Experimental evaluation of an OFDM-PWM-based X-ray communication system

Wenxuan Chen; Wenxuan Chen; Yunpeng Liu; Yunpeng Liu; Xiaobin Tang; Xiaobin Tang; Junxu Mu; Sheng Lai

doi:10.1364/OE.415291

1. Introduction

X-ray communication (XCOM) is a type of wireless optical communication technology that uses modulated X-ray beam as the carrier of data transmission. With the advantages of low divergence and high bandwidth, XCOM is considered as the next-generation aerospace communications technology [1]. Previous studies demonstrated that X-ray could penetrate the plasma sheath almost without attenuation [2–4] and may be feasible to eliminate reentry blackout as a communication carrier [5,6]. Moreover, the X-ray beam with energy higher than 10 keV can transmit without attenuation through an environment with an atmospheric pressure below 10⁻¹ Pa [7]. Hence, the XCOM system can potentially provide a stable deep space communication link with high data rates at low power consumption [8].

The data transmission in the XCOM system is achieved through intensity modulation and direct detection (IM/DD). General candidates for data modulation are the single-carrier pulse modulation schemes, such as on–off keying (OOK) modulation and pulse position modulation (PPM). In accordance with the transmission link model of the XCOM system, Zhou et al. [9] studied the relationship between the signal-to-noise (SNR) and bit-error-rate (BER) of the XCOM links with different modulation methods including OOK and PPM. Wang et al. [10] showed that the BER of OOK and PPM is approximately 10⁻⁴ level with 25 kbps communication rate. The single-carrier pulse modulation schemes are the most popular due to their simplicity and low-cost implementation. However, these modulation schemes have severe inter-symbol interference (ISI), which requires complex equalization techniques in systems to reduce the BER. Therefore, the time dispersion of the XCOM system’s channel is a major data rate limit factor.

Multi-carrier modulation has inherent robustness to ISI because the symbol duration is significantly longer than the root-mean-square delay spread of the channel [11,12]. As a result, orthogonal frequency division multiplexing (OFDM) with multilevel quadrature amplitude modulation (M-QAM) promises to deliver very high data rates. For the XCOM system, the grid-controlled X-ray tube is used as the emitter and the grid voltage is regulated to modulate the X-ray emission [13,14]. In OFDM, the time domain signal envelope is utilized to modulate the intensity of the grid voltage of the grid-controlled X-ray tube. However, due to the non-linearity between the grid voltage and the emitted X-ray flux, the grid voltage generally adopts a pulsed voltage signal instead of an arbitrary waveform signal. To address this problem, an improved scheme is used for converting the OFDM signal into a pulse width modulation (PWM) signal prior to the intensity modulation of the grid voltage of the grid-controlled X-ray tube.

In this study, we experimentally demonstrate the X-ray communication at 360 kbps using the 16-QAM-OFDM-PWM scheme. The communication system uses a grid-controlled X-ray tube as X-ray transmitter and a scintillator detector as receiver. During experiments, the BER performances on the data rates as well as the working parameters including the anode voltage and filament current of the grid-controlled X-ray tube are studied.

2. OFDM-PWM based on the XCOM system description

In the XCOM system, the electron flow from the cathode, which is a hot filament, of the grid-controlled X-ray tube needs to pass through the grid. The electric field distribution in front of the cathode can be changed by using the generated OFDM-PWM signal to adjust the grid potential to control the number of electrons bombarding the anode target. Then, the intensity of the emitted X-ray is changed to realize the modulation of X-ray, as shown in Fig. 1(a). The cut-off voltage and the bandwidth of the grid-controlled X-ray tube used in the experiment are 1.107 MHz and −120 V, respectively, as shown in Figs. 1(b) and 1(c), and the energy spectrum of the emitted X-ray is shown in Fig. 1(d).

Fig. 1. The characteristics of the grid-controlled X-ray tube (a) The grid-controlled X-ray tube working principle (b) The relationship between grid voltage and output X-ray flux under different anode voltages, (c) Frequency response of the grid-controlled X-ray tube, (d) The energy spectrum of the X-ray produced by the copper target under the anode voltage of 50 kV.

Download Full Size | PDF

2.1 Principle of the OFDM-PWM scheme

The block diagram of the OFDM-PWM scheme is shown in Fig. 2, where the complex bipolar discrete-time OFDM samples x(k) are first generated using the standard OFDM process as outlined in Refs. [15–18]. The grid voltage control circuit of the grid-controlled X-ray tube cannot be driven by the complex bipolar OFDM signal. A real OFDM signal is generated by constraining the complex vector of the input to the inverse fast Fourier transformation (IFFT) to satisfy Hermitian symmetry. The operands of IFFT are 2N and the output is X. The bipolar OFDM signal can be directly converted into PWM signal without adding DC bias because the grid voltage can be negative.

(1)$$X = [{X_{0,}}{X_1},{X_2},\ldots ,{X_{2N - 1}}],$$

(2)$${X_k} = X_{2N - k}^\ast ,0 < k < N,$$

Fig. 2. Block diagram of the OFDM-PWM

Download Full Size | PDF

The real signal generated by signal X in the time domain after IFFT transformation can be expressed as x[k].

(3)$$x[k] = {X_0} + \sum\limits_{n = 1}^{N - 1} {{X_n}\textrm{exp} \left( {\frac{{\textrm{2}\pi nkj}}{{2N}}} \right) + {X_N}\textrm{exp} (\pi kj) + \sum\limits_{n = N + 1}^{2N - 1} {X_{2N - n}^\ast \textrm{exp} \left( {\frac{{\textrm{2}\pi nkj}}{{2N}}} \right)} } .$$

In addition, a number of samples from the end of the symbol as cyclic prefix (CP) is appended to the start of the symbol. Therefore, instead of x[k], the sequence x_cp[k] is transmitted, where S is the length of the CP.

(4)$${x_{cp}}[N ]= [{x[{2N - S} ], \ldots ,x[{2N - 1} ],x[0 ],x[1 ],x[2 ], \ldots ,x[{2N - 1} ]} ].$$

Each frame of OFDM signal is processed separately. The amplitude of each sampled OFDM signal is converted to obtain the duty cycle of PWM signal between every two OFDM sampled signals, and the duty cycle ω of each PWM signal is given by:

(5)$$\omega = \left|{\frac{{x(n )- {x_{\min }}}}{{{x_{\max }} - {x_{\min }}}}} \right|,$$

Note that, x_min and x_max are the minimum and maximum amplitudes of the OFDM symbols, respectively.

In the OFDM-PWM scheme, the pulse width limit of X-ray depends on the bandwidth of the grid-controlled X-ray tube and detector. Therefore, the generated PWM signal needs to extend by a minimum delay cycle R, see Fig. 3. Since there is a zero protection interval between each frame of OFDM signal generated in the experiment, the minimum delay R = T_z / (N_sub + N_cp) of each PWM signal is added by the protection interval. T_z is the length of the zero protection interval. So the high-level time of OFDM-PWM signal τ is given by the following:

(6)$$\tau = \omega {T_c} + R,$$

where T_c is the OFDM symbol sampling period. The transmitted OFDM-PWM signal cycle is T_s = T_c + R. The OFDM-PWM signal y(t) is given by the following:

(7)$$y(t) = \left\{ {\begin{array}{{c}} C\\ 0 \end{array}} \right.\begin{array}{{c}},\\ , \end{array}\begin{array}{{c}} {0 \le t \le \tau }\\ {0 < t \le {T_s}} \end{array}.$$

Fig. 3. Process of the digital OFDM-PWM generation

Download Full Size | PDF

Algorithm: OFDM-PWM modulation
Inputs:
1) OFDM signal x_cp [k], k ɛ [0, (N_cp + N_sub) - 1] ;
2) Number of subcarriers N_sub;
Initialization:
1: CP length N_cp;
2: The XCOM system bandwidth B;
3: Maximum and minimum OFDM signals in each frame x_max, x_min ;
4: Pulse high level C ;
Iterations:
5: for i = k : k+1 do
6: $\; R = {T_z}\; /\; ({{N_{sub}} + {N_{cp}}} )$, where T_z is the length of the zero protection interval
7: $\omega = \|{({{x_{cp}}[i ]- {x_{min}}} )\; /\; ({{x_{max}}-{-}{x_{min}}} )} \|$
8: $\tau = \omega {T_c}\; + \; {T_z}/({{N_{sub}} + {N_{cp}}} )$, where T_c is the OFDM signal sampling period
9: ${T_s} = {T_c} + {T_z}/({{N_{sub}} + {N_{cp}}} )$
10: for j = 0 : BT_s do
11: $y[j ]= \left\{ {\begin{array}{{c}} {C,\; \; j\; \epsilon \; [{0,\; \tau } ]}\\ {0,\; \; j\; \epsilon \; [{\tau ,\; B{T_s}} ]} \end{array}} \right.$
12: end for
13: end for
Output: The OFDM-PWM signal y(t)

2.2 XCOM channel module

The data transmission in the XCOM system is achieved through IM/DD modulation. To calculate the H(0), the direct view channel model is shown in Fig. 4. X(t) is the radiated light power of the grid-controlled X-ray tube, Y(t) is the output current of MPPC, which includes various additive Gaussian noise N(t) in the transmission process, then the direct view channel model is as follows:

(8)$$Y(t )= h(t )\otimes \eta X(t )+ N(t ).$$

where η is the photoelectric conversion efficiency of the MPPC and h(t) is linear impulse response of the XCOM link including the grid-controlled X-ray tube and MPPC. N(t) is the sum of shot noise and thermal noise at the receiver, which is usually modeled as additive white Gaussian noise [19].

Fig. 4. X-ray communication system line-of-sight channel model

Download Full Size | PDF

In the Fig. 4, φ is the X-ray radiation angle of the grid-controlled X-ray tube, ψ is the incident angle of X-ray on the surface of the MPPC, L is the distance between the receiver and transmitter.

The X-ray transmission process includes geometric attenuation and absorption attenuation. The transmitter and receiver do not move relatively during the experiment, and it can be thought that the X-ray transmission channel is a linear channel. Since X-ray have low wavelength, high photon energy and strong penetrating ability, only the direct impulse response is considered. When the distance between the receiver and transmitter is much larger than the size of the detector, the X-ray radiance E_s can be calculated by the X-ray radiation intensity I_s:

(9)$${E_s} = \frac{{{I_s}}}{{{L^2}}}.$$

Since the grid-controlled X-ray tube generates X-ray by bombarding the anode target with electrons, the X-ray emission mode is cosine distribution by simulation. The emission power of the grid-controlled X-ray tube P_t is:

(10)$${P_t} = 2\pi {I_0}\int_0^{{\theta _{{1 / 2}}}} {{{\cos }^m}(\varphi )} \sin (\varphi )d\varphi ,$$

where m is related to the half power angle Φ_1/2, θ_1/2 is the maximum beam half angle and I₀ is the center radiation intensity of the grid-controlled X-ray tube. The X-ray radiation intensity can be expressed as:

(11)$${I_s}(\varphi ) = \frac{{{P_t}}}{{2\pi \int_0^{{\theta _{{1 / 2}}}} {{{\cos }^m}(\varphi )\sin (\varphi )d\varphi } }}{\cos ^m}(\varphi ),$$

After geometric attenuation and absorption attenuation, the X-ray power at the receiver can be expressed as:

(12)$${P_r} = \frac{{{I_s}(\varphi )A}}{{{L^2}}}{\cos ^2}(\varphi ){\eta _s},$$

where η_s is the X-ray absorption attenuation coefficient in the air channel, and A is the photosensitive area of the MPPC. Therefore, for the channel model established in Fig. 4, we calculate the H(0) of the air channel as following:

(13)$$H(0) = \frac{{{P_r}}}{{{P_t}}} = \frac{{A{\eta _s}\cos (\psi )}}{{2\pi {L^2}\int_0^{{\theta _{{1 / 2}}}} {{{\cos }^m}(\varphi )\sin (\varphi )d\varphi } }}{\cos ^{m + 2}}(\varphi ).$$

The frequency response of the XCOM system and the grid-controlled X-ray tube used in the experiment are measured separately, as shown in Fig. 5. With sinusoidal signals of different frequencies as the input signal of the grid voltage, the frequency response curve is obtained by measuring the power of the MPPC output signal and the X-ray power output of the grid-controlled X-ray tube. The results show that the bandwidth of the XCOM system is 821.14 kHz, and the bandwidth of the grid-controlled X-ray tube is 1.107 MHz.

Fig. 5. Frequency response of XCOM system and channel

Download Full Size | PDF

2.3 Experimental setup

Figure 6 illustrates the architecture of the XCOM system, which is utilized to demonstrate the working principle of the OFDM-PWM scheme in the experiment. The result is compared with the OOK scheme under the same conditions. The transmitter module and the receiver module are shown in the inset of Figs. 6(a) and 6(c), respectively.

Fig. 6. Experimental setup of the OFDM-PWM systems based on the XCOM system. Inset: (a) the grid-controlled X-ray tube, (b) the grid voltage control circuit, and (c) the LYSO Scintillator.

Download Full Size | PDF

The real bipolar 16-QAM-OFDM signals are generated offline by using Hermitian symmetry for IFFT input. Then, the OFDM-PWM signals are generated using the scheme outlined in Section 2.1. The signals are then loaded to the arbitrary waveform generator (RIGOL DG4062) via the LabVIEW 2018 interface, and the voltage of the output signal is 0–10 V. The voltage of the output signal is converted from 0–10 V to −160–0 V by the grid voltage control circuit, as shown in Fig. 6(b). No X-ray emission is observed when the grid voltage is −160 V. X-ray emission occurs when the grid voltage is 0 V. Then, the grid voltage is changed by the output signal of the grid voltage control circuit. In addition, a DC-bias current I_d (RIGOL DP823A) of 1.05–1.15 A and a high voltage V_a applied on the anode of 20–50 kV are added prior to intensity modulation of the grid-controlled X-ray tube.

After passing through the air channel, the OFDM-PWM signals are received by the detector, which consisted of an LYSO scintillator and a multi-pixel photon counter (MPPC) photomultiplier. The LYSO scintillator converts the received X-ray into visible light, and then it is detected by the MPPC (Hamamatsu S13360-3050VE). The effective photosensitive area of MPPC is 3 × 3 mm, and the corresponding spectral range is 320–900 nm. The outside of the scintillator is wrapped with the opaque aluminum foil to avoid the interference of ambient light, and the uncoated side is coupled with the MPPC, as shown in Fig. 6(c).

The detected OFDM-PWM signals are captured using a digital oscilloscope (RIGOL DS1104Z) for further offline processing. The oscilloscope sampling rates are set to 10 Msample/s for OOK and 16-QAM-OFDM-PWM. The captured signals are transmitted to a computer via the LabVIEW 2018 interface to be demodulated and evaluated offline. As a result, we can measure the SNR of the received signal, and then calculate the data rate and BER of the system based on the parameters set in the experiment.

2.4 Post-equalization algorithm based on DBSCAN

Nonlinearities induced by the grid-controlled X-ray tube and the optoelectronic devices can bring detrimental effects in the XCOM systems. For M-QAM modulation signals, serious nonlinearity leads to I, Q phase, and amplitude mismatch of the received data constellation points, leading to the traditional failure of the decision threshold. Different from the traditional hard decision, the nonlinear algorithm in machine learning can classify the data more accurately and reduce the BER in other types of communication cases, such as visible light communication and underwater visible light communication [20–24]. The machine learning method is potential to promote the development of the XCOM.

In the XCOM system, we use a post-equalization scheme on the basis of density-based spatial clustering of applications with noise nonlinear compensation (DBSCAN) algorithm, which is one of the most typical density-based clustering algorithms of machine learning. DBSCAN searches for dense areas and expands the area recursively to find arbitrarily shaped clusters [25].

In this method, each signal point on the received constellation with nonlinear interference (I, Q amplitude mismatch constellation) is clustered by DBSCAN algorithm. According to the clustering results, a new decision boundary can be obtained to balance the nonlinearity of the system.

3. Experiment results and discussion

The XCOM system is built as previously illustrated. Under the condition of air channel, we measure the BER performance of OFDM-PWM by changing the data rate, the distance between the X-ray tube and the detector, and the working parameters of the grid-controlled X-ray tube including anode voltage and filament current. A binary stream of 10,000 bits is tested during the measurement. If there is no error in the stream sent, this is represented as 1 × 10⁻⁴ on the graph. Each OFDM frame is composed of 64 OFDM data symbols, two training symbols (TS) for channel equalization, and two TSs for timing synchronization. In the experiment, the X-ray signal waveforms of OOK and 16-QAM-OFMD-PWM received by the detector are shown in Figs. 7(a) and 7(b), respectively.

Fig. 7. Waveforms of: (a) OOK and (b) 16-QAM-OFMD-PWM (The red waveform is the detected X-ray signal waveform, and the yellow waveform is the output signal waveform of the grid voltage control circuit.).

Download Full Size | PDF

3.1 BER versus data rate

The system distance between the receiver and transmitter is 5 cm, the anode voltage is 50 kV, and the filament current is 1.15 A. Figure 8 shows the comparison of the BER values for 16-QAM-OFDM-PWM and OOK versus data rate. Both modulation schemes show a trend of increasing BER as the data rate increases. The clear open eye as observed in the eye diagram of OOK (inset of Fig. 8) suggests that the XCOM system is capable of transmitting a high data rate. OOK can reach a rate of up to 200 kbps before the BER exceeds the target of the forward error correction (FEC) limit of 3.8 × 10⁻³, and 16-QAM-OFDM-PWM can reach to 360 kbps. High data rate results in low SNR and high BER [9]. Compared with OOK, OFDM-PWM is less affected by the decrease of SNR. For OOK and 16-QAM-OFDM-PWM, the fixed threshold detection method and pulse edge detection method are applied, respectively [17]. Since the information is carried by the pulse width, instead of pulse amplitude as in OOK, thus OFDM-PWM reaches a higher data rate.

Fig. 8. BER of OOK and 16-QAM-OFDM-PWM at different transmission data rates

Download Full Size | PDF

Moreover, the 16-QAM-OFDM-PWM scheme has great BER performance at 50–200 kbps, and it starts to rise substantially after 200 kbps. When the grid voltage of the X-ray tube switches from low to high, a pulse fluctuation higher than the average value of the high voltage is observed, as shown in the red waveform circled in Figs. 7(a) and 7(b). The fluctuation pulse width is between 3 and 5 us. When the data rate increases, the width of a single pulse signal is less than the width of a pulse fluctuation, thereby increasing the BER of the OFDM-PWM.

3.2 BER versus distance

The system data rate is set to 100 kbps, the anode voltage is 50 kV, and the filament current is 1.15 A. Figure 9 shows the BER values of 16-QAM-OFDM-PWM and OOK versus distances between the X-ray tube and the detector. The BER values of the two modulation schemes increase with increasing distance, especially over 15 cm. This phenomenon is contributed by the X-ray intensity attenuation severely by the air channel environment. However, it can be seen that the increasing BER level of 16-QAM-OFDM-PWM is evidently lower than that of OOK at distance range of 1–15 cm. For the OOK scheme, the fixed threshold detection method is applied, which is greatly affected by X-ray intensity attenuation. For the 16-QAM-OFDM-PWM scheme, pulse edge detection method is applied. The influence of X-ray intensity attenuation is limited because the duration of pulse edge is small.

Fig. 9. BER of OOK and 16-QAM-OFDM-PWM at different distances between the transmitter and receiver

Download Full Size | PDF

3.3 BER versus filament current

The system distance between the receiver and transmitter is 5 cm, the anode voltage is 50 kV, and the data rate is 100 kbps. Figure 10 shows the comparison of the BER versus filament current of 16-QAM-OFDM-PWM and OOK. When the filament current increases, the BER of the XCOM system gradually decreases. The eye diagram (inset of Fig. 10) shows that the jitter of the X-ray signal waveform at the receiver increases with the decrease of filament current. Moreover, as the filament current increases to a certain extent, the BER of the system tends to reach a fixed value of 1 × 10⁻⁴. When the filament current is adjusted from 1.09 A to 1.15 A at the transmitter module, the BER of the 16-QAM-OFDM-PWM scheme is better than the OOK scheme, and when the filament current is 1.10 A, the BER of 16-QAM-OFDM-PWM scheme is below the value of 3.8 × 10⁻³. The X-ray flux emitted by the X-ray tube is positively correlated with the filament current at a certain anode voltage, thereby affecting the SNR of the detector. Further increasing the SNR of the detector results in a BER lower than the FEC limited.

Fig. 10. BER of OOK and 16-QAM-OFDM-PWM at different filament current

Download Full Size | PDF

3.4 BER versus anode voltage

The system distance between the receiver and transmitter is 5 cm, the filament current is 1.15 A, and the data rate is 100 kbps. Figure 11(b) shows the relationship between the BER values of 16-QAM-OFDM-PWM and OOK and the anode voltage. The lower anode voltage results in lower X-ray energy emitted, and a larger jitter amplitude of the receiver signal is shown in the eye diagram (inset of Fig. 11(b)). When the anode voltage increases, the BER of the XCOM system sharply decreases and tends to reach a fixed value of 1 × 10⁻⁴ over 45 kV. High anode voltage generates high energy emitted X-ray, which has high penetration coefficient in the air channel. Evidently, the quality of the signal received in the detection section can be improved. As a consequence, the BER of the system is decreased.

Fig. 11. (a) Relationship between the anode voltage and the average voltage of the detector received signal; (b) BER of OOK and 16-QAM-OFDM-PWM at different anode voltage.

Download Full Size | PDF

The measured relationship between the anode voltage and the average voltage of the signal received by the detector is depicted in Fig. 11(a). With the increase in the anode voltage, the average voltage of the received signal at the detector increases, and then tends to reach a fixed value of 20.2 mV. This result is consistent with the trend of the relationship between BER and anode voltage shown in Fig. 11(b).

3.5 BER versus filament current with DBSCAN

To alleviate the influence of nonlinearity on communication performance in the XCOM system, this study explores the relationship between the filament current and BER by using the DBSCAN post-equalization algorithm. In the experiment, the distance between the receiver and the transmitter is 5 cm, the data rate is 100 kbps, and the anode voltage is 50 kV. The verification results are shown in Fig. 12. The comparison of constellations 12(a) and 12(b) in Fig. 12 shows that the system with DBSCAN algorithm reaches the FEC threshold easily. When the filament current I_d is 1.11 A, the BER of the XCOM system with DBSCAN equalization is 4 × 10⁻⁴, and that without DBSCAN is 9 × 10⁻⁴; the improvement in Q-factor is 0.62 dB.

Fig. 12. BER before and after utilizing the DBSCAN algorithm under different I_d

Download Full Size | PDF

4. Conclusion

We study the X-ray communication channel model and experimentally demonstrate the XCOM system by using the OFDM-PWM modulation. The BER performance of the signal at different data rate, distance, filament current, and anode voltage is investigated. The relationship between the BER and the filament current with DBSCAN is further studied to alleviate the nonlinearity of the system. With the grid-controlled X-ray tube and scintillator detector, we achieve the data rate of 360 kbps at a BER of 3.8 × 10⁻³ by using 16-QAM-OFDM-PWM. On the contrary, the data rate is only approximately 200 kbps at the same BER by using OOK. When the anode voltage and the filament current of the grid-controlled X-ray tube are set to 45 kV and 1.15 A, respectively, the BER of the OFDM-PWM XCOM system reaches 1 × 10⁻⁴, which is under FEC (3.8 × 10⁻³). Furthermore, the improvement in Q-factor is 0.62 dB after using the DBSCAN compensation algorithm at 100 kbps and 1.11 A. The results clearly demonstrate the benefit and feasibility of the OFDM-PWM scheme for the XCOM system.

Funding

Chinese Aeronautical Establishment (2018ZC52029); Foundation of the Graduate Innovation Center, Nanjing University of Aeronautics and Astronautics (kfjj20200609); Fundamental Research Funds for the Central Universities.

Disclosures

The authors declare no conflicts of interest.

References

1. National Aeronautics and Space Administration, “NASA Technology Roadmaps TA 5: Communications, Navigation, and Orbital Debris Tracking and Characterization Systems,” https://www.nasa.gov/sites/default/ files/atoms/files/2015_nasa_technology_roadmaps_ta_5_communication_ and_navigation_final.pdf.

2. H. Li, X. Tang, S. Hang, Y. Liu, and D. Chen, “Potential application of X-ray communication through a plasma sheath encountered during spacecraft reentry into earth’s atmosphere,” J. Appl. Phys. 121(12), 123101 (2017). [CrossRef]

3. Y. Li, T. Su, L. Sheng, N. Xu, and B. Zhao, “Simulation and experiment of X-ray communication in re-entry dusty plasma region,” Mod. Phys. Lett. B 34(04), 2050057 (2020). [CrossRef]

4. H. Li, X. Tang, S. Hang, Y. Liu, J. Mu, and W. Zhou, “Re-entry blackout elimination and communication performance analysis based on laser-plasma-induced X-ray emission,” Phys. Plasmas 26(3), 033503 (2019). [CrossRef]

5. M. Kundrapu, J. Loverich, K. Beckwith, P. Stoltz, A. Shashurin, M. Keidar, and A. Ketsdever, “Modeling radio communication blackout and blackout mitigation in hypersonic vehicles,” J. Spacecr. Rockets 52(3), 853–862 (2015). [CrossRef]

6. J. Li, S. Yang, L. Guo, M. Cheng, and T. Gong, “Bit error rate performance of free-space optical link under effect of plasma sheath turbulence,” Opt. Commun. 396, 1–7 (2017). [CrossRef]

7. L. Henke B, M. Gullikson E, and C. Davis J, “X-Ray Interactions: Photoabsorption, Scattering, Transmission, and Reflection at E = 50-30,000 eV, Z = 1-92,” At. Data Nucl. Data Tables 54(2), 181–342 (1993). [CrossRef]

8. NASA Goddard Space Flight Center, “Demonstrating the world’s first x-ray communication system,” https://www.nasa.gov/feature/goddard/2019/nasa-set-to-demonstrate-x-ray-communications-in-space.

9. W. Zhou, X. Tang, Y. Liu, S. Hang, H. Li, J. Mu, P. Dang, and S. Lai, “Power budget and performance analysis of X-ray communication during the Earth re-entry of spacecraft,” Optik 199, 163521 (2019). [CrossRef]

10. L. Q. Wang, T. Su, B. S. Zhao, L. Z. Sheng, Y. A. Liu, and D. Liu, “Bit error rate analysis of X-ray communication system,” Wuli Xuebao 64(12), 120701 (2015). [CrossRef]

11. J. Armstrong, “OFDM for Optical Communications(Invited Tutorial),” J. Lightwave Technol. 27(3), 189–204 (2009). [CrossRef]

12. F. Ahmad, S. Ramachandrapura, J. Manattayil, and V. Raghunathan, “Path-Loss Optimized Indoor Laser-Based Visible Light Communication System for Variable Link Length Gigabit-Class Communication,” IEEE Photonics J. 12(4), 1–12 (2020). [CrossRef]

13. T. Su, L. Tang, Y. Li, L. Sheng, and B. Zhao, “An X-ray frequency modulation method and its application in X-ray communication,” Optik 199, 163263 (2019). [CrossRef]

14. H. Mou and B. Li, “Inter-satellites x-ray communication system,” Second Int. Conf. Photonics Opt. Eng. 10256, 102561W (2017). [CrossRef]

15. J. A. C. Bingham, “Multicarrier Modulation for Data Transmission: An Idea Whose Time Has Come,” IEEE Commun. Mag. 28(5), 5–14 (1990). [CrossRef]

16. H. M. Oubei, J. R. Duran, B. Janjua, H.-Y. Wang, C.-T. Tsai, Y.-C. Chi, T. K. Ng, H.-C. Kuo, J.-H. He, M.-S. Alouini, G.-R. Lin, and B. S. Ooi, “48 Gbit/s 16-QAM-OFDM transmission based on compact 450-nm laser for underwater wireless optical communication,” Opt. Express 23(18), 23302 (2015). [CrossRef]

17. T. Zhang, Z. Ghassemlooy, S. Rajbhandari, W. O. Popoola, and S. Guo, “OFDM-PWM scheme for visible light communications,” Opt. Commun. 385, 213–218 (2017). [CrossRef]

18. Z. Ghassemlooy, F. Ebrahimi, S. Rajbhandari, S. Olyaee, X. Tang, and S. Zvanovec, “Visible light communications with hybrid OFDM-PTM,” 2017 13th Int. Wirel. Commun. Mob. Comput. Conf. IWCMC 2017894–898 (2017).

19. A. Trichili, M. A. Cox, B. S. Ooi, and M.-S. Alouini, “Roadmap to free space optics,” J. Opt. Soc. Am. B 37(11), A184 (2020). [CrossRef]

20. X. Lu, Y. Zhou, L. Qiao, W. Yu, S. Liang, M. Zhao, Y. Zhao, C. Lu, and N. Chi, “Amplitude jitter compensation of PAM-8 VLC system employing time-amplitude two-dimensional re-estimation base on density clustering of machine learning,” Phys. Scr. 94(5), 055506 (2019). [CrossRef]

21. Y. Han, S. Yu, M. Li, J. Yang, and W. Gu, “An SVM-based detection for coherent optical APSK systems with nonlinear phase noise,” IEEE Photonics J. 6(5), 1–10 (2014). [CrossRef]

22. X. Lu, K. Wang, L. Qiao, W. Zhou, Y. Wang, and N. Chi, “Nonlinear Compensation of Multi-CAP VLC System Employing Clustering Algorithm Based Perception Decision,” IEEE Photonics J. 9(5), 1–9 (2017). [CrossRef]

23. X. Lu, C. Lu, W. Yu, L. Qiao, S. Liang, A. P. T. Lau, and N. Chi, “Memory-controlled deep LSTM neural network post-equalizer used in high-speed PAM VLC system,” Opt. Express 27(5), 7822 (2019). [CrossRef]

24. K.-L. Hsu, Y.-C. Wu, Y.-C. Chuang, C.-W. Chow, Y. Liu, X.-L. Liao, K.-H. Lin, and Y.-Y. Chen, “CMOS camera based visible light communication (VLC) using grayscale value distribution and machine learning algorithm,” Opt. Express 28(2), 2427 (2020). [CrossRef]

25. E. Schubert, J. Sander, M. Ester, H. P. Kriegel, and X. Xu, “DBSCAN revisited, revisited: Why and how you should (still) use DBSCAN,” ACM Trans. Database Syst. 42(3), 1–21 (2017). [CrossRef]

Experimental evaluation of an OFDM-PWM-based X-ray communication system

Abstract

1. Introduction

2. OFDM-PWM based on the XCOM system description

2.1 Principle of the OFDM-PWM scheme

2.2 XCOM channel module

2.3 Experimental setup

2.4 Post-equalization algorithm based on DBSCAN

3. Experiment results and discussion

3.1 BER versus data rate

3.2 BER versus distance

3.3 BER versus filament current

3.4 BER versus anode voltage

3.5 BER versus filament current with DBSCAN

4. Conclusion

Funding

Disclosures

References

Cited By

Figures (12)

Equations (13)

Optics Express