An Optimized Bio‐Inspired Ensemble Waveform Architecture for High‐Efficiency 6G Massive MIMO Communication

ABSTRACT The widespread adoption of 5G networks worldwide has driven the need for smarter, more reliable, and more efficient communication systems, which has spurred early‐stage research into 6G technology. The prevailing waveform and optimization methods in 5G, as well as initial work on 6G, are generally plagued by high error rates, inefficient spectrum utilization, and insufficient adaptability in dynamic MIMO scenarios. To address the above challenges, this research proposes a new Boosting Hyena Filter Bank Multicarrier (BH‐FBMC) model, incorporated into a 6G MIMO system, to improve transmission reliability and mitigate error rates via optimized beamforming. The model leverages the spectral efficiency of FBMC and the adaptive search functionality of the Hyena optimization algorithm (HOA) to adjust beamforming vectors and allocate resources adaptively based on the channel environment. The operation involves signal encoding, BH‐based beamforming in a multiple‐input multiple‐output (MIMO) system, user signal tracking, and adaptive decoding. Performance is measured using key parameters such as Signal‐to‐Noise Ratio (SNR), throughput, error rate, data transfer rate, and communication delay. Experimental outcomes show dramatic enhancements, with a throughput of 12.5 Gbps, a data rate of 782 Kbps at 100 active nodes, an SNR of 33.36 dB, a delay of 14 ms in communication, and a rate of errors of 8.9%, proving the appropriateness of the suggested model for use in next‐generation 6G applications.