage by primary users (PUs).
Enables CR users to adapt to the
environment by detecting spectrum holes.
 Spectrum Decision: Capability to decide the best available bands
according to QOS requirements.
 Spectrum Sharing: Coordinates transmission attempts between CR
users to avoid collision
 Spectrum Mobility: Ensures smooth and fast transition during
spectrum handoff.
Outage Analysis in Frequency Planned Cognitive Radio Network
BS6
BS1
D/2
BS5
D
BS0
r00
R0
BS4
BS3
PU
Fig : Frequency planned cellularcognitive radio networks.
BS2
SU
Fig: Hexagonal CR-CDMA networks
model with seven BSs.
System Model: Analytical modeling
The average power without shadowing at a desired PU (whose performance is
being measured) from BS0 can be expressed as follows:

Pr  Pt .r .10 1 0
0
n
1  r0 0
2 r0  n
 2 .   Pr rdrd  Pt . 2  r .rdr
r0  0
r0 0
Pd _ avg
for i = 1 to
i
10
Pt .10 .d i
SIR 
j
6
n
N co g
n
 Pt .10 1 0 .d j   Pco g,m .10
The SIR expression
for the desired PU:
j 1
m 1
 co g , m
10
.d m
n
i

C.10 1 0
 j
 A.10 1 0   B.10
 co g , m
10
 log e SIRthd   m SIR
Pout  Pr ob.SIR  SIRthd   1  Q
 SIR





0.014
r=0, analytical
r=0.5, analytical
r=0.9, analytical
0.012
r=0.9, simulation
r=0.5, sig =8dB
Probability of outage
0.01
r=0.5, sig=8dB, P
P
0.008
cog
cog
=0.125
=0.125, simulation
r=0.5, d1=D/2-50
0.006
0.004
0.002
0
50
100
150
200
250
300
350
400
Number of Secondary users
Fig : Outage probability as a function of the number of cognitive users. Results
with cluster size (Nq) = 7
Pout
(i) Pcog
(ii) r
(iii) shadowing
0.045
r00=400, sig =6dB, d1=D/2-10, pg=64
,
Probability of outage
0.04
r00=400, sig =6dB, d1=D/2-10, pg=32
0.035
r00=400, sig =6dB, d1=D/2-20, pg=64
0.03
r00=300, sig=8dB, d1=D/2-10, pg=64
r00=300, sig=6dB, d1=D/2-10, pg=64
0.025
0.02
0.015
0.01
0.005
0
10
20
30
40
50
Number of Secondary users
60
Fig: Probability of outage for a PU vs. the number of SUs.
Results with Nq = 1; Desirable-> Higher PG; smaller r00
70
Spectrum Sensing in CR-CDMA Networks with Co-located BSs
Performance of Cognitive Radio (CR) CDMA networks is analyzed.
A simulation test bed for analyzing the performance of a CR user with
and without spectrum sensing in a three cell scenario is developed.
CR users belong to a Cognitive Radio Network (CRN) which coexists
with a Primary Radio Network (PRN). Both CRN and PRN are CDMAbased.
Three different schemes for spectrum sensing are considered (spectrum
underlay).
Soft Handoff (HO) and power control are considered for both CRN and
PRN.
Performance in terms of: (1) outage probability, (2) blocking probability,
(3) average data rate of secondary users (SUs).
G
H
BS1
E
C
BS0
Rh
A
B
R0
I
D
F
BS2
J
Fig: Hexagonal multi-cellular model with three BSs
labelled as 0, 1, 2.
System Model (contd.)
 Three-cell CDMA network. Each cell with co-located primary BS and
secondary BS. Each cell has three sectors.
 Fixed number of PUs and fixed number of SUs are considered. Multi
code (MC)-CDMA is assumed for PUs and SUs.
 BS distinguishes transmissions from SU and PU by cyclostationary
measurements.
 Interference due to SUs and PUs at SBS is estimated. SINR at SBS for the
desired SU is estimated. Performance of a SU is evaluated on the basis
of this SINR.
 Performance of a SU has been measured in terms of blocking probability
and achievable data rate.
System Model (contd.)
Scheme 1:
• Equal number of two types of PUs.
• Interference limit Imax (in uplink) determined in the absence of SUs.
• A basic data rate for PUs.
• At any time, total interference caused by SUs and PUs must be less than
this interference limit.
Scheme 2:
• Network allows some amount of interference from SUs as well, in the
presence of PUs.
• The tolerable amount of interference is limited by the ratio, Imax/ucp.
• The other main network parameters are set as in Scheme 1.
Simulation Model
Generation of Users’ Locations and Interference Powers:
1. Fixed numbers of users (PUs and SUs) are generated.
2. Link gains corresponding to each user are generated.
3. Corresponding interference at BS is also generated.
4. Interferences are generated from all users at non handoff region, soft
handoff region, and from users of other sectors.
Probability of Outage with Spectrum Sensing:
1. The ratio between the interference power due to SUs’ activity and the
interference power due to PUs’ activity is evaluated at SBS.
β +1 > 1 / u
2. If the condition
is not satisfied, then SUs are removed
one by one, initially from the non-HO region of BS0 (region ‘A’) and
β I /I
then from other zones i.e., regions ‘B’,…,‘H’. Here
is the ratio of the interference powers of SUs and PUs.
cp
SU
3. Finally, outage probability is evaluated.
PU
0.14
PU1=5, PU2=5, r d=7 kbps, Scheme1
PU1=5, PU2=5, r d=7 kbps, Scheme2
0.12
Ghavami no SS
Ghavami SS
Ghavami SS and BF
Probability of Outage
0.1
0.08
0.06
0.04
0.02
0
5
5.5
6
6.5
7
7.5
Number of Cognitive Users
8
8.5
9
Fig: Probability of outage for a SU as a function of the number of SUs.
Pout
if Nsu
0.14
PU1=5, PU2=5, r d=7 kbps, Scheme1
PU1=5, PU2=5, r d=7 kbps, Scheme2
0.12
Ghavami no SS
Ghavami SS
Ghavami SS and BF
Probability of Outage
0.1
0.08
0.06
0.04
0.02
0
5
5.5
6
6.5
7
7.5
Number of Cognitive Users
8
8.5
9
Fig: Probability of outage for a SU as a function of the number of SUs.
Pout
if Nsu
0.35
SU=5, r =10 kbps, Scheme1
d
0.3
SU=5, r =10 kbps, Scheme2
d
Blocking Probability
0.25
0.2
0.15
0.1
0.05
0
5
6
7
8
9
10
11
12
13
Number of Primary Users
Fig. Blocking Probability for SUs as a function of the number of PUs,
with fixed number of SUs and fixed value of SUs’ data rate.
Pblk Npu ; Scheme 2 is better than Scheme 1 in terms of Pblk .
10000
Average data rate of SU(bps)
9000
PU1=5, PU2=5, r =5 kbps
d
8000
PU1=5, PU2=5, r =10 kbps
d
7000
6000
5000
4000
3000
5
6
7
8
9
10
11
12
Number of Cognitive Users
Fig. Average data rate of SUs as a function of the number of SUs with
fixed numbers of PUs and various values of SUs data-rate for Ghavami
SS.
Data rate if Nsu or rd
Major Remarks
The proposed simulation model allows fast performance evaluation of a
Cognitive Radio CDMA network.
As expected, spectrum sensing can improve the performance.
Scheme 2 outperforms Scheme 1 in terms of SU blocking probability for
any given fixed number of SUs and this improvement is more pronounced
for large numbers of PUs.
The SU performance, in terms of outage and blocking probabilities,
improves if the data rate of SUs decreases.
A larger number of cognitive users degrade the SU performance, in
terms of outage and blocking probabilities, for fixed number of PUs.
On the Data Services of Secondary User with Primary
Exclusive Region
This work
Performance of Cognitive Radio (CR) CDMA networks is analyzed.
A simulation test bed for analyzing throughput, delay performances of a
SU in a single cell, where both SUs and primary users (PUs) are present.
PUs are inside the primary exclusive region.
CR users or SUs forming pair wise links belong to infrastructure less ad
hoc network, which coexist with a Primary Radio Network (PRN).
Spectrum underlay type of communication where SUs transmit in
presence of PUs maintaining a predefined interference limit for PRN.
 A SU transmits packetized data for its corresponding receiver.
 A stop and wait ARQ protocol at MAC layer for packet retransmission by
the SU of interest.
System Model
SUR
D
x
PU
SUT
SUT
x
BS
d0
x
SUR
x
Fig. One cell model with a number of PUs and SUs. PUs are power controlled by the BS at
the center of the cell. SU receiver corresponding to each SU transmitter is within the circle
of radius of 0.5dadhoc. The inner circle is exclusively for PUs only. SUs are allowed inside the
annular ring i.e., in between the circles with radii d0
and
D.
System Model (contd.)
The network with a number of PUs and SUs uniformly distributed inside
the cell.
All users (both PUs and SUs) have omni directional antennas for
transmission.
A PU is power controlled by the BS. Similarly, a SU transmitter is assumed
to be power controlled with respect to its corresponding SU receiver.
 A “continuously active” data traffic model as in [7] is considered for each
SU link where each SU generates a sequence of fixed length packets. A
new packet is generated as soon as the preceding packet is delivered
successfully.
A SU is allowed to transmit, if interference at BS for the PU link of interest
is below a predefined interference threshold. Up link interference at BS for
a PU is due to all other PUs other than the desired one, and all SUs. QoS of
any user is directly related to SINR of the user. Hence, we find SINR of a
PU and SINR of a SU.
System Model (contd.)
The SINR of a PU , in terms of bit energy to noise power spectral density, may be expressed as
follows:
Pt _ p ,i G p 2 p ,i
W
 N pu
N su
R pu
 Pt _ p ,q G p 2 p ,q   Pt _ s ,l Gs 2 p ,l  N
i 
p
q 1
q i
j 
The SINR at j-th SU receiver,
s
l 1
Pt _ s , j Gs 2 s , j
W
 N su
N pu
Rsu
 Pt _ s ,u Gs 2 s ,u   Pt _ p ,v G p 2 s ,v  N
u 1
u i
v 1
N pu
N su
q 1
q i
l 1
The UL instantaneous interference for i-th PU :  P G
t _ p ,q
p 2 p , q   Pt _ s ,l Gs 2 p ,l  N  I thd
The retransmission probability Pr :
Pr  1  (1  Pe )
L p rc
Pr is simulated and corresponding throughput, delay are found using following eqns.
Packet transmission time
:
Throughput
:
Ti 
Lp
G
Rsu

L p rc
D
Lp
PG
Rc

rc Rc (1  Pr )
PG
Delay :
D
L p PG
Ti

(1  Pr ) Rc (1  Pr )
Simulation Model
A. Generation of Users’ Locations and Interference Powers:
1. Fixed numbers of users (PUs and SUs) are generated.
2. The locations of all SUs and PUs (with respect to the BS are
generated within the cell. A number of SU receivers are generated
around corresponding SU transmitters.
3. For each of the users, the link gains corresponding to BS and SU
links (e.g., link gains from PU to BS, SU to BS, PU to SU, SU to SU)
are generated.
4. The interference power received at the reference BS for the PU of
interest is evaluated. Similarly, interference power for the SU link of
interest is evaluated, considering interference from all other SU
transmitters, and all PUs in the system.
5. Next, the SINR for the SU is evaluated. Interference at BS for the
PU is also evaluated. If this instantaneous interference is less than
the interference threshold then the SU of interest will be allowed to
transmit data.
Simulation Model (contd.)
B. BER simulation of data :
1. A sequence of random data bits +1 or –1 is generated which
indicates the transmitted bits.
2. A Gaussian noise sample is generated with variance  g2  1. /(2. pg. s )
and added to each transmitted bit, where  s is found following steps
A (1) to A (5) for a given PG.
3. The received bit is first detected as +1 or –1 after comparing with a
threshold of 0. Then each received bit is compared with
corresponding transmitted bit and an error_count is incremented if
they disagree.
4. Steps B(1) to B(3) are repeated to estimate BER.
Simulation Model (contd.)
C. Packet error, Delay and Throughput simulation
1. A packet consisting of L (information bits are generated. A sample
of Gaussian noise as in B(2) with processing gain (PG) as in B(2) is
added to each transmitted bit of a packet.
2. The received L bits of a packet are checked with their
corresponding transmitted bits to assess packet error.
3. If the received packet is incorrect, the same packet (i.e. same bit
pattern as in C(1)) is retransmitted until the packet is received
correctly finally.
4. Total number of erroneous packet is counted out of a large number
of transmitted packets to estimate the PER.
5. Average delay (D) and throughput are estimated from
retransmission probability.
0.07
0.06
Packet Error Rate
0.05
0.04
Pptmax = 0.5, P stmax = 0.5
Pptmax = 1, P stmax = 0.5
0.03
Pptmax = 0.5, P stmax = 0.05
Pptmax = 1, P stmax = 1
0.02
0.01
0
300
400
500
600
700
800
Radius of PUs exclusive region (meter)
Fig. PER vs. d0 (meter)
900
1000
0.02
Npu = 5, Nsu = 5
0.018
Npu = 5, Nsu = 10
Npu = 10, Nsu = 5
0.016
Packet Error Rate
0.014
0.012
0.01
0.008
0.006
0.004
0.002
0
300
400
500
600
700
800
Radius of PUs exclusive region (meter)
900
1000
Fig. PER vs. d0 (meter) for different number of users
PER
d0
20
18
Throughput (kbps)
16
Pptmax = 0.5, P stmax = 0.5
Pptmax = 1, P stmax = 0.5
14
Pptmax = 0.5, P stmax = 0.05
12
10
8
6
300
400
500
600
700
800
Radius of PUs exclusive region (meter)
900
1000
Fig. Throughput vs. d0 (meter) for different Pmax values
d0
Throughput
Major remarks
We have proposed a framework for analyzing data performance
of a SU operating in spectrum underlay.
Specifically, we have given more attention on the effect of
changing transmit powers of PUs and SUs on SU’s performance.
We have shown impacts of PUs’ interference on SU by
considering a PU’s exclusive region. If d0 decreases interference
on SUs increases which further worsen SUs’ data performance.
Increasing upper limit of PUs’ transmit power has more
detrimental effect on SUs’ performance than increasing upper limit
of SUs’ transmit power.
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Thank You