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Asymptotic Average Mutual Information Over Finite Input Mixture Gamma Distributed Channels

Information Theory 2021-11-29 v1 Signal Processing math.IT

Abstract

This letter establishes a unified analytical framework to study the asymptotic average mutual information (AMI) of mixture gamma (MG) distributed fading channels driven by finite input signals in the high signal-to-noise ratio (SNR) regime. It is found that the AMI converges to some constant as the average SNR increases and its rate of convergence (ROC) is determined by the coding gain and diversity order. Moreover, the derived results are used to investigate the asymptotic optimal power allocation policy of a bank of parallel fading channels having finite inputs. It is suggested that in the high SNR region, the sub-channel with a lower coding gain or diversity order should be allocated with more power. Finally, numerical results are provided to collaborate the theoretical analyses.

Keywords

Cite

@article{arxiv.2111.12822,
  title  = {Asymptotic Average Mutual Information Over Finite Input Mixture Gamma Distributed Channels},
  author = {Chongjun Ouyang and Sheng Wu and Chunxiao Jiang and Yuanwei Liu and Julian Cheng and Hongwen Yang},
  journal= {arXiv preprint arXiv:2111.12822},
  year   = {2021}
}

Comments

5 pages

R2 v1 2026-06-24T07:51:27.201Z