基于韦伯分布函数的低复杂度变步长符号算法

doi:10.11959/j.issn.1000-0801.2018223

Abstract

Abstract:

The performance of the traditional second-order statistics based channel estimation methods degrade seriously in the presence of impulsive noises.In order to deal with this problem,a Weibull distribution function based variable step-size sign algorithm for channel estimation under impulsive noises was proposed.The proposed method was robust against impulsive noises and it could improve the convergence speed of the sign algorithm with the Weibull distribution function based variable step-size method.Computational complexity analysis and simulation results demonstrate that the proposed algorithm can achieve the same steady-state estimation error with faster convergence speed and lower computational complexity.

Key words: impulsive noise, channel estimation, Weibull distribution function, variable step-size, sign algorithm

Rui ZHANG,Guchen SHI,Banteng LIU,Yourong CHEN. Low-complexity variable step-size sign algorithm based on Weibull distribution function[J]. Telecommunications Science, 2018, 34(9): 87-96.

Figures/Tables 7

算法	步长更新计算式	算法复杂度
DSA^[18]	$μ_{i} = {\begin{matrix} sign (e_{i}), \| e_{i} \| \leq τ \\ η sign (e_{i}), \| e_{i} \| > τ \end{matrix}$	2L+1
APSA^[19]	$μ_{i} = \frac{μ}{\sqrt{sign (e_{i}^{T}) X_{i}^{T} X_{i} sign (e_{i})}}$	(M+3)L
VSSA^[20]	${\begin{matrix} {\hat{p}}_{i} = θ {\hat{p}}_{i - 1} + (1 - θ) s i g n (e_{i}) X_{i} \\ \begin{matrix} \begin{matrix} \begin{matrix} μ_{i} = φ μ_{i - 1} + γ_{s} {‖ {\hat{p}}_{i} ‖}^{2} \end{matrix} \end{matrix} \end{matrix} \end{matrix}$	5L+4
提出算法	$μ_{i} = θ μ_{i - 1} + (1 - θ) \frac{k}{λ} {(\frac{\| e_{i} \|}{λ})}^{k - 1} \exp (- {(\frac{\| e_{i} \|}{λ})}^{k})$	2L+k+5

References 22

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算法	Alpha稳定分布噪声n ～ S (1.2,0,0.1,0)	高斯噪声n ～ S (2,0,0.1,0)
SA^[17]	μ=0.000 5	μ=0.000 5
DSA^[18]	μ₁=0.001、μ₂=0.000 1	μ₁=0.001 5、μ₂=0.000 5
APSA^[19]	μ=0.004、M=10	μ=0.004、M=10
VSSA^[20]	θ=0.995、φ=0.99、γ_s=0.000 1	θ=0.99、φ=0.99、γ_s=0.000 04
提出的算法	k=4、λ=10、θ=0.995	k=3、λ=5、θ=0.99

Low-complexity variable step-size sign algorithm based on Weibull distribution function

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