On the Accuracy of the High SNR Approximation of the Differential Entropy of Signals in Additive Gaussian Noise

被引:0
|
作者
Gohary, Ramy H. [1 ]
Yanikomeroglu, Halim [1 ]
机构
[1] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada
关键词
High-SNR non-coherent capacity; differential entropy; sum and product of random variables; Lebesgue dominated convergence; SUM; COMMUNICATION; CAPACITY;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
One approach for analyzing the high signal-to-noise ratio (SNR) capacity of non-coherent wireless communication systems is to ignore the noise component of the received signal in the computation of its differential entropy. In this paper we consider the error incurred by this approximation when the transmitter and the receiver have one antenna each, and the noise has a Gaussian distribution. For a general instance of this case, we show that the approximation error decays as 1/SNR. In addition, we consider the special instance in which the received signal corresponds to a signal transmitted over a channel with additive Gaussian noise and a Gaussian fading coefficient. For that case, we provide an explicit expression for the second order term of the Taylor series expansion of the differential entropy. To circumvent the difficulty that arises in the direct computation of that term, we invoke Schwartz's inequality to obtain an efficiently computable bound on it, and we provide examples that illustrate the utility of this bound.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] On the Accuracy of the High-SNR Approximation of the Differential Entropy of Signals in Additive Gaussian Noise: Real and Complex Cases
    Gohary, Ramy H.
    Yanikomeroglu, Halim
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2015, 64 (10) : 4845 - 4850
  • [2] Differential Entropy of the Conditional Expectation Under Additive Gaussian Noise
    Atalik, Arda
    Kose, Alper
    Gastpar, Michael
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2022, 70 : 4851 - 4866
  • [3] Gaussian Extremality for Derivatives of Differential Entropy under the Additive Gaussian Noise Flow
    Zhang, Xiaobing
    Anantharam, Venkat
    Geng, Yanlin
    2018 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2018, : 1605 - 1609
  • [4] Approximation of Achievable Rates in Additive Gaussian Mixture Noise Channels
    Duc-Anh Le
    Vu, Hung V.
    Tran, Nghi H.
    Gursoy, Mustafa Cenk
    Tho Le-Ngoc
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2016, 64 (12) : 5011 - 5024
  • [5] On the Accuracy of the Gaussian Approximation for the Evaluation of Nonlinear Effects in OFDM Signals
    Araujo, Teresa
    Dinis, Rui
    2010 IEEE 72ND VEHICULAR TECHNOLOGY CONFERENCE FALL, 2010,
  • [6] Differential Entropy of the Conditional Expectation under Gaussian Noise
    Atalik, Arda
    Kose, Alper
    Gastpar, Michael
    2021 IEEE INFORMATION THEORY WORKSHOP (ITW), 2021,
  • [7] On the Accuracy of the Gaussian Approximation for the Evaluation of Nonlinear Effects in OFDM Signals
    Araujo, Teresa
    Dinis, Rui
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2012, 60 (02) : 346 - 351
  • [8] Dictionary learning for signals in additive noise with generalized Gaussian distribution
    Zheng, Xiaomeng
    Dumitrescu, Bogdan
    Liu, Jiamou
    Giurcaneanu, Ciprian Doru
    SIGNAL PROCESSING, 2022, 195
  • [9] Dictionary learning for signals in additive noise with generalized Gaussian distribution
    Zheng, Xiaomeng
    Dumitrescu, Bogdan
    Liu, Jiamou
    Giurcăneanu, Ciprian Doru
    Signal Processing, 2022, 195
  • [10] Sparse fast Fourier transform for exactly sparse signals and signals with additive Gaussian noise
    Ermeydan, Esra Sengun
    Cankaya, Ilyas
    SIGNAL IMAGE AND VIDEO PROCESSING, 2018, 12 (03) : 445 - 452