Adaptive denoising at infrared wireless receivers

This paper proposes an innovative approach for noise cancellation at infrared (IR) wireless receivers. Ambient noise due to artificial lighting and the sun has been a major concern in infrared systems. The background induced shot noise typically has a power from 20 to 40 dB more than the signal induced shot noise and varies with time. Due to these changing conditions, infrared wireless receivers experience high level of non-stationary noise. The objective of the work mentioned in this paper is to develop digital signal processing algorithms at the infrared wireless system to combat high power non-stationary noise. The noisy signal is decomposed using a joint time and frequency representation such as wavelets and wavelet packets, into transform domain coefficients and the lower order coefficients are removed by applying a threshold. Denoised version is obtained by reconstructing the signal with the remaining coefficients. In this paper, we evaluate different wavelet methods for denoising at an infrared wireless receiver. Simulation results indicate that if the noise is uncorrelated with the signal and the channel model is unavailable the wavelet denoising method with different wavelet analyzing functions improves the signal to noise ratio (SNR) from 4 dB to 7.8 dB.