Wideband Mixed Signal Separation Based on Photonic Signal Processing
Abstract
:1. Introduction
2. Interference Management
2.1. Related Work
2.1.1. Photonic Circuit
2.1.2. Digital System
2.2. Challenges
2.3. Future Perspectives
2.3.1. Ultra-Fast Sampling with Pico-Second Laser Pulse
2.3.2. Separation of Mixed Signal with Progressive Cancellation
- ADC resolution: ADC resolution determines the accuracy of by introducing digitization error. In a completely digital system, the cancellation ratio depends on the ADC resolution in the first stage. In the ill-condition cases, the SOI amplitudes are comparable to the ADC resolution, and the signal information is lost in the first at ADC and cannot be recovered. For example, in an 8-bit ADC system, the digitization error is of the signal peak amplitude. In the first ill-condition case, the received signal peak amplitude is defined by the interference. If the signal is not pre-separated in an analog way, the digitization error is comparable to or larger than the amplitude of the SOI, which causes unsuccessful separation. The analog system is different from the digital system in a way that the analog system maintains all the signal information, and the cancellation ratio in a multi-stage system can be progressively improved.
- Weight tunability: Weight tunability determines the accuracy of The de-mixing matrix is implemented by adding weights to the received signal. By applying multiple stages with coarse and fine adjustment of the weights, the mixed signals can be progressively separated at each stage with the cancellation ratio from each of the stages multiplied.
3. Stealth Communication
3.1. Related Work
3.2. Challenges and Threats to the Existing System
Methods to Address the Threats
- Gaussianity and kurtosis of the signal: Most BSS methods, including the one discussed in Section 2, cannot separate the mixed signals when all the original signals are Gaussian signals. This is because the last step (ICA) is to rotate the mixed signal based on the change of kurtosis at different independent component directions. If both the stealth signal and noise have Gaussian distribution, or Gaussian-like signals (Equations (8) and (9)), the kurtosis is equal to 3 at all the directions, and the mixed signals cannot be rotated to separate the mixed signal. Therefore, the system is immune to BSS attacks when both the stealth signal and noise are Gaussian signals.
- Bandwidth of the signal: The requirement of a Gaussian signal is a strict restriction to the stealth signal since most digital signals are not Gaussian signals. Another means of defending against the BSS attack is to expend the bandwidth of the noise signal. The sampling time must be short enough, so the sampled signal is not a time average of the mixed signal. By using the mode-locked laser to improve the sampling time, mixed signals with a bandwidth of up to 50 GHz can be properly sampled. Bandwidth of 50 GHz is an ultra-wideband for interference management, while for stealth communication with noise applied intentionally, bandwidth beyond 50 GHz can be deployed. Experimental results have demonstrated using noise bandwidth of 150 GHz–5000 GHz to hide signals.
- Linear and nonlinear operation: For interference management, the signals are mixed with linear functions. To hide signals in noise, both linear and nonlinear operations can be applied to mix the signals and noise. Experimental results show that with nonlinear operations, the SOI cannot be identified by the statistical properties of the mixed signals, which means the stealth system with a nonlinear mixing function can effectively defend the BSS attack.
3.3. Future Perspectives
3.3.1. Wireless Stealth Communication and Hybrid with Interference Management
3.3.2. Coexistence of Stealth Channel and Public Channel
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
Symbol | Definition |
---|---|
SOI | Signal of interest |
BSS | Blind source separation |
RF | Radio frequency |
CDMA | Code-division multiple access |
OFDM | Orthogonal frequency-division multiplexing |
PCA | Principal component analysis |
ICA | Independent component analysis |
ASE | Amplified spontaneous emission |
Received mixed signal | |
Mixing matrix | |
Source signal | |
Signal received by Receiver 1, 2 | |
Channel coefficient | |
Added weights for PCA to mixed signal | |
for PCA | |
for PCA | |
Rectangular diagonal matrix for PCA | |
for ICA | |
Added weights for ICA to mixed signal | |
4th order moments (kurtosis) for ICA |
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Interference Bandwidth | Cancellation Ratio |
---|---|
200 MHz | 60 dB |
1 GHz | 36 dB |
3 GHz | 30 dB |
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Qi, Y.; Shi, T.; Wu, B. Wideband Mixed Signal Separation Based on Photonic Signal Processing. Telecom 2021, 2, 413-429. https://doi.org/10.3390/telecom2040024
Qi Y, Shi T, Wu B. Wideband Mixed Signal Separation Based on Photonic Signal Processing. Telecom. 2021; 2(4):413-429. https://doi.org/10.3390/telecom2040024
Chicago/Turabian StyleQi, Yang, Taichu Shi, and Ben Wu. 2021. "Wideband Mixed Signal Separation Based on Photonic Signal Processing" Telecom 2, no. 4: 413-429. https://doi.org/10.3390/telecom2040024