Hybrid approaches to PAPR, BER, and PSD optimization in 6G OTFS: Implications for healthcare

Abstract

The envisioned smart hospital framework leveraging the sixth-generation (6G) technology aims to enhance healthcare services by ensuring reliable communication across various wireless channel conditions, including both line-of-sight and obstructed paths. However, the traditional orthogonal frequency division multiplexing (OFDM) approach, used in 4G and 5G, struggles with the high Doppler shifts associated with dynamic environments, presenting challenges for burgeoning smart hospital demands. To address this, orthogonal time frequency space (OTFS) modulation is proposed. The OTFS operates effectively across both stationary and highly mobile channels by manipulating delay and Doppler domains. Nevertheless, a high peak-to-average power ratio (PAPR) remains a critical challenge for OTFS implementation within 6G smart hospitals. Elevated PAPR levels can reduce power amplifier efficiency, causing them to operate outside their ideal linear range and impairing battery performance. They also contribute to signal distortion, increased interference, and suboptimal spectrum utilization, which can undermine wireless communication and data integrity. To mitigate the PAPR issue in OTFS, this work introduces a hybrid algorithm that integrates the benefits of the Riemann matrix optimal phase element-based partial transmission sequence (PTS) and selective mapping (SLM), along with A and μ-law complementary algorithms. This study compares the performance of the proposed hybrid algorithm with traditional PAPR reduction techniques by evaluating metrics such as PAPR, bit error rate (BER), and power spectrum density (PSD) within the Rician and Rayleigh fading channels. Simulation outcomes indicate that the hybrid algorithm achieves superior PAPR, BER, and PSD performance with only a marginal increase in complexity when compared with the established methods.