IOT and DSP (combination of hardcore Virtex-5 FPGA and soft core DSP processor) OFDM System PAPR Reduction Using Artificial Intelligence Algorithm
Main Article Content
Abstract
Orthogonal frequency division multiplexing (OFDM) is extensively applied in the downlink of narrowband Internet of Things (IoT). However, the high peak-to-average power ratio (PAPR) of OFDM systems leads to a decrease in transmitter efficiency. Therefore, the researchers proposed the artificial neural network (ANN) based PAPR reduction schemes. However, these schemes have the disadvantages of high complexity or cannot overcome the defects of traditional schemes. In this Synopsis, a novel PAPR reduction scheme based on neural networks (NNs) is proposed for OFDM systems. This scheme establishes a PAPR reduction module based on NN, which is trained using the low PAPR data obtained by the PTS method. To overcome the defect of poor BER performance of the SCF scheme, a recovery module is introduced at the receiver, to recover the distorted signal. To realize the improvement of BER performance and the reduction of PAPR simultaneously, the Virtex-5 two modules are jointly trained based on multi objective optimization.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
Goel, A., & Gupta, S. (2022). Side information embedding scheme for PTS based PAPR reduction in OFDM systems. Alexandria Engineering Journal, 61(12), 11765-11777.
Huang, Y., Ye, Q., Hu, Z., Liu, J., Hu, S., & Zhang, Z. (2022). Partially-Reserved Cyclic Algorithm For OFDMBased RadCom PAPR Reduction. Procedia Computer Science, 202, 436-448.
Azarnia, G., Sharifi, A. A., & Emami, H. (2020). Compressive sensing based PAPR reduction in OFDM systems: Modified orthogonal matching pursuit approach. Ict Express, 6(4), 368-371.
Sengupta, S., & Lande, B. K. (2020). An approach to PAPR reduction in OFDM using Goppa codes. Procedia Computer Science, 167, 1268-1280. 5. Sharifi, A. A. (2019). PAPR reduction of optical OFDM signals in visible light communications. ICT Express, 5(3), 202-205.
Kim, M., Lee, W., & Cho, D. H. (2017). A novel PAPR reduction scheme for OFDM system based on deep learning. IEEE Communications Letters, 22(3), 510-513.
Singh, S., & Kumar, A. (2016). Performance analysis of adaptive clipping technique for reduction of PAPR in alamouti coded MIMO-OFDM systems. Procedia Computer Science, 93, 609-616.
Aghdam, M. H., & Sharifi, A. A. (2019). PAPR reduction in OFDM systems: An efficient PTS approach based on particle swarm optimization. ICT Express, 5(3), 178-181.
Vittal, M. V. R., & Naidu, K. R. (2017). A novel reduced complexity optimized PTS technique for PAPR reduction in wireless OFDM systems. Egyptian informatics journal, 18(2), 123-131.
Sudha, V., & Kumar, D. S. (2018). Low complexity PAPR reduction in SLM-OFDM system using time domain sequence separation. Alexandria engineering journal, 57(4), 3111-3115.
Gao, J., Wang, J., Wang, B., & Song, X. (2011). A PAPR reduction algorithm based on harmony research for OFDM systems. Procedia Engineering, 15, 2665-2669.
Mishra, R. (2024). Raspberry Pi Performance analysis across its Operating System in LED Control Operation. International Journal of Advanced Research and Multidisciplinary Trends (IJARMT), 1(2), 01-11.
Mishra, M. T. S. R., & Bisen, V. (2025). Review on PAPR Reduction and Improvement of OFDM System Performance Using Artificial Intelligence Machine Learning Algorithm.