Scholarlink

<p>In wireless multi hop networks, forwarding data packets to their destination through multiple nodes introduces significant delay, which affects real-time performance, easily leads to packet loss and retransmission, and reduces transmission efficiency. Therefore, an EM-MAP-based delay channel state estimation algorithm for wireless multi-hop networks is proposed. A signal transmission model for wireless multi-hop networks is constructed using space–time-frequency coding, and the communication mechanism of delay channels is deeply analyzed with the Nakagami-m fading channel model. Maximum likelihood decoding and Fourier transform array are employed to recover the transmitted signal. Bayesian statistical methods are used to analyze the signal attenuation, transmission bandwidth limitations, and other information present in each hop of the network, combining channel prior information and likelihood energy to infer the posterior probability distribution of channel parameters. To obtain the optimal posterior probability distribution value, the global best estimation parameters are identified through expectation and maximization operations, ultimately yielding the network delay channel state estimation results. Experimental results show that the estimation results obtained by the proposed method exhibit good normalized variance and a high correlation coefficient with the true values.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Delay channel state estimation algorithm for wireless multi-hop networks based on EM-MAP

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月30日

查看全文
  • Yali Zhang,
  • Xiaoli Meng

摘要

In wireless multi hop networks, forwarding data packets to their destination through multiple nodes introduces significant delay, which affects real-time performance, easily leads to packet loss and retransmission, and reduces transmission efficiency. Therefore, an EM-MAP-based delay channel state estimation algorithm for wireless multi-hop networks is proposed. A signal transmission model for wireless multi-hop networks is constructed using space–time-frequency coding, and the communication mechanism of delay channels is deeply analyzed with the Nakagami-m fading channel model. Maximum likelihood decoding and Fourier transform array are employed to recover the transmitted signal. Bayesian statistical methods are used to analyze the signal attenuation, transmission bandwidth limitations, and other information present in each hop of the network, combining channel prior information and likelihood energy to infer the posterior probability distribution of channel parameters. To obtain the optimal posterior probability distribution value, the global best estimation parameters are identified through expectation and maximization operations, ultimately yielding the network delay channel state estimation results. Experimental results show that the estimation results obtained by the proposed method exhibit good normalized variance and a high correlation coefficient with the true values.