Node clustering scheme supporting mobility in NOMA-enabled backscatter communication networks

Abstract

In this paper, we study the problem of mobile node clustering in non-orthogonal multiple access (NOMA) backscatter communication networks. The nodes are clustered based on the differences between their channel gains to accomplish NOMA transmission within the clusters. However, as the channel gains change constantly with node mobility, the nodes need to be re-clustered, which leads to a significant computational overhead. We propose a node clustering scheme (IGAC). This scheme formulates the node clustering problem as a combinatorial optimization problem to find the optimal node clustering that maximizes system throughput. To handle the large search space of multi-node clustering, we employ a genetic algorithm to solve this optimization problem effectively. Moreover, to overcome the NOMA principle violation problem(NPVP) caused by mobile nodes, we propose a node clustering adjustment scheme (SMSO) based on stable matching ideas and swapping operations. According to the theory of stable matching, optimizing the long-term throughput of the system can be achieved by swapping nodes between different clusters to eliminate blocking pairs in clustering. The simulation results show that our proposed node clustering scheme outperforms traditional schemes in terms of system throughput.