# Secure PD-NOMA with Multi-User Cooperation and User Clustering in Both Uplink and Downlink PD-NOMA
## 3 Proposed Secure Communication, Multi-User Cooperation, and User Clustering Strategy in PD-NOMA
### Proposed Solution for User Clustering Strategy  
In the multi-user PD-NOMA system, user clustering or user pairing is as important as the power allocation among the users. The capacity and performance of the PD-NOMA system can be greatly improved by using the proper user clustering strategy. The concept of user grouping is in line with the basic needs of PD-NOMA systems because simultaneous transmissions at the same time and frequency in the denser systems are impractical. The lack of user clustering in the denser PD-NOMA system increases the system overhead for error propagation and channel feedback cooperation. To avoid the system overhead, user clustering can be utilized to improve the capacity and efficiency of PD-NOMA systems. In user clustering, users are divided into multiple groups where PD-NOMA can be effectively employed within each NOMA cluster. Through user clustering, the power distribution among users becomes an easy assignment. Our proposed user clustering strategy is very helpful in assigning users into different clusters. Suppose we have a total of \(N\) users in the vicinity of a gNodeB. The total number of clusters (\(C\)) equals or less than half of the total number of users (\(C\leq N/2\)). A minimum of two users and a maximum of \(N/2\) users can be assigned to each NOMA cluster. However, an increasing number of users in a cluster results in poor performance. This is due to the multiple levels (m-levels) of SIC that are involved when there are the most users in a cluster. Due to m-level SIC, the complexity of decoding the weak user signals at the strong user increases, which results in poor performance. The best performance can be achieved when users have a maximum distance separation. Our proposed technique uses the following steps to distribute users among clusters:  
* Make \(C\) clusters with \(C\leq N/2\). * Select a minimum number of users in each cluster to reduce intra-cell interference. * Each group must contain users with a maximum distance separation. The proposed three-step technique has been tested on a four-user system and can be expanded to an \(N\) number of users distributed across \(C\) clusters. All possible cluster arrangements for four users, \(R_{1}\), \(R_{2}\), \(R_{3}\), and \(R_{4}\) are shown in Figure 5. Based on the above three steps, four different cluster types are presented, and each user is supposed to be distance \(d\) away from the next user. Using the first step of the proposed algorithm, four different clusters are created. In the Cluster Types 1, 2, and 3, two clusters \(C_{1}\) and \(C_{2}\) are made and assigned with two users each. As shown in Figure 5, Cluster Type 4 has one cluster \(C_{1}\) with four users. The second step of the proposed algorithm is to choose a minimum number of users in each cluster. This is performed to reduce the intra-cell  
Figure 4: Multi-user cooperation in Cop-PD-NOMA with \(R_{1}\), \(R_{2}\), and \(R_{3}\) as strong users and \(R_{4}\) as a weak user. interference that happens when there are more users within the cluster. For example, Cluster Type 4 has four users and each successive user is distance (\(d\)) apart from the other. It will use a 3-level SIC technique to decode the signal at near user \(R_{1}\). Similarly, \(R_{2}\) will use a two-level SIC technique, while \(R_{3}\) will use a single-level SIC technique. Due to the increased number of users, the cluster complexity in terms of the multi-level SIC operation and intra-cell interference increases. Hence, Cluster Type 4 fails to achieve the criteria of the second step. On the other hand, Cluster Types 1, 2, and 3 have limited the number of users to a minimum level (each cluster with two users). In these three cluster types, each cluster performs a single-level SIC technique and experiences a minimum intra-cluster interference.