Optimization Techniques In AI For Telecommunication
Description
The rapid evolution of communication networks has created a strong demand for intelligent and adaptive management techniques. Artificial Intelligence (AI) has emerged as a key enabler in addressing these challenges by introducing data-driven decision-making into telecommunications systems. A critical function of AI in this domain is optimization, which focuses on improving how network resources are allocated and utilized under varying conditions. This study investigates multiple AI-based optimization approaches, including learning-based models, heuristic strategies, and bio-inspired algorithms, and analyzes their role in enhancing network performance. It further examines how these methods contribute to reduced operational costs, improved service delivery, and autonomous system behavior. The paper also discusses practical challenges associated with real-world deployment, highlighting the need for scalable and efficient AI integration in future communication networks.
Files
RTET-2K26.V14_issue3_136.pdf
Files
(575.8 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:7fb4756beb8bec5dfafe9bdf17877dac
|
575.8 kB | Preview Download |