Joint communication and radar sensing functions system based on photonics at the W-band

Yanyi Wang; Jiaxuan Liu; Junjie Ding; Mingxu Wang; Feng Zhao; Feng Zhao; Jianjun Yu; Jianjun Yu

doi:10.1364/OE.449153

1. Introduction

By 2030 and the future, human society will enter the era of artificial intelligence. The immersive and interactive experience, smart medical care with real-time human body sensing, and autonomous driving will be applied on a large scale and become a reality. The leap from “Internet of Everything” will be realized by 6G to “Intelligent Connection of Everything. This provides a link between the real physical world and the virtual digital world and helps human society realize the “Intelligent Connection of Everything” [1–5]. Higher frequency bands will be used in future 6G systems, such as millimeter waves (mm-wave). The integration of mm-wave-based communication and radar sensing functions is considered a key technology for promoting smart cities and industries, and the internet of things in the future [6,7]. As an example of application scenarios, a joint communication, and radar sensing functions system based on photonics at W-band for the future smart cities is shown in Fig. 1. In this scenario, the available bandwidth is 35 GHz, the functions of communication and radar are simultaneously implemented by using different bandwidths but designed for different application purposes. For example, high-speed communication is applied to populated places, augmented reality (AR), 8k high-definition video, and so on. Radar sensing is used in environmental monitoring, intelligent robots, intelligent transportation, and so on.

Fig. 1. The concept of joint communication and radar sensing functions system for the smart city.

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Photonics-based mm-wave communication [8–15] is the most popular method at present in the practical application of mm-wave communication, which overcomes the bottleneck of the deployed electrical devices. Recently, numerous excellent researches have been reported on mm-wave communication using photonics-based methods. By involving polarization multiplexing with multiple-input multiple-output (MIMO) technology [10], over 100 Gbit/s transmission rate is demonstrated. To further enhance the system performance, probabilistic shaping (PS) has been introduced [11,12]. Through optical single sideband (SSB), the fiber chromatic dispersion (CD) is overcome [13]. At the offline digital signal processing (DSP) side, the artificial neural network (ANN) structure is introduced to compensate for the nonlinear and linear impairments [14]. Beyond 1 Tbit/s transmission data rate has been achieved by introducing advanced DSP techniques, including PS, Nyquist shaping, and look-up-table algorithm [15]. Unfortunately, the above-mentioned scheme only realizes the function of mm-wave communication.

In the practical application of radar sensing, photonics-based radars [16–22] can simply break through the bandwidth limitation of electronic systems and generate ultra-broadband radar signals. Hence, the range resolution is increased by an order of magnitude. A bandwidth of 8 GHz linear frequency modulation (LFM) signal is achieved by introducing photonic frequency quadrupling technology [16]. To extend radar array size, the MIMO radar architecture is introduced [17]. The logic-operation-based photonic digital-to-analog converter is introduced [18] to generate an LFM signal with a large time-bandwidth product. The real-time inverse synthetic aperture radar is achieved [19]. Meanwhile, to realize a multifunction system, polarization division multiplexing is introduced [20]. The ultra-bandwidth LFM pulses are generated in Ref. [21,22]. However, the above-mentioned scheme only realizes the function of radar sensing.

The integration of radar and communication in a single system has numerous advantages such as achieving hardware reuse, reducing signaling costs, and improving the efficiency of the system. Unfortunately, there have been only a few reports so far on joint communication and radar sensing functions systems. A joint data communication and radar sensing functions system was proposed [23], based on the photonics-aided scheme. Here, the function of our model called ‘sensing’ is not realized without the recognition of echo signals. In Refs. [24–26], a unified communication and radar sensing functions system using photonics technology is proposed. Unfortunately, the communication rate is relatively low. In this paper, we propose a novel joint communication and radar sensing functions system based on photonics. At the transmitting side, by heterodyning two free-running external cavity lasers (ECLs), the LFM signal integrated M-quadrature amplitude modulation (MQAM) signals are generated. At the receiving side, part of the generated signal is captured by a W-band horn antenna (HA) for the communication function, and then down-converted into an intermediate frequency (IF) band with the aid of a W-band mixer. After a series of DSP, the M-QAM signal is recovered. For the radar sensing function, the echo signal is first down-converted into IF band and then applied to a Mach-Zehnder modulator (MZM) operating at its minimum transmission point (MITP) to modulate continuous-wave (CW) light [16]. The CW light is obtained by a polarization maintaining-optical coupler (PM-OC). The modulated signal from the MZM couples with the reference optical signal for de-chirping. Thus, high-resolution radar sensing and high-speed communication functions can thus be achieved. In this paper, radar sensing with a cm-scale range resolution is realized, while a communication rate of 78 Gbit/s is realized at the same time. To the best of our knowledge, it is for the first time to realize the integration of high-speed data communication and high-resolution radar sensing functions at W-band.

2. Principle

Figure 2 presents the schematic of our proposed photonics-based joint communication and radar sensing functions system. We integrate an upper sideband (USB) MQAM and a double-sideband (DSB) LFM signals by frequency division multiplexing (FDM). By employing Hilbert transform phasing techniques to remove the real cosine or sinusoidal source’s negative or positive spectrum, the baseband single-sideband (SSB) signal is obtained. Then, the baseband SSB signal is mixed with a complex sinusoidal radio frequency (RF) signal, we can get an IF USB signal. The baseband LFM signal is mixed with another complex sinusoidal RF signal to obtain a DSB LFM signal. These processes are completed in MATLAB programming. The FDM-based signal is generated by MATLAB programming and then uploaded into an arbitrary waveform generator (AWG), as shown in Fig. 2(a). The instantaneous frequency of the LFM signal can be expressed as ${f_{IF}}(t) = {f_0} + kt$, ${f_0}$ represents the initial frequency and $k$ is the chirp rate. According to [27], k is expressed as

(1)$$k = \frac{B}{T}.$$

in which $B$ is the bandwidth, and T denotes the temporal width. The USB MQAM signal can be stated as

(2)$${\textrm{S}_E}(t) = A{e ^{j2\pi {f_s}t}}.$$

where ${f_s}$ denotes the sideband frequency of the USB carrier. $A$ is a complex parameter and defined as M-quadrature amplitude modulation (MQAM) data, including quadrature phase-shift keying (QPSK), 16 quadrature amplitude modulation (16QAM), and 64 quadrature amplitude modulation (64QAM) formats, and so on.

Fig. 2. The schematic of photonics-based joint communication and radar sensing functions system. AWG: arbitrary waveform generator, ECL: external cavity laser, PM-OC: polarization maintaining-optical coupler, PD: photodiode, HA: horn antenna, ELO: electrical local oscillator, MZM: Mach-Zehnder modulator, OSC: oscilloscope, LFM: linear frequency modulated, MQAM: M-ary quadrature amplitude modulation. (a) is the electrical spectrum of the FDM-based signals, (b)-(d) are the optical spectra at different positions.

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A CW light from an external cavity laser (ECL1) is first split by a 3-dB coupler. One part of the light is modulated by the FDM-based signal in the I/Q modulator. The other part of the light is modulated by the echo signal in MZM. We obtain the optical field at the output of the I/Q modulator as

(3)$${E_{I/Q}}(t) \propto {J_0}({m_0}){J_1}({m_1})[A{e^{j2\pi ({f_{c1}} + {f_s})t + j{\varphi _1}(t)}} + {e^{j2\pi ({f_{c1}}\textrm{ + }{f_{IF}})t + j{\varphi _1}(t)}} + {e^{j2\pi ({f_{c1}} - {f_{IF}})t + j{\varphi _1}(t)}}].$$

where ${m_i}(i = 0,1)$ is the modulation index of the inserted sub-MZM in the I/Q modulator, and ${J_n}(n = 0,1)$ denotes the first kind of n-order Bessel function, ${f_{c1}}$ shows the frequency of the optical carrier and ${\varphi _1}(t)$ denotes the phase of the optical carrier, which is generated by ECL1. Subsequently, we use an optical filter to select the upper or lower path optical signals after the I/Q modulator. According to Fig. 2(b) and Fig. 2(c), the chosen upper and lower path optical signals are obtained

(4)$${E_{\textrm{upper}}}(t) = \textrm{A}{J_0}({m_0}){J_1}({m_1}){e ^{j2\pi ({f_{c1}}\textrm{ + }{f_s})t + j{\varphi _1}(t)}}\textrm{ + }{J_0}({m_0}){J_1}({m_1}){e ^{j2\pi ({f_{c1}} + {f_{IF}})t + j{\varphi _1}(t)}}$$

(5)$${E_{lower}}(t) = {J_0}({m_0}){J_1}({m_1}){e ^{j2\pi ({f_{c1}} - {f_{IF}})t + j{\varphi _1}(t)}}.$$

In the lower path, the left sideband of the LFM signal is utilized as a reference for radar sensing. The upper path optical signal which is integrated with the MQAM signal and the right sideband of the LFM signal beats with an optical local oscillator (OLO) in photodiode (PD1). Through the ECL2, the OLO is generated as presented in Fig. 2(d). The output of PD1 can be written as

(6)$$\begin{aligned} {I_{PD1}}(t) &= 2R\{ A{J_0}({m_0}){J_1}({m_1})\cos [2\pi ({f_{c1}} + {f_s} - {f_{c2}})t + {\varphi _1}(t) - {\varphi _2}(t)]\\ \textrm{ } &+ {J_0}({m_0}){J_1}({m_1})\cos [2\pi ({f_{c1}} + {f_{IF}} - {f_{c2}})t + {\varphi _1}(t) - {\varphi _2}(t)]\\ \textrm{ } &+ A{J_0}{({m_0})^2}{J_1}{({m_1})^2}\cos [2\pi ({f_{IF}} - {f_s})t]\\ \textrm{ } &+ 1/2 + 1/2{A^2}{J_0}{({m_0})^2}{J_1}{({m_1})^2} + 1/2{J_0}{({m_0})^2}{J_1}{({m_1})^2}\} . \end{aligned}$$

where ${f_{c2}}$ represents the frequency of the CW light and ${\varphi _2}(t)$ denotes the phase of CW light, which is generated by ECL2, and $R$ denotes the PD sensitivity. The mm-wave LFM signal and MQAM signals are simultaneously generated at the frequency of ${f_{c1}} - {f_{c2}}$ in Eq. (6). Through an HA1, the generated mm-wave signal is emitted to free-space transmission. Part of the mm-wave signal is received by the communication receiver. The MQAM signal is recovered after a series of DSP processing. The mm-wave signal is also reflected by the target. Obviously, in the radar sensing function, the LFM signal is only considered. The echo signal from the target is collected by radar receive antenna given as

(7)$${S_{R1}}(t) \propto R{J_0}({m_0}){J_1}({m_1})\cos [2\pi ({f_{c1}} + {f_{IF}} - {f_{c2}}\textrm{ + }k\tau )t + {\varphi _1}(t) - {\varphi _2}(t)].$$

where $\tau$ denotes the time delay of the reflected signal. Then, the reflected echo signal is down-converted into the IF domain. After down-converting, the MZM biased at MITP is driven by the IF echo signal. The CW light from ECL1 is modulated by the IF echo signal, which can be written as

(8)$$\begin{aligned} {E_{MZM}}(t) &\propto R{J_0}({m_0}){J_1}({m_1}){J_1}({m_2})\{ \cos [2\pi (2{f_{c1}} + {f_{IF}} - {f_{c2}} - {f_{ELO1}} + k\tau )t + 2{\varphi _1}(t) - {\varphi _2}(t) + {\varphi _3}(t)]\\ &+ \cos [2\pi ({f_{c2}} + {f_{ELO1}} - {f_{IF}} - k\tau )t + {\varphi _2}(t) + {\varphi _3}(t)]\} . \end{aligned}$$

where ${m_2}$ is the modulation index of the MZM, ${f_{ELO1}}$ denotes the frequency of the electrical local oscillator (ELO1), and ${\varphi _3}(t)$ is the phase of ELO1. Subsequently, the modulated signal is coupled the reference optical from the optical filter by a 3-dB coupler, which is given by

(9)$$\begin{aligned} {E_{OC3}}(t) &= R{J_0}({m_0}){J_1}({m_1}){J_1}({m_2})\{ \cos [2\pi (2{f_{c1}} + {f_{IF}} - {f_{c2}} - {f_{ELO1}} + k\tau )t\ldots \\ \textrm{ } &+ 2{\varphi _1}(t) - {\varphi _2}(t) + {\varphi _3}(t)]\\ \textrm{ } &+ \cos [2\pi ({f_{c2}} + {f_{ELO1}} - {f_{IF}} - k\tau )t + {\varphi _2}(t) + {\varphi _3}(t)]\} \\ \textrm{ } &+ {J_0}({m_0}){J_1}({m_1}){e^{j2\pi ({f_{c1}} - {f_{IF}})t\textrm{ + }{\varphi _1}(t)}}. \end{aligned}$$

Then, the optical signal is sent to another PD2 for de-chirped. The de-chirped signal with a frequency of ${f_{c1}} - {f_{c2}} - {f_{ELO}}_1 + k\tau + {\varphi _1}(t) - {\varphi _2}(t) - {\varphi _3}(t)$ can be obtained followed by de-chirping processing. Another de-chirped signal is obtained by moving the target to another position with a frequency of ${f_{c1}} - {f_{c2}} - {f_{ELO}}_1 + k\tau ^{\prime}\textrm{ + }{\varphi _1}(t) - {\varphi _2}(t) - {\varphi _3}(t)$. The distance difference between two positions can be obtained by calculating the frequency difference $\Delta f$ between the two positions as

(10)$$d = \frac{{c\Delta \tau }}{2} = \frac{{c\Delta f}}{{2k}}.$$

where c represents the velocity of light. The range resolution of the radar can be expressed as [27],

(11)$${\delta _r} = \frac{c}{{2B}}.$$

By our proposed architecture, communication and radar sensing functions can be simultaneously achieved. It will have huge application potential in the future 6G.

3. Experiment and results

Figure 3 represents the experimental setup of our proposed joint communication and radar sensing functions system. The ECL1 (Agilent N7714A) works at 1550.32-nm with a linewidth of 100 KHz. Then the CW light generated by ECL1 is subsequently divided into two paths through a 50:50 PM-OC1. One part of the CW light is modulated by an I/Q modulator, with a 3-dB optical bandwidth of 40 GHz. The 7.5-GHz USB signal carrying 15-Gbaud QPSK transmitted data and the 17.5-GHz LFM signal with a bandwidth of 5 GHz are generated via offline MATLAB programming. The QPSK waveform is pulse-shaped with a root-raised-cosine filter with a roll-off factor of 0.2. The USB QPSK and the DSB IF-LFM signals are FDM. The FDM-based signal electrical spectrum is presented in Fig. 4, which is generated by the MATLAB process. The FDM-based signal is then converted into an analog signal using an AWG having a sampling rate of 64 GSa/s. Subsequently, FDM-based signals are amplified by two parallel electrical amplifiers (EAs) to drive the I/Q modulator. Figure 5 represents the measured optical spectrum of the modulated signals after the I/Q modulator. As described above, we used an optical interleaver (IL) with a frequency space of 50 GHz to divide the modulated signals into upper and lower paths, for which the measured optical spectra are displayed in Fig. 6(a) and (b), respectively. The upper path optical signal is amplified by an EDFA and then coupled with ECL2 at a wavelength of 1550.93 nm by PM-OC2 prior to PD1. The ECL2 (Agilent N7714A) works as an OLO. The frequency spacing between optical carrier and OLO is 77 GHz, which is located at W-band. The W-band LFM signal and MQAM format signal are simultaneously obtained by optical heterodyne beating at the output of PD1. We adopt an additional attenuator (ATT) before the PD1, whose 3-dB bandwidth is 100 GHz. A gain of 20 dB power amplifier (PA) is adopted before wireless transmission. A 25 dBi gain HA1 is adopted to deliver the W-band signal.

Fig. 3. The experimental setup. AWG: arbitrary waveform generator, ECL: external cavity laser, EA: electrical amplifier, PM-OC: polarization maintaining-optical coupler, IL: interleaver, PM-EDFA: polarization-maintaining erbium-doped fiber amplifier, ATT: attenuator, PD: photodiode, HA: horn antenna, ELO: electrical local oscillator, PA, power amplifier, MZM: Mach-Zehnder modulator, OSC: oscilloscope.

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Fig. 4. The electrical spectrum of the generated FDM-based signal.

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Fig. 5. Optical spectrum (0.01-nm resolution) after I/Q modulator, which is composed with USB MQAM and DSB LFM signal.

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Fig. 6. Optical spectra (0.01-nm resolution) after IL, (a) upper path optical signal, (b) lower path optical signal.

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For the communication signal transmission and reception, part of the generated W-band signal is emitted into a 1-m wireless link. The W-band signal is captured by another HA2 and down-converted into the IF domain, at the communication receiver side. The ELO2 operates at 75 GHz. Then, the IF signal is fed into an oscilloscope (OSC), with a sampling rate of 100 GHz and 3-dB bandwidth of 33 GHz. The subsequent DSP processing includes down-conversion, orthogonalization, constant modulus algorithm equalization, frequency offset estimation, and carrier phase estimation [28].

For the radar sensing, the generated W-band signal is reflected by the target, and the echo signal is received by a radar receive antenna, with a gain of 25 dBi. The received echo signal is appropriately amplified by another PA. Then, the received echo signal is down-converted into the IF band by a W-band mixer and an 83.5-GHz sinusoidal RF source. After down-converting, the echo signal is amplified by an EA with 25-dB gain before driving the MZM, with a 3-dB bandwidth of 40 GHz. Another part of the light of the ECL1 is modulated by the echo signal. After the MZM, the modulated signal beats with the reference optical signal by the PD2. Here, the 3-dB bandwidth of the PD2 is 15 GHz. Ultimately, the electrical signals are captured by an OSC. After de-chirping processing, the radar sensing function can be realized.

3.1 High-speed communication

To explore the performance of communication function in the joint communication and radar sensing functions system, we first investigate the 16QAM modulated signal. Figure 7(a) displays the calculated spectrum of IF signals detected by OSC wireless transmission for 1 m. From Fig. 7(a), the 16QAM modulated signal and LFM signal are captured.

Fig. 7. (a) Captured IF signals spectrum after OSC fo16QAM modulated signal and LFM signal. (b) BER versus input power into PD for the 16QAM modulated signal.

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The transmit power is certain for the transmitted signal. Considering the tradeoff between communication rate and radar resolution. At the transmitting end, the transmit power ratio must be balanced between the LFM signal and the communication signal. In our experiment, the transmit power ratio between the LFM signal and communication signal is 3:1. Figure 7(b) gives the measured bit error rate (BER) performance versus the input power into the PD. As seen in Fig. 7(b), for both 14-Gbaud and 15-Gbaud 16QAM cases, the BER can reach the soft-decision forward error correction (SD-FEC) threshold of 2.4 × 10⁻².

The 64QAM signal is performed to further explore the high-speed communication rate. From Fig. 8(a), the W-band signal is captured after 1m wireless transmission. Figure 8(b) displays the measured BER performance versus the input power into the PD. Based on the measured BER results, the SD-FEC threshold of 2.4 × 10⁻² can be met by the 9-Gbaud, 11-Gbaud, and 13-Gbaud 64QAM signals when the optical power into PD is higher than −2 dBm. A communication rate of up to 78 Gbit/s is obtained at this point.

Fig. 8. (a) Captured IF signals spectrum after OSC for 64QAM modulated signal and LFM signal. (b) BER versus input power into PD for the 64QAM modulated signal.

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The high-order modulation format would be a good solution for the future communication system. To explore the high-order modulation format, we consider the 128QAM signal. After 1-m wireless transmission, the W-band signal is captured, as shown in Fig. 9(a). The measured BER performance versus the input power into the PD is displayed in Fig. 9(b). As seen in Fig. 9(b), for 4-Gbaud, 6-Gbaud, and 8-Gbaud 128QAM cases, the BER can reach the SD-FEC threshold of 2.4 × 10⁻². This indicates in the joint communication and radar sensing functions system. The high-order modulation format is successfully transmitted.

Fig. 9. (a) Captured IF signals spectrum after OSC for 128QAM modulated signal and LFM signal. (b) BER versus input power into PD for the 128QAM modulated signal.

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3.2 Radar sensing

In this section, we explore the performance of the radar sensing function. The system parameters are summarized in Table 1. The minimum detectable power of our radar was about −35 dBm, which is suitable for the detection of weak signals.

Table 1. System parameters

View Table

The phase noise of transmitted mm-wave signal is measured by a spectrum analyzer (Agilent E4407B) and presented in Fig. 10.

Fig. 10. Phase noise of the transmitted mm-wave signal.

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A distance measurement experiment is implemented. According to session II, we first put a static metal target at 1-m away from the TX side as the reference position. This reference position is utilized to calibrate the range of the target. The de-chirped signal is sampled by OSC. The spectrum of the signal can be achieved by performing a fast Fourier transform (FFT), as presented in Fig. 11. The spectral peak with a signal-to-noise ratio (SNR) of 18 dB located at 6.8 GHz is termed peak1 corresponding to the reference position. Then, we the put metal target 20 cm away from the reference position. By performing FFT, another spectral peak located at 6.2 GHz is obtained, as shown in Fig. 11. Based on Eq. (10), the distance difference between the reference position and target can be calculated as 18 cm.

Fig. 11. Spectra of the de-chirped echo for the reference position and 20 cm away from the reference position.

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At last, the metal target is set at a distance of 40 cm away from the reference position. Figure 12 represents the corresponding spectra. Similarly, the distance difference between the reference position and target can be calculated as 39 cm. There is a measurement error of 1 cm, compared to the actual distance difference value (40cm).

Fig. 12. Spectra of the de-chirped echo for the reference position and 40 cm away from the reference position.

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The theoretically SNR of the target can be expressed as

(12)$$\textrm{SN}{\textrm{R}_{t\arg et}} = \frac{{{P_\textrm{t}}{G^2}{\lambda ^2}\sigma }}{{{{\textrm{(}4\mathrm{\pi )}}^\textrm{3}}{k_\textrm{B}}{T_\textrm{0}}BFLR_\textrm{D}^4}}.$$

where ${P_\textrm{t}}$ is the transmitted power, G is antenna gain, $\lambda$ is the wavelength, $\sigma$ is the cross-sectional area, ${k_\textrm{B}}$ is Boltzmann constant, ${T_\textrm{0}}$ is room temperature, $F$ is noise figure, $L$ is path loss, and ${R_\textrm{D}}$ is the distance, respectively. In our experiment, $\sigma$ is equal to 0.02 m2, $F$ is 12 dB, $L$ is 3 dB, and ${R_\textrm{D}}$ is 1 m. Thus, the theoretical SNR of the target is 22.1 dB. The observed SNR of ∼18 dB is close to the theoretical SNR.

4. Conclusion

In the present work, we have proposed and demonstrated a novel joint communication and radar sensing functions system based on photonics. With the aid of photonics, the MQAM signal and LFM signal are simultaneously generated. Benefiting from photonics technology, the radar possesses a large operation bandwidth, enabling high-resolution radar in range. The feasibility of the integrated communication and radar sensing functions is verified by the experimental result the capability for high-speed communication and high-resolution radar sensing are confirmed. In the experiment, a communication rate of 78 Gbit/s and a radar with a 5-GHz bandwidth are demonstrated. Two different distances are detected successfully. It is believed that the proposed system is expected to be promising in future 6G communications.

Funding

National Natural Science Foundation of China (61720106015, 61805043, 61835002, 61935005, 62127802, 91938202).

Disclosures

The authors declare no conflicts of interest

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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Transmitted power	8 dBm
Antenna Gain	25 dBi
Target reflectance	80%
Range resolution	3 cm
Bandwidth	5 GHz
Temporal width	10 ns
Carrier frequency	94.5 GHz

Joint communication and radar sensing functions system based on photonics at the W-band

Abstract

1. Introduction

2. Principle

3. Experiment and results

3.1 High-speed communication

3.2 Radar sensing

4. Conclusion

Funding

Disclosures

Data availability

References

Data availability

Cited By

Figures (12)

Tables (1)

Equations (12)

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