Reduced-Complexity Selective Mapping for Improving Wireless Communication in Smart Irrigation Systems

This paper presents a novel approach for reducing peak-to-average power ratio (PAPR) in filter bank multi-carrier systems and its application in smart irrigation. The proposed reduced-complexity selective mapping (RC-SLM) technique divides frequency domain data symbols into smaller sub-blocks and applies shorter phase sequences than traditional selective mapping methods. Additionally, it utilizes a low-complexity conversion block to further reduce complexity. Simulation results show that the RC-SLM outperforms traditional selective mapping in PAPR reduction and computational complexity. Furthermore, it is demonstrated how the RC-SLM can be applied in wireless communication systems for remote control and monitoring of irrigation systems. This paper also examines the impact of carrier frequency offset on bit error rate performance of RC-SLM technique. The results illustrate that the RC-SLM can significantly improve the range and reliability of communication in smart irrigation systems and make them more energy-efficient.