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1. Chapter 3 system model
3.1 system scenario based on CRSN architecture
The proposed system scenario consisting of wireless Sensor Network with Cognitive Radio is
depicted below. Here, the cellular network is used as primary network and the sensory
nodes act as the secondary or cognitive users whereas some nodes act as relay for
secondary nodes. This scenario is vaguely based on a typical CRSN architecture with the
feature that the relaying is offered only to the secondary node here, not to the primary
users as we have considered the underlay approach to spectrum access.
3.1.1 Underlay paradigm
The secondary nodes in this system use the technique of spectrum sharing with the primary
users concurrent primary and secondary transmissions may occur only if the interference
generated by the secondary transmitters at the primary receivers is below some acceptable
threshold- this is c. concurrent primary and secondary transmissions may occur only if the
interference generated by the secondary transmitters at the primary receivers is below
some acceptable threshold. The secondary transmitter is therefore very conservative in its
output power to ensure that its signal remains below the prescribed interference threshold.
In this case, since the interference constraints in underlay systems are typically quite
restrictive, this limits the secondary users to short range communications. Both spreading
and sever restriction of transmit power avoid exact calculation of secondary user
interference at primary receivers, instead using a conservative design whereby the
collective interference of all secondary transmissions is small everywhere. This collective
interference known as interference temperature which is discussed in detail at section 3.3.2.
3.2 System and Channel models
The cognitive network consists of a secondary source (ST), secondary receiver (SD) and a
secondary relay (SR) along with primary source (PT) and primary receiver (PR) shown in
figure 3. Here, h0, h1 h2 are the channel coefficients of the data links between ST to SD, ST

2. to SR and SR to SD respectively and h4 and h5 are the channel coefficients of the
interference link from ST to PR and SR to PR respectively. Again, g0 is the channel coefficient
of the link between PT and PR and g1, g2 are the channel coefficient of the interference link
from PT to ST and PT to SR respectively. All the channels are considered to follow Rician
distribution. Therefore
In the cognitive network, the secondary source and relay must adapt their transmit powers
(Ps and Pr respectively) below an interference threshold. Therefore, the minimum transmit
power at ST and SR are,
3.3, 3.4
Where I is the interference threshold and d is the relative distance from primary user. The
interference caused by the transmission of primary user PT is also taken into consideration.
In this model, the data transmission is divided into two time slots. In the first slot, ST
transmits it’s data to SR and SD, The SNIR of received signal is compared to a threshold at
the relay node. If the SNIR if received signal is greater than threshold, then relay transmits
the signal to SD. Otherwise ST transmits signal to SD and relay does nothing.
The SNIR of received signal at SR can be denoted as,
3.5
If SR can successfully decode the signal, it will forward the signal to SD in the second time
slot. The SNIR at RD and SD are,
3.6,3.7
Putting values of Ps, Pr and primary user Pp we get,
3.8, 3.9, 3.10
The end to end mutual information of the system under decode and forward relaying is
illustrated as,
3.11
Based on this, the end to end SNR at SD is,
3,12

3. 3.3 Performance metric:
The
3.3.1 Outage analysis:
The outage probability is defined as the instantaneous error probability exceeds a specified
value, or equivalently the case in which probability that the output SNR falls below a certain
threshold,γth. So, the outage probability can be written as
3.3.2: interference temperature:
The interference metric to be used in this work requires to provide a strict constraint on the
,,,transmission power of the nodes. Therefore, we have focused on the deterministic
Interference Temperature Constraints to be used as the interference metric for the
transmission power control. In an RF environment, the interference temperature is basically
the temperature equivalent of the power available at the receiver antenna measured in
unites of kelvin. The received power can be calculated as the product of the interference
temperature and bandwidth
P= kTB
Here, k is the boltzmann’s constant (), T is the interference temperature. In our case, it is
denoted as I
So, T= P/kB