In the present scenario, orthogonal frequency division multiplexing (OFDM) systems are greatly utilized in multimedia applications due to their robustness to frequency selective fading channels. OFDM forms the basis for various wireless standards due to its high data rate achieving potential and high spectral efficiency. Despite these advantages, the challenge faced in implementing OFDM system, is high peak to average power ratio (PAPR) that degrades the system performance. To overcome the problem of PAPR, a modified clipping algorithm is proposed in this paper. In the present scheme, successive peaks are clipped adaptively. The complementary cumulative distribution function (CCDF) and the bit error rate (BER) performance for the present scheme are analyzed. The simulation results reveal that appreciable reduction in PAPR of around 4dB may be obtained in the proposed technique.Keywords-Orthogonal frequency division multiplexing (OFDM), peak to average power ratio (PAPR), complementary cumulative distribution function (CCDF), Clipping.
The improvement of multimedia, biomedical, medical and digital imaging has led to huge amount of data required to represent modern imagery. This requires a large disk space for storage and more time for transmitting from one computer networks to the other. Both are relatively expensive. In the biomedical images, the resolution is also very high. So, the factors like large space for storage, time and high resolution proves the need for images compression. Image compression addresses those problems and gives the solution of reducing the space required to represent biomedical image and then this takes less time to transmission from one computer network to other and it converts high resolution into the low resolution. Biomedical images are in the form of DICOM. In this paper we consider the condition of medical report. If we send the biomedical image of person from one place to other by using the network, then we will perform the compression techniques. In this paper we also perform the inverse transform for encoding or decoding the image. In this paper we propose the predictive compression algorithm with the help of ROI on biomedical images.
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