Hybrid coalitional game-theory model for coordinated wireless sensor networks

Coordinated Multipoint Transmission (CMT) is critical in obtaining faster data transfer speeds than other systems during the Advanced Long-Term Evolution (LTE-A) of networks and 5G data transmission. Additionally, the Radio Access Network (RAN) requires more transmission points (TP) for data transfer in smaller groups. This article proposes a unique architecture for sending data from the sensor node to the receiver via cluster creation and data aggregation techniques. With the models mentioned above, the implementation of a game-theoretic energy-efficient clustering mechanism. The clustering model utilized in this work is a load-aware model based on a coalitional game with merge/split operations for maximizing Spectral Efficiency (SE) of the network and load balancing (LB). Suggested hybrid algorithm’s simulation results indicate that the supplied model beats the greedy clustering model by 71.6 percent energy efficiency in over-load scenarios. Thus, the network may run without backlogs even under high load situations, such as those associated with hotspots. Thus, the number of dissatisfied users under the given overload state is substantially lower than conventional clustering techniques.