Accurate Asymptotic Characterization of α-κ-μ Shadowed Fading Channel With Application to Secure URLLC

Teng Wu, Jie Zeng*, Neng Ye, Wei Feng, Tiejun Lv

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this letter, we propose a novel characterization method of α - κ - μ shadowed fading channel. For both the single α - κ - μ shadowed random variable (RV) and the sum of independent identically distributed α - κ - μ shadowed RVs, we accurately derive asymptotic closed-form expressions of their probability density functions (PDFs), cumulative distribution functions (CDFs), and moment-generating functions (MGFs) in this method. Moreover, we analyze the secure ultra-reliable and low latency communications (URLLC) in terms of average information leakage (AIL) in the massive multiple-input multiple-output (MIMO) system based on the proposed method. Numerical results of the proposed theory analysis are supported by Monte-Carlo simulations to validate the accuracy of the derivation.

Original languageEnglish
Pages (from-to)1100-1104
Number of pages5
JournalIEEE Communications Letters
Volume27
Issue number4
DOIs
Publication statusPublished - 1 Apr 2023

Keywords

  • Accurate asymptotic characterization method
  • massive multiple-input multiple-output (MIMO)
  • secure ultra-reliable and low latency communications (URLLC)
  • α-κ-μ shadowed fading channel

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