Cognitive Radio and Signal Processing Approaches for Energy-Efficient Next-Generation Wireless Networks
Md. Solaiman Mia, Jonathan Osei‐Owusu · International Journal on Smart & Sustainable Intelligent Computing · 2025
Spectrum use and energy efficiency are also paramount issues in next generation wireless networks as the amount of user demand and dynamic conditions in the channel goes up. The paper proposes a hybrid cognitive radio system combined with a sophisticated signal processing method in a way that optimizes energy usage, spectral efficiency and latency. The proposed model dynamically detects available spectrum, anticipates channel states, and allocates resources dynamically and attempts to reduce error rates. Experiments with simulation prove that the system is 92 % energy efficient, surpassing traditional wireless (68 %), OFDM (75 %), and non-optimized cognitive radio (81 %). The system provides throughput of 82 Mbps with lower latency of 12 ms and bit error rate of 2.5×10 3 and is robust to communication both at peak and system loads. Spectral efficiency increased to 5.6 bps/Hz with a fairness in resource allocation of 0.91 allowing it to operate at low-, medium-, and high-load conditions in a scalable manner. Despite a rise in computation time to 2.5 s, the efficiency and flexibility benefits justify the trade-off. Generally, cognitive radio and optimized signal processing are one avenue that offers potential solution to the two goals of energy efficiency and high-performance wireless communication in future wireless networks.