Channel modeling for the satellite-to-underwater laser communication (StULC) link remains challenging due to long distances and the diversity of the channel constituents. The StULC channel is typically segmented into three isolated channels: the atmospheric channel, the air-water interface channel, and the underwater channel. Previous studies involving StULC channel modeling either focused on separated channels or neglected the combined effects of particles and turbulence on laser propagation. In this paper, we established a comprehensive StULC channel model by an analytical-Monte Carlo hybrid approach, taking into account the effects of particles, bubbles, and turbulence. We first obtained the intensity distribution of the transmitted laser beam after passing through the turbulent atmosphere based on the extended Huygens-Fresnel principle. Then we derived a closed-form probability density function of angular fluctuations of the beam refracted by the random sea surface. These analytical results are then mapped to initialize photon states for the Monte Carlo simulation of the underwater channel. Based on the proposed StULC channel model, we analyzed the bit error rate and the outage probability under different environmental conditions and system parameters. Numerical results demonstrated that the influence of underwater particle concentration on the communication performance is more pronounced than that of both the atmospheric turbulence and the underwater turbulence. In addition, enlarging the receiver aperture provides a more effective performance improvement than increasing the receiver field-of-view angle.

Modeling of multiple-scattering channels in atmospheric turbulence is essential for the performance analysis of long-distance non-line-of-sight (NLOS) ultraviolet (UV) communications. Existing works on the turbulent channel modeling for NLOS UV communications either focused on single-scattering cases or estimate the turbulent fluctuation effect in an unreliable way based on Monte-Carlo simulation (MCS) approach. In this paper, we establish a comprehensive turbulent multiple-scattering channel model by using a more efficient Monte-Carlo integration (MCI) approach for NLOS UV communications, where both the scattering, absorption, and turbulence effects are considered. Compared with the MCS approach, the MCI approach is more interpretable for estimating the turbulent fluctuation. To achieve this, we first introduce the scattering, absorption, and turbulence effects for NLOS UV communications in turbulent channels. Then we propose the estimation methods based on MCI approach for estimating both the turbulent fluctuation and the distribution of turbulent fading coefficient. Numerical results demonstrate that the turbulence-induced scattering effect can always be ignored for typical UV communication scenarios. Besides, the turbulent fluctuation will increase as either the communication distance increases or the zenith angle decreases, which is compatible with existing experimental results and also with our experimental results. Moreover, we demonstrate numerically that the distribution of the turbulent fading coefficient for UV multiple-scattering channels under all turbulent conditions can be approximated as log-normal distribution; and we also demonstrate both numerically and experimentally that the turbulent fading can be approximated as a Gaussian distribution under weak turbulence.

Terahertz (THz) band is acknowledged as a candidate spectrum in future networks. However, THz communications demand the assistance of high-accuracy parameter estimations to achieve narrow beam-alignment. Despite existing works have intensively explored sensing-assisted THz communications, they fail in mobile and near-field scenarios without concerning the benefits brought from velocity and distance estimations. To this end, a closed-form framework toward sensing-assisted terahertz near-field mobile communications (SA-TNMC) is introduced in this paper. Four-dimensional parameters containing distance, azimuth angle, radial velocity, and tangential angular velocity are extracted from the echoes, all of which are utilized for beamfocusing. For performance characterizations, both Cramér-Rao Bound and Ergodic Shannon Capacity are derived in closedform expressions. Besides, a novel critical point is proposed to demarcate the minimized resource division factor to activate SA-TNMC system. At last, numerical results are proceeded to validate the framework.

Hybrid analog and digital ultra-massive multiple-input multiple-output (UM-MIMO) has become one of the key enabling technologies for the upcoming 6G. As the number of antennas of UM-MIMO systems increases and the array size grows, the near-field assumption should be considered instead of the far-field assumption. Therefore, more complex algorithms are required to estimate the DoA and distance that describe the characteristics of the source. In this paper, we propose an efficient near-field localization algorithm for hybrid analog and digital UM-MIMO systems, which reduces the high computational complexity of existing algorithms in the near field by decoupling directions of arrival (DoA) and distance estimation. Firstly, by designing the digital combiner, we estimate the DoA using the central subarray received signal. Next, we design a set of analog combiners that depend solely on the distance, and apply signal-to-noise ratio (SNR) determination to narrow down the range for distance estimation. Finally, digital combiners are applied to perform an exhaustive search within the narrowed distance range, enabling efficient localization. Simulation results show that the localization performance of our proposed algorithm is superior to the existing algorithms, and its computational complexity is significantly reduced.

Reconfigurable intelligent surfaces (RIS) have received significant attention in the field of communication and wireless networks, due to their numerous advantages, such as low cost, low energy consumption, miniaturization, programmability, and ease of deployment. This paper proposes an RIS based on liquid crystal (LC) for constructing wireless communication systems. Tunable LC embedded between metal microstructures supported by quartz substrates allows for precise control of the reflected wave phase. The experimental results demonstrate that RIS has more than 3600 of phase modulation capability and four stable digital coding states at the optimal operating frequency of 100.2 GHz. In addition, the RIS has a 100∘ beam scanning capability, providing a solid foundation for tracking and targeting during communications. The communication capability of RIS was then demonstrated in the sub-terahertz band by constructing a 16QAM constellation diagram test system and a video real-time transmission system with varying deflection angles. Our work provides excellent solutions for communication and wireless network applications in the millimeter wave and terahertz (THz) frequency bands.

Terahertz (THz) offers the availability of huge bandwidth to provide unprecedented data rate for the sixth-generation mobile communication and beyond. Since the narrow beam would be transmitted in the terminals to address severe path loss, THz beam alignment has been a source of significant overhead. The Direction of Arrival (DoA) sensed from a low-frequency band communication system could help fast beam alignment of THz communication. However, it is inefficient since it wastes hardware sources and requires exchange information between the sub-6 GHz and THz systems. In this article, based on the spatial similarity of the intermediate frequency (IF) channel and THz channel, a THz communication system is designed by sensing the DoA of the leaky waves from IF ports of the classical superheterodyne communication structure to aid the THz beam alignment, in which the IF part is controlled by a switching network. It is fast and efficient, since the DoA is employed and no additional communication baseband is used. Compared to the conventional beam alignment methods, the proposed shows well performance on accuracy, reactiveness and overhead, especially in scenarios for limited channel measurement as well as massive multiple-input multiple-output which are regular in THz communication.

With gigahertz-level bandwidth, terahertz (THz) holds promise for achieving exceptionally high transmission rates in prospective sixth-generation (6G) communications. However, considerable path loss poses an obstacle to THz communications. To compensate for this, massive multiple-input-multiple-output (MIMO) based beamforming is utilized to promote directional power with narrow beams in communications. In dynamic environments, the frequent adjustment of narrow beams results in fast time-varying channel state information (CSI), which constrains the application of the THz communication systems. While traditional deterministic-based and statistical-based channel tracking methods address different aspects of this issue, they suffer from balancing accuracy and complexity in the THz dynamic environments. To solve this problem, based on the cluster distribution of THz time-varying channel, we propose a novel hybrid channel tracking method that uses deterministic physical motion variation law to extract the cluster subspace, and then statistical Markov evolution models are applied within it. To achieve this, an integrated clustering and estimation method, clustering subspace matching pursuit (CSMP) is proposed for obtaining the channel clusters prior knowledge. Then based on above hybrid tracking method design, we propose a virtual cluster subspace turbo-approximate message passing (VCS-TAMP). Finally, several simulation results validate that our proposal achieves great improvement in both accuracy and computational time performance.

As one of the key enabler technologies for future networks, terahertz communications (THzComs) are vulnerable to performance degradation and even outage in mobile and near-field scenarios. The emerging integrated sensing and communications (ISAC) technique paves a way to settle the challenges by estimating user position or channel state to achieve beam-alignment, but fails to content the needs of near-field beam-focusing in mobile scenarios. To this end, a closed-form model for terahertz near-field sensing-assisted mobile communications (TNF-SAMC) is provided. Firstly, the TNF-SAMC system models in temporal/frequency/spatial-division schemes are exhibited. Secondly, a near-field four-dimensional sensing framework characterized by Cramér-Rao Bound is put forward. Thirdly, considering the assistance of sensing, the closed-form expressions of Ergodic Shannon Capacity is derived. Next, the theoretical analysis is proceeded to reveal TNF-SAMC performance features in terms of Division Factor, Joint Cramér-Rao Bound, and Critical Point. Especially the simplified closed-form derivations of Critical Points are given, hinting the minimum resources that should be allocated for sensing in TNF-SAMC systems. Then, numerical results verify the conclusion that temporal-division scheme prefers low mobility scenario, spatial-division scheme performs better in beam alignment case, while frequency-division scheme is most superior in TNF-SAMC systems.

As data transmission demand grows rapidly, terahertz (THz) frequency has been regarded as the most promising candidate in future sixth-generation (6G) communication systems. Facing severe path loss, THz communications have to use massive MIMO technology to promote the directional transmission gain in narrow beams. However, narrow beams and wide bandwidth signal in THz communications together result in the time-frequency-space non-stationary channel. To track this non-stationary channel, we first combine THz massive MIMO communication system with orthogonal time frequency space (OTFS) modulation to get the union sparse channel on delay-Doppler-angle (DDA) domain. Then this non-stationary channel is modeled through our proposed DDA-2D-Markov models (DDA-2D-MM) considering the unique channel characteristics on delay, Doppler and angle dimension respectively. Besides, we design a unique DDA-structured approximate message passing (DDA-STAMP) algorithm to track the dynamic channel with the prior information in consecutive time slots to improve the algorithm convergence speed and accuracy performance. Simulation results show that the proposed DDA-STAMP algorithm enhances both of the time consumption and accuracy performance in THz massive MIMO-OTFS communication channel tracking.

Terahertz (THz) massive MIMO with wideband hybrid precoding has been considered one of the crucial techniques to compensate for the high-path loss in 6G high-data-rate Internet of Things (IoT). However, the beam split in wideband hybrid precoding makes the beam of different subcarriers aiming at different directions, which results in only partial channel state information (CSI) from the users to the BS. The efficiency of the CSI-based terahertz (THz) wideband beamforming scheme which is more efficient than the hardware-based scheme in narrow-band would degrade severely. To address the degradation, in this article, we first propose a sensing-aided THz wideband hybrid precoding which restores the full CSI. Through sensing and deducing the angle-frequency information, we construct a channel-selecting matrix and inverse the full CSI from our complete channel dictionary. Moreover, in order to satisfy the multiuser access requirements in IoT, we also propose dynamic radio frequency (RF) chains and dynamic power allocation schemes to further enhance the performance in multiuser scenarios based on a new precoding perspective in which each RF chain serves only one user. This benefits from the highly sparse THz channel characteristic. The spectral efficiency and energy efficiency are employed to validate that the proposed is efficient. The numerical results demonstrate that our proposed sensing-aided wideband hybrid precoding scheme achieves similar performance to the optimal precoding and much better performance to the true time delay scheme and the full CSI-based scheme.

The beam split in the frequency domain seriously affects hybrid precoding performance in wideband terahertz (THz) massive multiple-input multiple-output (MIMO) systems. The receiver hardly catches full Channel State Information (CSI) of all subcarriers due to spatial angle diffusion caused by the beam split, which would decrease the efficiency of hybrid precoding. To address the decrease, sensing-aided hybrid precoding is proposed to deduce the frequency-angle information in this paper. A channel matrix inverting scheme which can regain full CSI from the frequency-angle information of partial CSI is modeled. A 300 GHz MIMO system with 15 GHz bandwidth is simulated to validate the proposed sensing-aided hybrid precoding. Spectral and energy efficiency are employed to characterize the performance of the systems. Compared with true-time-delayers (TTD) based and partial CSI based schemes with no sensing in the state of the art, the proposed sensing-aided scheme performs higher spectral and energy efficiency.

As an enabler technology in future network, terahertz (THz) joint radar-communication (T-JRC) has been envisioned as a solution to overcome the challenges in THz communications. Recent works on JRC mainly emphasize either performance tradeoffs or mutual benefits between radar and communication functionalities. Unable to characterize both benefit and tradeoff relationships, existing metrics and models are inapplicable to performance analysis on T-JRC systems. In this paper, a closed-form T-JRC performance model are proposed to explore the relationship between radar and communication metrics. To begin with, a novel T-JRC system model concerning random mobility and THz beam tracking is put forward. Next, the performance bounds of T-JRC performance in terms of communication rate and a proposed radar rate are acquired in three different integration cases. Furthermore, the expression of communication rate by radar rate in T-JRC is obtained theoretically, which is the first time to derive the closed-form relationship considering both benefits and tradeoffs to the best of our knowledge. Finally, numerical results validate the proposed model as well as closed-form expression, showing that the model succeeds in benefit and tradeoff relationship characterization in T-JRC systems and the fitting bounds are applicable in non-extreme scenarios.

Terahertz (THz) joint radar-communication (T-JRC) has been envisioned as a method to overcome the challenges in THz communications. Recent works mainly emphasize the tradeoffs between radar estimations and data communications, unable to characterize the mutual benefit relationship as a key feature of T-JRC system. In this work, a comprehensive performance model considering both tradeoff and benefit relationship is derived for THz systems under random mobility. TJRC performance in three typical cases is analyzed to present the universality of the model. Additionally, the bounds of TJRC performance are acquired in terms of the communication data rate and a novel radar rate extended from the traditional works. Finally, the simulations of T-JRC systems considering mobility, beamwidth and distance are performed to validate the derived models. Numerical results indicate that the mutual benefit relationship dominates in low radar rate, while tradeoffs are crucial when the radar estimations are sufficient.

In the above letter, the authors investigate and present dielectric measurements of powdered forest fire ash using the Nicholson–Ross–Weir method within a WR-90 waveguide (X-band 8–12 GHz). However, some errors have been found, which are clarified in this letter.