Channel Estimation for OFDM FFT/DWT in Multi-carrier Modulation Used in Wireless Telemedicine

Migdadi, Hassan; Obeidat, H. A.; Anoh, Kelvin; Khatib, Nada Nabil; Noras, James M.; Qahwaji, Rami; Abd‐Alhameed, Raed A.

doi:10.1109/cit/iucc/dasc/picom.2015.160

Cited by 3 publications

(1 citation statement)

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“…Accuracy is the parameter used to measure the reliability of the retrieved images in Telemedicine applications. 18,19 It is estimated using the similarity measure between the transmitted image and the retrieved image at the OFDM receiver. The metrics used for similarity measure are Euclidean distance, mean square error (MSE) and peak signal to noise ratio (PSNR).…”

Section: Validation Of Image Accuracymentioning

confidence: 99%

Enhanced brain image retrieval using carrier frequency offset compensated orthogonal frequency division multiplexing for telemedicine applications

Chitra¹,

Kumaratharan²,

Ramesh³

2018

Int J Imaging Syst Tech

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Wireless technology plays a vital role in the Electronic health (e‐health) applications such as telemedicine and remote patient monitoring. One of the major challenges of telemedicine applications is ensuring adequate quality of service and realizing precise diagnosis. Telemedicine employs image fusion to enhance the quality of medical image for better diagnosis. However, the transmission of medical image needs high data rate and bandwidth. Due to the robustness to multipath fading, high data rate transmission capability, high flexibility, high bandwidth efficiency, and easy implementation using fast Fourier transform, an orthogonal frequency division multiplexing (OFDM) is the suitable technique for medical image transmission in telemedicine applications This paper is focused on improving the quality of the fused brain image transmission over OFDM based telemedicine service using comb type pilot based carrier frequency offset compensation. The simulation results show that the proposed method offers better performance in terms of mean squared error, Euclidean distance, peak signal to noise ratio, bit error rate, carrier to interference ratio, and computational complexity.

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Section: Validation Of Image Accuracymentioning

confidence: 99%