Next-generation communication networks require the integration of traditional and high-frequency bands to support diverse applications, positioning the optical heterodyne approach as a promising candidate for remote radio head (RRH) signal generation. However, deploying point-to-point (PtP) analog links based on such an optical heterodyne approach for the radio access networks (RAN) is challenging. Particularly, widespread deployment is expected to be hindered by practical communication resource constraints. In this context, we propose an arrayed waveguide grating router (AWGR)-based RAN architecture incorporating optical heterodyne signal generation, enabling adaptive frequency adjustment and scalable resource management. We detail the architecture and establish its generalizability through mathematical derivation. For a representative 64×64 AWGR-based system, the proposed architecture could reduce the required number of local oscillator (LO) lasers to 1/8 of conventional approaches, with potential for further reduction via scheduling. Experimental validation at both 28 GHz (mmWave) and 286 GHz (THz) bands demonstrates physical feasibility, achieving bit-error rates (BER) of 3.06×10−5 and 1.53×10−4, respectively. This AWGR-based architecture offers a practical path towards resource-efficient, high-agility fiber-wireless converged access.

The recent AI boom requires more focus on energy-efficient and scalable optical interconnects. Silicon Photonics is enabling technology to satisfy growing demand. However, the lack of lasers and high-performance modulators hinders wide-scale adoption. Therefore, we present a heterogeneously integrated Indium Phosphide electro-absorption modulator with Silicon waveguides. We demonstrate up to 256 Gb/s on-off keying, 340 Gb/s 4-level pulse amplitude modulation, 375 Gb/s 6-level pulse amplitude modulation, and 360 Gb/s 8-level pulse amplitude modulation transmission over 500 m and 6 km of single-mode fiber with performance satisfying requirements of 6.25% overhead hard-decision forward error correction threshold of 4.5×10-3. Additionally, we investigate the modulator at 200 Gb/s per lane scenarios, demonstrating excellent performance with a simple seven-tap feed-forward equalizer.

Unprecedented demand for energy-efficient optical interconnects in AI clusters requires scalable and small footprint solutions. Silicon photonics platform has emerged as scalable cost-effective solution for short-reach optical interconnects. In this paper, we report record optical-amplification free performance using our designed silicon photonics C + L band and O band ring-resonator modulators suitable for high energy-efficiency optical interconnects. We demonstrate optical-amplification-free transmission of up to 245 Gbps OOK, 280 Gbps PAM4 and 265 Gbps PAM6 using C + L band RRM and up to 206 Gbps OOK and 224 Gbps PAM4 using O band RRM. The achieved speeds are shown as gross bitrate. This paves way for energy-efficient dense optical interconnects with great manufacturing scalability.

We demonstrate record unamplified transmissions of 256 Gbaud OOK, 155 Gbaud PAM4 and 128 Gbaud PAM6 using a C-band differential-drive SiP TW-MZM, achieving BER performance below the 6.25% HD-FEC threshold after 100 m SMF transmission.

We show a record optical amplification-free 400 Gbps PAM4/6/8 net bitrate transmission in the O-band over 500-meter SMF with performance below 6.25% OH HD-FEC threshold using 1 V<inf>pp</inf> driving voltage on the TFLN MZM.

The photonic terahertz integrated sensing and communication (THz-ISAC) holds immense potential for enabling ultrahigh data rates and millimeter-resolution sensing, due to its exceptionally broad bandwidth. Nevertheless, the limited radiation power of existing THz sources restricts the full utilization of their broadband advantages in single-channel ISAC systems. In this work, a photonic THz-ISAC system model utilizing the chirp spread spectrum (CSS) waveform scheme is proposed and theoretically analyzed, by considering the noise contribution of the photonic THz transceiver and the free-space propagation loss (FSPL). Based on the proposed waveform, we derive the closed form of communication error vector magnitude (EVM) and radar sensing Cramér–Rao lower bound (CRLB), as well as the performance bounds. Then, a proof-of-concept experiment operating at 285 GHz is conducted to verify the performance of the CSS waveform, achieving 12 Gbit/s transmission with a 1.5 cm range resolution. In addition, the experiment validates the performance trade-offs among chirp bandwidth, data rate, and signal power, aligning well with our theoretical bounds. Therefore, the proposed scheme provides a design guideline for CSS-based photonic THz-ISAC systems.

Terahertz (THz, 0.3–10 THz) radar systems have garnered significant attention due to their superior capabilities in high-precision and robust sensing. However, the susceptibility to jamming, along with the sensing precision loss and ranging ambiguity induced by inflexible implementation of the conventional radar signal source, presents major challenges to the practical deployment of THz radars. Herein, a flexible photonic chaotic radar system is proposed at the THz band and investigate the ranging performance in precision and ambiguity. The photonic heterodyne detection scheme facilitates the generation of optoelectronic feedback loop-based THz chaos at 300 GHz, achieving a seamless connection between THz domains and optical domains. The system is experimentally demonstrated its superior performance of sub-centimeter resolution with 0.9345 cm and ranging unambiguity simultaneously. This work bridges the THz gap in the practical deployment of chaos theory and will pave the way for a new regime of THz radar empowered by chaos.

This paper explores the role of photonic terahertz technologies in integrated sensing and communication systems, focusing on integrated waveform design, optical processing, and algorithms to enhance communication capabilities and sensing performance.

This paper explores photonic-based analog fronthaul solutions for 6G, highlighting their effectiveness in meeting the RF requirements of standards, supporting future distributed-MIMO networks, and providing insights into prospective solutions for radios in potential 6G bands.

The radio-over-fiber (RoF) system is promising to support broadband transmission and increased flexibility. To boost channel capacity in multi-carrier RoF systems with variable-rate forward error correction, probabilistic shaping and water-filling-based entropy loading outperforms bit-power loading in terms of achievable information rate. However, its reliance on specific channel conditions limits practical use in channel-dynamic RoF systems, highlighting the need for adaptive entropy loading that requires minimal channel state information. This paper presents a deep neural network-based transfer learning model for adaptive entropy prediction in discrete multi-tone signals, addressing frequency-selective responses in RoF systems. Numerical and experimental results confirm capacity-approaching generalized mutual information (GMI) and smoother normalized GMI (NGMI) performances, consistently achieving the 0.83 NGMI threshold across subcarriers. Unlike traditional methods requiring pre-measured signal-to-noise ratios (SNR), this approach simplifies implementation by using only demodulated data and the received SNR, providing a more channel-independent entropy loading option in dynamic RoF systems.