Secure and reliable image transmission with PAPR reduction using enhanced SLM over power line communication channels in the presence of impulsive noise
Power Line Communication (PLC) systems offer a promising platform for high-speed data transmission; however, their performance is significantly affected by channel impairments, particularly impulsive noise. This paper proposes a novel approach to improve the security and reliability of image transmi...
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| Published in | Signal, image and video processing Vol. 19; no. 13; p. 1071 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Springer London
01.12.2025
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1863-1703 1863-1711 |
| DOI | 10.1007/s11760-025-04651-1 |
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| Summary: | Power Line Communication (PLC) systems offer a promising platform for high-speed data transmission; however, their performance is significantly affected by channel impairments, particularly impulsive noise. This paper proposes a novel approach to improve the security and reliability of image transmission in PLC environments subject to such disturbances. The proposed method combines a six-dimensional hyperchaotic system with Orthogonal Frequency Division Multiplexing (OFDM) and an enhanced selected mapping (SLM) technique for peak to average power ratio (PAPR) reduction. Performance evaluation using the complementary cumulative distribution function (CCDF) reveals that the proposed Toeplitz-based SLM outperforms conventional SLM methods. Furthermore, the hyperchaotic system is utilized for image encryption, with detailed analysis of its attractors and Lyapunov exponents. Simulation results demonstrate strong performance, with an entropy of 7.9975, a low bit error rate (BER) of
6.34
×
10
-
4
, and PAPR reduced to 0.50 dB using 16-QAM. These metrics confirm the robustness and security of the proposed method for image transmission over noisy PLC channels. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1863-1703 1863-1711 |
| DOI: | 10.1007/s11760-025-04651-1 |