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A Variable Step-Size MSD-Based Diffusion LMS Algorithm With Noisy Input and Quantization Link Noise
DOI:10.1109/LWC.2025.3602184.png)
摘要
En 中文
This letter presents a variable step-size diffusion least-mean-square algorithm that considers both input and quantization noise in digital communication, particularly in wireless sensor networks. Whereas link noise has simply been modeled as additive white Gaussian noise in the previous algorithms, this letter considers uniform quantization effects during weight vector transmission. The proposed combination protocol utilizes mean-square-deviation values to set an upper bound, dynamically adjusting the combination coefficients. As a result, it ensures energy-efficient operation even in low-bit allocation environments. Experimental results indicate that the proposed algorithm surpasses the existing algorithms and maintains performance in changing environments through reset algorithms.
Keyword:
Noise
Quantization (signal)
Vectors
Noise measurement
Signal processing algorithms
Estimation
Wireless sensor networks
Mathematical models
Heuristic algorithms
Signal to noise ratio
Distributed system
adaptive filtering
wireless sensor network
variable step size
input noise
quantization noise
期刊
I
IF:
5.5
论文数:
867
被引数:
0
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暂无机构信息
引用论文
The Performance Analysis of Diffusion LMS Algorithm in Sensor Networks Based on Quantized Data and Random Topology基于量化数据和随机拓扑的扩散LMS算法在传感器网络中的性能分析

