Novel Technique For PAPR and Average Power Reduction In OFDM Scheme

Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation technique that relies on orthogonality feature to increase transmission data rate while enhancing spectral efficiency at the same time. OFDM’s major issue is the high peaks or peak-to-average power ration (PAPR) that introduced due to summation of subcarriers’ signal. Many methods has been proposed to alleviate this issue however some may increase signal average power. In this paper, a new scrambling method using simple XOR operation is proposed for PAPR and average power reduction in OFDM syste

Deep Pipeline Architecture for Fast Fractal Color Image Compression Utilizing Inter-Color Correlation

Fractal compression technique is a well-known technique that encodes an image by mapping the image into itself and this requires performing a massive and repetitive search. Thus, the encoding time is too long, which is the main problem of the fractal algorithm. To reduce the encoding time, several hardware implementations have been developed. However, they are generally developed for grayscale images, and using them to encode colour images leads to doubling the encoding time 3× at least. Therefore, in this paper, new high-speed hardware architecture is proposed for encoding RGB images in a short time. Unlike the conventional approach of encoding the colour components similarly and individually as a grayscale image, the proposed method encodes two of the colour components by mapping them directly to the most correlated component with a searchless encoding scheme, while the third component is encoded with a search-based scheme. This results in reducing the encoding time and also in increasing the compression rate. The parallel and deep-pipelining approaches have been utilized to improve the processing time significantly. Furthermore, to reduce the memory access to the half, the image is partitioned in such a way that half of the matching operations utilize the same data fetched for processing the other half of the matching operations. Consequently, the proposed architecture can encode a 1024×1024 RGB image within a minimal time of 12.2 ms, and a compression ratio of 46.5. Accordingly, the proposed architecture is further superior to the state-of-the-art architectures.©2022 The Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

An Improved Blind Selected Mapping With Decoding Complexity Reduction For Orthogonal Frequency Division Multiplexing System

SLM is a well-known peak-to-average power ratio (PAPR) reduction technique that is capable of effectively reducing the system’s PAPR without distorting the signal. However, SLM causes a data rate loss issue due to the necessity for sending the selected iteration index to the receiver as side-information. To solve this issue, many blind SLM (BSLM) methods have been proposed in the literature. Such BSLM methods embed side-information in either pilot or data signals using phase or energy disparity forms. Hence, the receiver can blindly decode the signals using a maximum likelihood (ML) decoder. In this research, different data-based BSLM schemes with very low decoding complexity are proposed for both QAM and PSK modulation. The proposed BSLM schemes are broken down into three main stages for different system parameters