Improving Conductive Fabric Networks with Error Correction Codes

This paper explores the enhancement of conductive fabric area networks (CFANs) through the integration of error correction coding techniques. Utilizing a two-layer conductive fabric as the communication channel, we leverage frequency shift keying (FSK) for modulation and demodulation across the nodes. Aimed at improving the quality of service, this paper presents a comparative analysis of error correction methods: Repetition code and Hamming code under various channel conditions, including Gaussian and non-Gaussian interference. These conditions mimic real-world disturbances potentially affecting CFANs, such as other sensors or actuators within the network. Performance metrics, specifically bit error rate (BER) and packet error rate (PER), are employed to evaluate the efficacy of each coding method. Preliminary results indicate that the repetition code significantly outperforms others in minimizing the BER and the PER, followed by the Hamming code and the baseline approach, particularly under conditions of low Signal-to-Noise Ratio (SNR). To ensure a fair comparison, we normalized the BER and PER values to account for different code rates. This investigation highlights the potential of error correction codes to substantially improve CFAN reliability, laying the groundwork for future applications in wearable technology and soft robotics.