Non-stationary Channel Estimation with Diffusion Adaptation Strategies Over Distributed Networks

Mostafapour, Ehsan; Ghobadi, Changiz; Amirani, Mehdi Chehel

doi:10.1007/s11277-017-5190-3

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…Considering the need for beamforming in cell-free networks, which necessitates high-complexity signal processing for tasks like beamforming, we propose a fully distributed beamforming scheme applicable to both radar and cell-free communication networks. Additionally, it is important to note that the concept of one-bit distributed adaptive processing can be extended to other tasks in mobile communication systems, such as channel estimation [23,24], spectrum sensing [25,26], and localization [27][28][29][30]. This implies that a cell-free mobile network can be developed to handle highly complex tasks in a distributed manner using low-resolution one-bit data.…”

Section: Introductionmentioning

confidence: 99%

The one‐bit diffusion for distributed beamforming over cell free wireless networks

Mostafapour,

Ghobadi,

Nourinia

et al. 2023

IET Communications

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This paper presents an investigation into the theoretical performance of diffusion adaptive networks within a distributed beam coordination application in a cell‐free communication network that utilizes coarsely quantized data. This analysis assumed data pulses with 1, 2, and 3 bits, and based on this assumption, simulations and theoretical analyses of distributed beamforming are conducted. The consistency between the simulation results and theoretical findings validated the accuracy of the calculations. Additionally, the distributed quantization aware least mean square (DQA‐LMS) algorithm was introduced for distributed beam coordination, demonstrating its superior performance in scenarios involving coarsely quantized data. Convergence conditions were provided and the results through various simulations were presented, including the array network mean square deviation (MSD), mean square error (MSE), and beamforming diagrams.

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Section: Introductionmentioning

confidence: 99%

The one‐bit diffusion for distributed beamforming over cell free wireless networks

Mostafapour,

Ghobadi,

Nourinia

et al. 2023

IET Communications

Self Cite

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“…However, in diffusion, each node interacts with some nearby nodes, and thus it is more resilient to node failure. Distributed estimation algorithms are extended for channel estimation due to faster convergence and improved steady-state error, but many of the works still incorporate Gaussian assumption [27], [28]. The stochastic gradientbased adaptive algorithm based on the minimization of mean square error (MSE) fails when the communication system deviates from linear and Gaussian assumptions, as in the real world.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Geman-McClure Estimator for Robust Distributed Channel Estimation

et al. 2021

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Communication systems are affected by channel distortions. Impulsive noise is one of the significant factors for channel impairments. The standard additive white Gaussian noise (AWGN) channel model and conventional estimation algorithms like least mean square (LMS) and its variants tend to be ineffective under such conditions. This paper presents a robust adaptive channel estimation algorithm using the Geman-McClure estimator in a diffusion-based distributed network. The analytical study on mean stability and mean square analysis is carried out under two separate noise statistics: Symmetric αstable (SαS) and Bernoulli-Gaussian (BG) distribution. The computer simulations confirm the proposed algorithm's competitive robustness compared to the Maximum Correntropy Criterion and Minimum Kernel Risk Sensitive Loss algorithms at a high impulsive noise environment without exponential cost function. Further, the efficiency is also verified by simulating the bit error rate by designing a minimum mean square error (MMSE) equalizer with the estimated coefficients.

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Convergence Analysis of Diffusion Adaptive Networks Working Through Free Space Optical Communication Channels

Aminfar

Amirani

Ghobadi

2019

Wireless Pers Commun

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Non-stationary Channel Estimation with Diffusion Adaptation Strategies Over Distributed Networks

Cited by 6 publications

References 10 publications

The one‐bit diffusion for distributed beamforming over cell free wireless networks

The one‐bit diffusion for distributed beamforming over cell free wireless networks

Adaptive Geman-McClure Estimator for Robust Distributed Channel Estimation

Convergence Analysis of Diffusion Adaptive Networks Working Through Free Space Optical Communication Channels

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