Cooperative underlay cognitive radio assisted NOMA: secondary network improvement and outage performance

In this paper, a downlink scenario of a non-orthogonal multiple access (NOMA) scheme with power constraint via spectrum sensing is considered. Such network provides improved outage performance and new scheme of NOMA-based cognitive radio (CR-NOMA) network are introduced. The different power allocation factors are examined subject to performance gap among these secondary NOMA users. To evaluate system performance, the exact outage probability expressions of secondary users are derived. Finally, the dissimilar performance problem in term of secondary users is illustrated via simulation, in which a power allocation scheme and the threshold rates are considered as main impacts of varying system performance. The simulation results show that the performance of CR-NOMA network can be improved significantly.


System Description
A network consists of a secondary source (S), a relay (R) and two destination users (D1, D2) is considered. We only examine a downlink cooperative underlay CR-NOMA network and existence of a primary destination (P) as shown in Figure 1. The corresponding distances between nodes S-P, R-P, S-R, R-D1, R-D2 are given as , , , 1 and 2 .
Thus, the secondary transmit node is restricted as ≤ ( |ℎ | 2 ,̂), ∀ ∈ { , }. In this case, ̂ denotes the maximum average allowed transmit power at node while indicates the interference temperature constraint (ITC) at P. to user D1 through the assistance . In NOMA, is the power allocation factors with ∑ √ = 1 2 =1

S
. Then, the signal received the relay can be express as: the signal-to-interference-plus-noise ratio (SINR) and signal-to-noise ratio (SNR) of 1 is decoded and removed from the received signal at R and it can be given as: then the SINR of 2 when it is decoded from the received signal where = 2 . In the second time period, forwards the detected superimposed signal to both users D1 and D2. Therefore, the signal received by the two destination can be given by:

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Based on NOMA scheme, D2 first decodes the message designated for D1 and removes it using SIC, then it decodes its own message without interference. Therefore, the instantaneous SNR at D2 can be expressed as: next, D1 can detect ̃1 by treating ̃2 as a noise with the following SINR

Outage Analysis 3.1. Outage Probability at D1
Consider metric to evaluate system performance, the NOMA users'performance will be examined in term of outage probability. The transmission strategy in CR NOMA is performed related to how success each node in such network can support transmission, which significantly improve quality of the communication for multiple services provided. In this paper, main evaluation metric, namely outage probability is used to characterize the system performance. The outage event for D1 can be expressed by: Considering , as integration variable, by employing exponential distribution for |ℎ | 2 and |ℎ | 2 ; the Cumulative Distribution Function (CDF) of |ℎ | 2 is |ℎ | 2 ( ) = (|ℎ | 2 < ) = 1 − − . So, with help of (2) 1 ( 1 ) can be write as: where: Δ = Ω |ℎ | 2 , Ω = , ̄=2, = 2 . Now, we can transfer as: in this case, we define the first term and the second term of (10) denote A and B respectively. Based on the exponential distribution of |ℎ | 2 , can be written as: next, the second term denoted by B can be obtained as: therefore, replacing (11) and (12) into (10) 1 ( 1 ) can be express as: similar, with help (5) we can wirte 21 ( 1 ) as: next, 21 ( 1 ) can be transfer as: then, following the same steps as in (10)-(12), Based on the exponential distribution of |ℎ | 2 , 1 ( 1 )and 21 ( 1 ) can be written respectively as:

Outage Probability at D2
Similarly, the outage event for D2 can be formulated by: with help (3) then we can write 2 ( 2 ) as: similarly, based on the exponential distribution of |ℎ | 2 . So 2 ( 2 ) can be express as: with the help of (6), we can write 2 ( 2 ) as: applying similar techniques as before, we simplify 2 ( 2 ) as: replacing (21) and (23) into (19) 2 can be obtain as:

Performance Evaluation
In this section, we evaluate the performance of resource allocation for NOMA-based cognitive radio network. Consider a geographical area covered by a primary wireless network and a cognitive wireless network. We assume equality noise terms as 2 = 2 = 1 2 = 2 2 = 2 and regarding distances we set = = = 2 = 2, 1 = 2 2 . The path loss factor is 3, power allocation fractions are 1 = 1 = 0.8, 2 = 2 = 0.2, = 25 and = 0.001 We evaluate the impact of the transmit SNR on the outage performance for NOMA-based cognitive radio network in Figure 2 and Figure 3. At higher SNR, outage performance can be enhanced significantly. With the case data rate R1 increases, the outage performance will be worse. In addition, there is strict agreement between analytical result and Monte-Carlo result. From Figure 4 and Figure 5, it can be concluded that the proposed system not only guarantees the minimum transmission rate, but also improves the outage performance significantly. Although NOMA scheme improves the performance of cognitive radio network, it is at the cost of increasing the complexity of secondary user receiver. At high Consequently, designing a proper value for the parameter threshold SNR can achieve the values of the threshold SNRs 1 and 2 , the system meets outage event. The tradeoff between the performance gain and the required transmit SNR of secondary users. This is due to the fact that there is more power for transmitter to improve the outage behavior at the receiver.

Conclusion
In this work, we studied the downlink NOMA problem for NOMA-based cognitive radio network. The secondary network performs the resource allocation of power with acceptable outage performance. The transmit SNR, the threshold data rates are main impacts on outage performance. Simulation results demonstrated that the proposed system improve the spectrum efficiency significantly.