在认知无线电网络中以非常低的SNR进行高效的深波波列特高斯马尔科夫普斯特-沙弗基于网络的频谱传感
1Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India.
Sensors (Basel, Switzerland)
|December 11, 2025
概括
一个新的Deep Wavelet循环静止网络增强了认知无线电网络中的频谱传感. 它提高了初级用户在低信号对噪声比率下使用自适应波纹消噪和证据融合的检测精度.
科学领域:
- 无线通信无线通信
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 认知无线电网络 (CRN) 需要强大的光谱传感器来检测主要用户 (PU).
- 低信号噪声比 (SNRs) 对精确的PU检测构成重大挑战.
- 现有的方法与间歇信号和噪声干扰作斗争,违反了标准假设.
研究的目的:
- 提出一种新的深度学习网络,用于CRN中可靠的频谱传感.
- 为了应对在低SNR条件下检测主要用户活动的挑战.
- 在动态环境中提高频谱传感的准确性和效率.
主要方法:
- 一个深波浪网周期静止的独立高斯马尔科夫里埃变换Dempster-Shafer网络被开发.
- 一个自适应的连续波段旋转静止断解自编码器 (ACWC-DAE) 被集成到一个深度Q网络 (DQN) 中,用于信号恢复和噪声分离.
- 适应高斯短时间里埃变换Dempster-Shafer模型 (AGSTFT-DSM) 被纳入第二个DQN层,用于状态跟踪和证据融合.
主要成果:
- 拟议的模型实现了97.8%的高检测精度.
- 它表现出较低的错误率和快速检测时间30.10 ms.
- 该网络有效地恢复了爆发信号,并将不确定的证据合并为可靠的检测.
结论:
- 适应波纹无声化和不确定性意识的证据融合对于可靠的频谱检测至关重要.
- 拟议的网络在低SNR环境中显著优于现有模型.
- 这种方法为增强认知无线电网络的频谱传感能力提供了一种新的解决方案.
相关概念视频
Downsampling
575
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
575
¹³C NMR: ¹H–¹³C Decoupling
1.7K
The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
1.7K
Upsampling
568
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
568
Aliasing
523
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
523
Linear Approximation in Frequency Domain
329
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
329
Bandpass Sampling
457
In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
457


