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Communication

Generation of Flat Terahertz Noise by Mixing Incoherent Light Fields

by
Youwen Zhang
1,
Wenjie Liu
2,
Ya Guo
3,
Junbin Liu
2,
Zhiwei Jia
1,*,
Yuehui Sun
2,
Anbang Wang
1,2 and
Yuncai Wang
2,*
1
Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education and Shanxi Province, College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
2
Key Laboratory of Photonics Technology for Integrated Sensing and Communication, Guangdong University of Technology, Ministry of Education, Guangzhou 510006, China
3
School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
*
Authors to whom correspondence should be addressed.
Photonics 2023, 10(7), 778; https://doi.org/10.3390/photonics10070778
Submission received: 29 May 2023 / Revised: 24 June 2023 / Accepted: 3 July 2023 / Published: 4 July 2023
(This article belongs to the Topic Applications of Photonics, Laser, Plasma and Radiation Physics)
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Abstract

:
Terahertz (THz) noise sources play an irreplaceable role in testing THz devices and evaluating THz application systems, and the flatness of their radio frequency (RF) spectra is an important technical parameter. In this paper, a scheme for generating flat THz noise by mixing multiple filtered incoherent light fields is proposed. A theoretical analysis is conducted to investigate the impact of different spectral linewidths and central wavelength differences of incoherent light fields on the noise power and RF spectrum flatness, and an optimized experimental scheme is obtained. The results show that the proposed method can generate a 280–380 GHz flat THz noise signal with an RF spectrum flatness of ±0.5 dB in simulation and ±2.7 dB in our experiments. This article provides an excellent technical solution to the demand for flat THz noise in the THz field.

1. Introduction

Terahertz (THz) waves refer to electromagnetic waves with frequencies ranging from 0.1 to 10 THz [1], and have significant applications in various fields such as communication systems [2,3,4,5], radar imaging [6,7,8,9,10], sensing technology [11,12,13,14], metamaterial absorbers [15,16,17], and military equipment [18,19]. THz noise sources are an essential measurement tool for radar performance testing and receiver demodulation threshold detection [20,21]. In addition, THz noise sources can be widely used to characterize THz components and devices [22,23], evaluate a THz system’s dynamic range and sensitivity [24], analyze gas composition [25], and perform incoherent imaging [26]. Recently, an increasing number of single-frequency THz devices and application systems have been developed and many of them are operating in the 300 GHz band according to the demands of communication and radar [27,28]. For example, Yi et al. reported a photonic source based on stimulated Brillouin scattering for 300 GHz wireless communication [29]. Seo et al. reported fundamental fixed-frequency and voltage-controlled oscillators operating at 346 GHz [30]. Consequently, noise sources in the corresponding frequency band are urgently needed to characterize relevant devices. The noise radio frequency (RF) spectrum flatness is of significant importance, and a flat RF power spectrum distribution can enhance the application of a noise source. For instance, in the measurement of a system with a large dynamic range, the noise with a flat RF spectrum can improve the dynamic accuracy and eliminate the need for tedious calibrations [31].
The existing technical solutions for generating THz noise sources include thermal [32,33], electronic [34,35], and photonic methods [36,37]. Thermal noise sources can generate THz noise with a flat RF spectrum. However, they require low-temperature operating environments, have large volumes, and generate noise with low output power [38]. The electronic method involves utilizing electronic components such as Schottky diodes and transistors to directly generate THz noise. Goncalves et al. generated a 130–170 GHz integrated noise source based on an avalanche silicon Schottky diode in BiCMOS 55 nm [39]. Ehsan et al. used a GaAs Schottky diode to generate a 160–210 GHz noise signal [40]. However, owing to limitations in the operating bandwidth of electronic devices, the output power of electronic noise sources drops to a negligible and unsuitable level in the THz band.
Photonic technology, which breaks the bandwidth bottleneck, is a suitable alternative for generating THz noise. The most direct scheme is the conversion of broadband optical amplifier spontaneous emission (ASE) to a noise signal by using an optical-to-electrical (O-E) converter [41]. However, the noise power is low and the noise RF spectrum is not flat because the optical power is dispersed over a broad frequency band. Song et al. proposed a method for 280–380 GHz noise generation by mixing two wavelength-sliced ASE light fields using a uni-traveling carrier photodiode (UTC-PD), which can significantly improve noise power [42]. However, the noise RF spectrum was very narrow and not flat. In order to cover the frequency range of 280–380 GHz, it is necessary to change the filtering frequency bands multiple times. In our previous work, we proposed and demonstrated a scheme that mixes three incoherent light fields, through which the noise power and bandwidth can be easily controlled and the flatness of the noise RF spectrum can be optimized. A 20–50 GHz noise signal and a 130–170 GHz noise signal were generated [43,44].
In this study, we propose a scheme to generate a THz noise signal in the 280–380 GHz frequency band by mixing seven filtered incoherent light fields. Compared to the previous approach, different numbers of incoherent light fields and theoretical model are used, and the impact of the relative noise power is considered. A theoretical analysis is conducted to investigate the impact of different spectral linewidths and central wavelength differences on the noise power and RF spectrum flatness, and an optimized experimental scheme is obtained. The results indicate that the experiment can generate a 280–380 GHz flat THz noise with an RF spectrum flatness of only ±2.7 dB. Compared with previous noise generation methods, our proposed method has a significant advantage in achieving a noise signal with a broadband and flat RF spectrum. Further work will consider the use of this noise source to characterize the receiver operating at 280–380 GHz to improve the dynamic accuracy and measurement efficiency.

2. Theoretical Principle

First, we simulated the generation of THz noise by mixing incoherent light fields to optimize the scheme for the target band of 280–380 GHz. Incoherent light fields can be converted to electrical noise using an O-E converter based on the square-law characteristic [45]. Given the Gaussian-shaped spectrum incoherent light fields, the RF spectrum of the generated electrical noise signal, sa(f), can be described as [46,47]
S a f = 2 k R 0 ℜ 2 f P 2 m π Λ 1 m e x p − f − ν m − ν m − 1 2 4 Λ 2 + … + 1 m e x p − f − ν m − ν 1 2 4 Λ 2 + e x p − f 2 4 Λ 2
where m is the number of wavelength-sliced incoherent light fields, vm represents the m-th central frequency, Λ represents the spectral full-width at half maximum (FWHM) of incoherent light fields, k represents the maximum power transfer, R0 is the system impedance, ℜ(f) is the responsivity of the frequency characteristics of the O-E converter, and P represents the average optical power. Here, we define the RF spectrum flatness as the difference between the maximum and minimum values of the RF spectrum in the target band 280–380 GHz.
Figure 1 shows the simulation results of THz noise generation achieved by employing different incoherent light field mixing schemes based on Equation (1). Converted from an incoherent light field with a spectral width of 46 nm, as shown in Figure 1a, the noise RF spectrum covers a wide frequency range. The output electrical noise power decreases with an increase in the frequency. Consequently, a very large part of the noise energy is outside of the target band, leading to low noise power. In addition, the RF spectrum flatness is ±2.4 dB.
Figure 1b illustrates the simulation results for the modified scheme of noise generation obtained by mixing two incoherent light fields. Two incoherent light fields with an FWHM value of 0.1 nm are obtained after filtering. The center frequency of the noise RF spectrum depends on the difference between the two central wavelengths and is given as
  f = c / λ 1 − c / λ 2 ,
where c represents the speed of light. According to the calculation results, the central wavelengths are λ1 = 1550.00 nm and λ2 = 1552.64 nm, and the center frequency is f = 330.0 GHz. The simulated RF spectrum shows that most of the electrical noise power can be centered on the center frequency, and the power level is higher than that of an incoherent light field without filtering. However, because the optical spectra are narrow, the RF spectrum is not flat, and the RF spectrum flatness is ±18.2 dB.
Furthermore, a method involving the mixing of multiple incoherent light fields can be used to generate a broadband noise signal with a flat RF spectrum, as shown in Figure 1c. In this manner, the incoherent source is filtered into several light fields with different central wavelengths, and the FWHM of each light field is 0.1 nm. After the calculation, seven filtered light fields are obtained, and the central wavelengths are λ1 = 1550.00 nm, λ2 = 1552.27 nm, λ3 = 1552.42 nm, λ4 = 1552.57 nm, λ5 = 1552.72 nm, λ6 = 1552.87 nm, and λ7 = 1553.02 nm. The central wavelength difference between each pair of incoherent light fields (i.e., λ1 − λ2, λ1 − λ3, λ1 − λ4, …, and λ1 − λ7) determines the corresponding center frequency of the RF spectrum. The beating of the incoherent light field centered at λ1 and the other light fields (λ2, … λ6, and λ7) generates electrical noise with six different center frequencies, resulting in a broadband flat RF spectrum in the 280–380 GHz range, and the RF spectrum flatness is as low as ±0.5 dB. Notably, the incoherent light fields centered at λ2, … λ6, and λ7 will also beat each other and generate noise signals. Nevertheless, these noise signals cover the low-frequency band because the differences between their wavelengths are small, and their frequencies are not in the target frequency band. According to this principle and Equation (1), by adjusting the number and central wavelengths of the filtered incoherent light fields, we can generate electrical noise in any desired frequency range.
To optimize the power and RF spectrum flatness of THz noise generated by seven incoherent light fields mixing, numerical simulation is conducted to investigate the impact of different FWHM values and central wavelength differences on the relative noise power and RF spectrum flatness in the target frequency range. Here, we define the relative power as the ratio of noise power within the target frequency range of 280–380 GHz to the noise power outside the target frequency range. Figure 2a shows the variation in relative noise power as the FWHM value and the difference in central wavelengths among the last six incoherent light fields are changed while keeping the output optical power constant. The simulation results indicate that as the difference in central wavelengths among the last six incoherent light fields increases, the relative power of the noise decreases. Additionally, when the central wavelength difference is within the range of 0.1–0.25 nm, the relative power decreases as the FWHM value increases. However, when the central wavelength difference reaches 0.3 nm, the relative power increases with an increase in the FWHM value. Figure 2b depicts the simulation results for the variation in the RF spectrum flatness of the 280–380 GHz noise. Except for the central wavelength differences of 0.1–0.15 nm, the RF spectrum flatness generally decreases as the FWHM value increases for other central wavelength differences. Considering both the impact of the relative power and the RF spectrum flatness, we chose the incoherent light field with a central wavelength difference of 0.15 nm and an FWHM of 0.1 nm for further experiments. The theoretical relative power in this case is 0.40, and the RF spectrum flatness is 1 dB, which corresponds to ±0.5 dB.

3. Results and Discussion

3.1. Experimental Setup

The experimental setup of the proposed method is shown in Figure 3. First, the incoherent light field generated using the super-luminescent diode (SLD) is decoupled into multiple channels by an optical coupler (OC). Then, multiple optical tunable filters (OTFs) with different central wavelengths are used to filter and shape each channel to obtain multiple Gaussian-shaped spectral light fields with the same FWHM value of 0.1 nm. These filtered light fields are coupled using another OC and amplified using an erbium-doped fiber amplifier (EDFA) to ensure that the output optical power is maintained at 15 dBm. The UTC-PD operating in the frequency range of 280–380 GHz with a DC conversion efficiency of 0.22 A/W (NTT Electronics Corp. IOD-PMJ-13001) [48] then converts the optical noise signal to the electrical domain. To measure the RF spectrum using an electronic spectrum analyzer (ESA), the electrical noise signal from the UTC-PD is down-converted with a diode harmonic mixer. Notably, the ESA used in this experiment is equipped with the B21 module (local-oscillator (LO)/intermediate-frequency (IF) connection for external mixer), and we can measure the THz signals without external LO signals.

3.2. Experimental Results and Analysis

Figure 4 displays the associated experimental results of the optical and RF spectra. First, we generated a noise signal using the SLD without separating into different channels and filtering for comparison. The optical spectrum is shown in Figure 4a. The central wavelength λ1 was 1550.00 nm, and the entire optical spectrum from the SLD was sent to the UTC-PD. To eliminate the impact of the optical power difference, the optical power output into the UTC-PD was maintained at 15 dBm, similar to subsequent incoherent light field mixing schemes. Figure 4b depicts the associated experimental RF spectrum. The output electrical noise power decreased with an increase in the frequency, and the RF spectrum flatness was ±5.6 dB in the 280–380 GHz range. The differences between simulation results and experimental results can be attributed to the non-flat response curve of the UTC-PD and the impact of the internal system noise from the mixer and amplifier.
The noise signal could also be generated by mixing two filtered incoherent light fields with the central wavelengths of λ1 = 1550.00 nm and λ2 = 1552.64 nm, and the FWHM value of the optical spectra was 0.1 nm (Figure 4c). An uneven noise RF spectrum was produced. Figure 4d shows the experimental result obtained using this scheme, and the resulting RF spectrum flatness was ±14.4 dB. As the optical power was identical to that in the aforementioned no-filtering method, the output noise power in this method could center on the frequency of f = 330.0 GHz; however, it attenuated rapidly in higher or lower frequencies, leading to a poor RF spectrum flatness over the frequency range of 280–380 GHz.
Furthermore, the noise signal was generated by mixing seven incoherent light fields. Based on the proposed principle, seven optical spectra with different central wavelengths can be generated, as shown in Figure 4e. Similar to the simulation, the corresponding calculated central wavelengths were λ1 = 1550.00 nm, λ2 = 1552.27 nm, λ3 = 1552.42 nm, λ4 = 1552.57 nm, λ5 = 1552.72 nm, λ6 = 1552.87 nm, and λ7 = 1553.02 nm. The optical power launching into the UTC-PD was identical to 15 dBm in the three approaches, and the FWHM value of the optical spectra was 0.1 nm. The beats between the filtered incoherent light field centered at λ1, and the other six filtered incoherent lights produced six different center frequencies in the RF spectrum. Figure 4f presents the experimental result of the RF spectrum. The spacings between the center frequencies were designed to be identical, and the center frequencies were f1 = 283.75 GHz, f2 = 302.50 GHz, f3 = 321.25 GHz, f4 = 340.00 GHz, f5 = 358.75 GHz, and f6 = 377.50 GHz. Therefore, after the superposition of these frequencies, a flat RF spectrum ranging 280–380 GHz could be achieved, and the corresponding RF spectrum flatness in the experimental result was as low as ±2.7 dB. In terms of the previously mentioned influencing factors, the experimental results agreed well with the simulation results. The comparison of these three sets of experimental results clarifies that seven filtered incoherent light fields can be mixed to optimize the RF spectrum flatness by more than ±2.9 dB in the 280–380 GHz range compared with the scheme of using incoherent light fields without filtering and more than ±11.7 dB compared with the mixing of two filtered incoherent light fields. Moreover, the entire SLD optical spectrum without filtering has an excessively broad bandwidth, and only part of it can be converted to the noise signal in our target frequency band. The electrical noise power level of the seven incoherent light fields scheme is higher than that of the scheme without filtering in the 280–380 GHz range. Table 1 lists the flatness and bandwidth of the THz noise sources reported in recent years.

4. Conclusions

In this study, we have proposed and demonstrated a broadband THz noise generation technique that involves mixing multiple incoherent light fields. A theoretical analysis has been conducted to investigate the impact of different spectral linewidths and central wavelength differences of incoherent light fields on the noise power and RF spectrum flatness. The results obtained show that the proposed method can generate a 280–380 GHz noise signal with an RF spectrum flatness of ±2.7 dB. Compared with the existing noise generation methods, our method has a significant advantage in achieving a broadband and flat RF spectrum. It can characterize 280–380 GHz components and devices such as receivers and amplifiers without tedious calibrations. Moreover, based on our theoretical principle, the central wavelengths of the filtered incoherent light fields can be precisely adjusted to generate a noise signal in different high-frequency bands depending on the demand. We believe that this noise generation method will play a significant role in THz applications in the future.

Author Contributions

Conceptualization, Y.Z., Y.G. and J.L.; methodology, Y.Z., W.L., Z.J. and Y.W.; simulation, Y.Z. and J.L.; validation, Y.Z., Y.G. and J.L.; writing—original draft preparation, Y.Z. and W.L.; writing—review and editing, Z.J., Y.S., A.W. and Y.W.; project administration, Y.W.; funding acquisition, A.W. and Y.W. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (61927811, 61961136002, 61731014, 62150410435, 62275054, 62035009, and 62105233), the Fundamental Research Program of Shanxi Province (202203021221079, 20210302123183, 20210302123185, and 20210302124536), and the Program for Guangdong Introducing Innovative and Entrepreneurial Teams.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new or additional data are available.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Simulation results of optical spectra and RF spectra of noise generation by incoherent light fields: (a) incoherent light field without filtering; (b) two filtered incoherent light fields mixing; (c) multiple filtered incoherent light fields mixing. λ, the central wavelength of the optical spectra.
Figure 1. Simulation results of optical spectra and RF spectra of noise generation by incoherent light fields: (a) incoherent light field without filtering; (b) two filtered incoherent light fields mixing; (c) multiple filtered incoherent light fields mixing. λ, the central wavelength of the optical spectra.
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Figure 2. Simulation results of relative power and RF spectrum flatness: (a) relative power; (b) RF spectrum flatness.
Figure 2. Simulation results of relative power and RF spectrum flatness: (a) relative power; (b) RF spectrum flatness.
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Figure 3. Experimental setup of THz noise generation. SLD, superluminescent diode; OTF, optical tunable filter; OC, optical coupler; EDFA, erbium-doped fiber amplifier; UTC-PD, uni-traveling carrier photodiode; LO, local oscillator; ESA, electrical spectrum analyzer.
Figure 3. Experimental setup of THz noise generation. SLD, superluminescent diode; OTF, optical tunable filter; OC, optical coupler; EDFA, erbium-doped fiber amplifier; UTC-PD, uni-traveling carrier photodiode; LO, local oscillator; ESA, electrical spectrum analyzer.
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Figure 4. Experimental results of optical spectra and RF spectra. Experimental optical spectra: (a) incoherent light field source without separating and filtering; (c) two incoherent light fields mixing; (e) seven incoherent light fields mixing. Experimental RF spectrum: (b) incoherent light field source without separating and filtering; (d) two incoherent light fields mixing; (f) seven incoherent light fields mixing.
Figure 4. Experimental results of optical spectra and RF spectra. Experimental optical spectra: (a) incoherent light field source without separating and filtering; (c) two incoherent light fields mixing; (e) seven incoherent light fields mixing. Experimental RF spectrum: (b) incoherent light field source without separating and filtering; (d) two incoherent light fields mixing; (f) seven incoherent light fields mixing.
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Table
Table 1. Flatness and bandwidth of noise sources in comparison to this work.
Table 1. Flatness and bandwidth of noise sources in comparison to this work.
Flatness
(dB)		Bandwidth
(GHz)		Frequency Range
(GHz)		Ref
±240130–170[39]
±330170–200[40]
±3.5110125–235[35]
±2.515290–305[42]
±2.560260–320[41]
±2.7100280–380This work
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MDPI and ACS Style

Zhang, Y.; Liu, W.; Guo, Y.; Liu, J.; Jia, Z.; Sun, Y.; Wang, A.; Wang, Y. Generation of Flat Terahertz Noise by Mixing Incoherent Light Fields. Photonics 2023, 10, 778. https://doi.org/10.3390/photonics10070778

AMA Style

Zhang Y, Liu W, Guo Y, Liu J, Jia Z, Sun Y, Wang A, Wang Y. Generation of Flat Terahertz Noise by Mixing Incoherent Light Fields. Photonics. 2023; 10(7):778. https://doi.org/10.3390/photonics10070778

Chicago/Turabian Style

Zhang, Youwen, Wenjie Liu, Ya Guo, Junbin Liu, Zhiwei Jia, Yuehui Sun, Anbang Wang, and Yuncai Wang. 2023. "Generation of Flat Terahertz Noise by Mixing Incoherent Light Fields" Photonics 10, no. 7: 778. https://doi.org/10.3390/photonics10070778

APA Style

Zhang, Y., Liu, W., Guo, Y., Liu, J., Jia, Z., Sun, Y., Wang, A., & Wang, Y. (2023). Generation of Flat Terahertz Noise by Mixing Incoherent Light Fields. Photonics, 10(7), 778. https://doi.org/10.3390/photonics10070778

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