Optimizing adaptive modulation technique using standard propagation model for enhanced wireless communication channels

Recent progress in the domain of wireless communication systems has brought to light emerging trends that underscore the evolution of modern communication paradigms. Nonetheless, the performance of such systems remains constrained by persistent technical limitations, including packet loss, bandwidth scarcity, and suboptimal spectral efficiency, all of which necessitate rigorous analytical investigations. To address these constraints, the present study leverages an adaptive modulation technique tailored to enhance communication efficiency. This technique is systematically evaluated considering various parameters, including the signal-to-interference-plus-noise ratio (SINR), link distance, and the Standard Propagation Model (SPM), across canonical wireless channel environments, such as Additive White Gaussian Noise (AWGN), Rayleigh, and Rician fading models. The primary objective is to minimize the Bit Error Rate (BER), maximize system throughput, and ensure efficient utilization of available bandwidth by strategically optimizing the SPM parameters for long-range cellular communication links. Simulation outcomes substantiate that the proposed SPM-integrated framework achieves a target BER = 10-2 and exhibits enhanced spectral efficiency for 64-QAM modulation across a 6 km cell radius, thereby outperforming the conventional non-SPM approach. Notably, the proposed technique achieves SINR improvements of 40%, 43%, and 41% under AWGN, Rayleigh, and Rician conditions, respectively. To ensure optimal configuration, an advanced optimization algorithm is employed to dynamically select the most effective SPM parameters, enabling robust performance across varying channel conditions. Moreover, empirical analysis confirms that the SPM-enhanced system architecture facilitates the stable deployment of 64-QAM across all tested channel models, consistently yielding superior SINR and reduced BER relative to baseline techniques that lack SPM integration.