| Summary: | Topology control in next-generation wireless networks has recently attracted the interest of several researchers. The network performance is significantly affected by the topology. Therefore, creating an optimal topology is essential, particularly in fifth-generation (5G) networks, where latency, throughput, energy efficiency, and other performance metrics are highly stringent. In this study, we investigated topology control algorithms in 5G-based mobile ad-hoc networks (MANET). A novel algorithm, namely Topological control by Flexibly Adjusting the Coverage Radius (TFACR) was proposed to improve network performance. The main idea of the TFACR algorithm is to adjust the communication range flexibly to obtain the desired degree of nodes. The degree constraint of the neighboring nodes is considered each time a node adjusts the communication area to ensure node degree balancing throughout the network topology. The TFACR algorithm is implemented in the OMNET++ and INET frameworks using the Reinforcement Learning-based routing protocol (RLRP), Ad-hoc On-demand Distance Vector (AODV) and Destination Sequenced Distance Vector (DSDV) routing protocols to evaluate its performance. The simulation results proved that the proposed algorithm outperformed well-known topology control algorithms in terms of the average node degree, quality of transmission, and energy consumption. This is suitable for 5G-based MANET.
|
|---|