DEVELOPMENT OF METHODS TO IMPROVE ENERGY EFFICIENCY OF DIGITAL RADIO SYSTEMS USING A MULTI-THRESHOLD DECODER

Energy efficiency in digital radio systems is one of the key challenges in modern communication systems. This is especially relevant in fading environments, where it is necessary to minimize energy consumption while maintaining high data transmission quality. The goal of this research is to develop and evaluate methods for improving the energy efficiency of digital radio systems using multi-threshold decoding (MTD) and convolutional coding. The efficiency of these methods was tested under various operating conditions of radio channels. Effective convolutional codes were selected for MTD, which ensure a high level of data protection during transmission. The study evaluated the energy efficiency of these codes in channels with additive white Gaussian noise. The convolutional coding methods allowed for significant improvements in MTD performance, which led to increased reliability of data transmission. Additionally, iterative demodulation and decoding methods were used, enabling the correction of errors with each iteration. This approach contributed to a significant increase in data transmission accuracy by repeatedly performing the processes of demodulation and decoding, especially in complex conditions. The research results showed that the proposed methods allowed for a 12-18% reduction in system energy consumption. Furthermore, with a signal-to-noise ratio (SNR) of 10 dB, the bit error rate (BER) decreased from 10⁻³ to 8×10⁻⁴, improving error correction efficiency by 15-20%. The accuracy of data transmission in fading environments also improved by 10-15%, enhancing the overall reliability of the system. The practical significance of this research is that the proposed methods can be successfully applied in modern radio systems to increase their energy efficiency and improve communication quality, particularly in challenging transmission conditions.