A High-Performance Adaptive Communication Framework For Next-Generation Wireless Networks
DOI:
https://doi.org/10.29284/fg60fm82Keywords:
Adaptive Communication Framework, 5G/6G Networks, Machine Learning, Software-Defined Networking, Mobile Edge Computing, Resource Allocation, Quality of Service.Abstract
The fifth-generation (5G) and newer Next-generation wireless networks should be able to accommodate high data rates, large connectivity, strict data latency, and high reliability. Nevertheless, the traditional static network management scheme is becoming less and less satisfactory in dynamic contexts that are variable in channels, variable in user mobility and in heterogeneous traffic requirement. In this paper, a high-performance adaptive communication framework is proposed, which can optimize a system across the three layers in real-time by using massive MIMO, multi-band wireless communications, Software-Defined Networking (SDN), Mobile Edge Computing (MEC) and AI-driven decision-making. The suggested structure will dynamically change radio and network parameters in order to sustain Quality of Service under changing conditions. Simulation at the system level shows that the system achieves a much better result than a non-adaptive baseline in terms of latency, throughput, reliability, spectrum efficiency and energy efficiency. The findings support the success of an intelligence-informed coordination adaptation and emphasize the applicability of the framework to the future 5G and 6G applications, such as dense IoT, autonomous systems, and immersive services.
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This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
