Doppler Impact on Image Transmission over OFDM in IoT Networks
Keywords:
OFDM, IoT Networks, Image Transmission, Doppler Frequency, Channel Estimation, Minimum Mean Square Error (MMSE), Pilot Subcarriers, Dynamic Environments.Abstract
This paper focuses on signal processing methods for receivers handling OFDM encoded signals in IoT networks, emphasizing the transmission of images and evaluating the impact of Doppler frequency on image quality. The OFDM signals are transmitted over multiple frequency channels, with pilot subcarriers aiding in channel estimation. Accurate channel coefficient estimation is essential, particularly in complex IoT environments such as urban, industrial, and rural settings. The process begins with estimating channel coefficients at pilot subcarriers, followed by filtering to reduce noise and a second estimation for data subcarriers. Given the rapidly fluctuating channels in IoT, the frequency response is assumed to vary linearly, and interpolation techniques help track these variations.A comparative evaluation of channel estimation methods—Least Squares (LS), Minimum Mean Square Error (MMSE), TDLMMSE, and TD Qabs LMMSE—shows that MMSE significantly enhances image transmission quality, especially in scenarios impacted by the Doppler effect. The study specifically examines how Doppler frequency influences the visual quality of transmitted images, revealing that MMSE outperforms other methods like LS, TDLMMSE, and TD Qabs LMMSE in dynamic environments. The results demonstrate that selecting the appropriate estimator, particularly MMSE, is crucial for maintaining high quality image transmission over OFDM in IoT environments affected by Doppler variations.
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