Adaptive Routing Protocol for 5G WSN Using DBN-PSO and Spectrum Optimization Techniques

Wireless Sensor Networks (WSNs) operating over 5G infrastructure require energy-efficient and adaptive routing mechanisms to support high data rates, dynamic spectrum conditions, and prolonged network lifetime. This paper proposes an adaptive routing protocol for 5G-enabled WSNs using a Deep Belief Network optimized with Particle Swarm Optimization (DBN-PSO) combined with spectrum optimization techniques. The proposed framework integrates modulation, Singular Value Decomposition (SVD)-based spectrum enhancement, adaptive equalization, and intelligent resource allocation to mitigate channel impairments and optimize routing decisions. Simulation results demonstrate that the proposed Extn-dep-LN approach significantly outperforms existing protocols. Energy consumption is reduced to approximately 0.40 units at 200 nodes and remains below 0.65 units at 1000 nodes, achieving an energy saving of nearly 35– 45% compared to GEEC and TTDfP. The network lifetime is extended to about 3.24 × 10⁴ rounds, compared to less than 3.0 × 10⁴ rounds for conventional methods. The proposed protocol achieves a high throughput of approximately 0.97 at 200 nodes and maintains above 0.90 at larger network sizes. Furthermore, packet delivery to the sink reaches nearly 2.4 × 10⁶ packets at 6000 rounds, indicating improved routing reliability and reduced packet loss. These results confirm that the proposed DBN-PSO-based adaptive routing protocol is highly effective for scalable, energy-efficient, and high- throughput 5G WSN applications.