The hot-carrier photothermoelectric (PTE) effect in two-dimensional materials can be used to develop room-temperature, fast, and sensitive detectors for microwave, terahertz, and far-infrared radiations. Here, we present a van der Waals semimetal PtSe ₂ terahertz detector and find a giant terahertz PTE response mediated by hot carriers at the metal-PtSe ₂ interfaces. The detector demonstrates an excellent zero-bias responsivity of 0.62 ampere per watt (A/W), a low-noise equivalent power of 19.6 picowatt per square root of hertz (pW/Hz ^1/2 ), and a fast response time of 4.5 nanosecond (ns) at 0.1 terahertz (THz). The metal doping effect and asymmetric terahertz heating play vital roles in the hot-carrier PTE response at the metal-semimetal interfaces. Moreover, scanning photocurrent mapping shows that the short-wave zero-bias photoresponse is closely localized to the metal-semimetal interfaces, further revealing the metal doping effect. The bias-dependent photocurrent indicates that the short-wave photoresponse still originates from the PTE effect and the photovoltaic response is negligible. Our results provide important guidance for developing high performance semimetal detectors.

Recently, neural networks have gained prominence as potent tools in the realm of channel modeling in optical wireless communication (OWC) systems. However, existing channel networks tend to ignore random intensity noise and phase noise induced by optical sources under spontaneous and excited radiation, and likewise the shot noise of the devices. They could only characterize deterministic noise such as ໿inter-symbol interference (ISI), ໿signal-to-signal beat interference (SSBI), and nonlinearities. In this paper, a novel channel simulator framework to optical wireless communication systems is proposed, which can jointly learn the deterministic noise and random noise of the real channel simultaneously. The proposed approach is a comprehensive noise joint channel estimator (CNJCE) architecture. A comprehensive comparison is carried out in both simulations, free space optical (FSO) experiments and underwater visible light communication (UVLC) experiments, including three classical deep learning algorithms, two tributaries heterogeneous neural network (TTHnet) with posteriori additive white Gaussian noise (AWGN), white Gaussian noise layer-based channel estimator (WGNCE) and conditional generative adversarial network (CGAN) based channel model. In order to represent both deterministic noise and random noise modeling capabilities, an overall estimation score is also proposed, based on frequency mismatch and random noise distribution error. The final experimental results show that CNJCE achieved the highest average estimation scores of 79.86 and 97.52 in real FSO and UVLC channels respectively. In contrast, TTHnet without AWGN or WGNCE only achieved 39.83 and 43.82. And CGAN based channel model completely lost signal characteristics, far worse than CNJCE. Through comparison of various performance, CNJCE demonstrates commendable capabilities in generalization and robustness, concurrently achieving optimal performance in channel modeling. To the best of our knowledge, this is the first time that deterministic and random noise have been fully modeled in optical wireless communication modeling. Its applicability is showcased through successful deployment in real FSO and UVLC systems, thus establishing a foundational framework for comprehensive end-to-end learning paradigms.

Integration of sensing and communication (ISAC) systems at the terahertz (THz) band will play a crucial role across a myriad of applications in the 6G era, profoundly enhancing our daily experiences. Photonic-based THz ISAC systems harness the inherent broad bandwidth to directly generate high-frequency broadband signals, ensuring seamless integration with fiber-wireless networks and demonstrating significant potential. Current ISAC systems employ linear frequency modulation (LFM) signals for sensing struggle to directly receive and de-chirp THz echo signals, which, nonetheless, curtails sensing capabilities; moreover, no research has yet investigated the impact of varying fiber lengths on the performance of downlink sensing signal transmission and uplink echo signal return. This article presents a THz photonic-based ISAC system designed to surmount these limitations. At the radar receiver, full-photonic direct reception and de-chirping of D-band LFM signals are realized by a high-bandwidth thin-film lithium niobate Mach–Zehnder modulator (TFLN-MZM); moreover, we evaluate the impact of different fiber lengths on system performance. Our system attains an exceptional range resolution of 6 mm and a peak data rate of 116 Gbit/s at a center frequency of 134 GHz, with a calibrated mean ranging error of less than 3 mm.

The E/W band millimeter-wave (MMW) emerges as a promising frequency band with many advantages such as the possession of abundant spectrum resources, low atmospheric attenuation, and good directionality. Meanwhile, full-photonic based MMW systems offer the potential to further reduce the complexity of electronic down-conversion and enhance overall system bandwidth, and allow seamless integration with the fiber-optic network. In this paper, we proposed an E/W band MMW communication architecture based on full-photonic up- and down-conversions, utilizing a frequency- and phase-locked optical two-tone generator at both the transmitting and receiving end. We successfully demonstrated a long-distance field trial of E/W-Band wireless transmission, achieving 26.8-km wireless delivery of 32-Gb/s quadrature phase shift keying (QPSK) signal, and the largest net-rate-distance-product up to 745.74 Gb/s·km per antenna per channel. The long-distance transmission performance of different modulation formats was also studied. We also achieved a 22-Gb/s QPSK transmission over a longer distance of 30.4 km, with a net-rate and distance product reaching 581.56 Gb/s·km. Moreover, this paper analyzes the complex sea surface channel and experimentally verifies the influence of the sea surface environment on the channel, which is instructive for long-distance MMW sea surface communications.

We propose and demonstrate a hybrid communication architecture that combines millimeter-wave (MMW) in the radio frequency (RF) domain and free-space-optics (FSO) technologies using adaptive combining and hybrid automatic repeat request (HARQ) techniques. At the receiving end, we employed joint signal processing with an adaptive diversity combining technique (ADCT) based on a maximum ratio combining (MRC) algorithm. We derived closed-form expressions for the outage probability and throughput of the hybrid RF and FSO (RF/FSO) system, considering various characteristics of atmospheric turbulence in the FSO link. Experimental testing with 10-Gbaud quadrature phase shift keying (QPSK) data was conducted under different simulated atmospheric turbulence intensities, FSO and MMW speed-ratios, and forward error correction (FEC) overheads. Additionally, we validated improvements in terms of bit error ratio (BER), outage probability, and throughput performance.