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<p>The OFDM system is popular due to its broadband capabilities, but because it employs the multicarrier concept, synchronization issues may arise. These errors are caused by the incompatibility of the transmitted and received signals. The performance of multiple relay cooperative systems is assessed in this study using receiver compensation and estimation of multicarrier frequency offsets (MCFOs) and multiple timing offsets (MTOs). To demonstrate improved bit error rate (BER) performance, MCFOs and MTOs should be treated with less computational complexity. At the receiver end, the maximum likelihood (ML) approach is used to decode data and estimate offsets. The ML approach estimates using the ECM and SAGE algorithms. In terms of BER and SNR after estimation, the SAGE algorithm outperforms the ECM approach. A performance analysis of the estimated time and carrier frequency offsets was performed using the ECM and SAGE algorithms. Furthermore, the statistical percentage difference demonstrates that the maximum probability strategy for compensating the CFO and TO is effective. The statistical percentage difference underscores the effectiveness of compensating CFO and TO through ECM and SAGE algorithm within the maximum likelihood framework.</p>

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Estimating time and frequency under imperfect channel knowledge using ECM and SAGE algorithms in multi-relay cooperative networks

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月3日

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  • Ezhilazhagan Chenguttuvan,
  • Lakshmi Prabha Karuppiah,
  • Karuppanan Sakthisudhan

摘要

The OFDM system is popular due to its broadband capabilities, but because it employs the multicarrier concept, synchronization issues may arise. These errors are caused by the incompatibility of the transmitted and received signals. The performance of multiple relay cooperative systems is assessed in this study using receiver compensation and estimation of multicarrier frequency offsets (MCFOs) and multiple timing offsets (MTOs). To demonstrate improved bit error rate (BER) performance, MCFOs and MTOs should be treated with less computational complexity. At the receiver end, the maximum likelihood (ML) approach is used to decode data and estimate offsets. The ML approach estimates using the ECM and SAGE algorithms. In terms of BER and SNR after estimation, the SAGE algorithm outperforms the ECM approach. A performance analysis of the estimated time and carrier frequency offsets was performed using the ECM and SAGE algorithms. Furthermore, the statistical percentage difference demonstrates that the maximum probability strategy for compensating the CFO and TO is effective. The statistical percentage difference underscores the effectiveness of compensating CFO and TO through ECM and SAGE algorithm within the maximum likelihood framework.