With the growing demands for marine environmental monitoring, collaborative operations, and marine resource development, high-speed and reliable Internet of Things (IoT) communication has become essential for maritime activities. This paper presents a wideband channel measurement campaign at 3.3 GHz in complex nearshore environments to investigate ship-to-ship (S2S) channel characteristics. The study systematically examines time-frequency stationarity, large-scale fading (LSF), dispersion, and small-scale fading (SSF). Results show that the mean stationarity distance reaches 22.48 m, with an average stationarity bandwidth exceeding 39.95 MHz. The statistical close-in (CI) model provides superior accuracy for path loss modeling, while the shadow fading autocorrelation exhibits a periodic oscillatory pattern, captured by a proposed improved model. Time–frequency–angular analysis indicates weak overall dispersion, with stronger dispersion in complex nearshore environments compared to open sea. Furthermore, RMS delay spread, Doppler spread, and angular spread are accurately modeled by Lognormal, Weibull, and Lognormal distributions, respectively. The Rician distribution dominates SSF envelope modeling, with the K-factor following a Normal distribution (mean 14.28–16.03 dB). These findings provide valuable insights for the design and evaluation of maritime IoT communication systems in nearshore environments.

As a key technology of future communication systems, reconfigurable intelligent surfaces (RISs) can intelligently control wireless signal reflections, thereby optimizing propagation channels and enhancing communication performance. However, the indoor channel characteristics and communication performance of RISs in real-world deployment environments remain insufficiently studied. In this paper, we develop a RIS-based measurement platform for simultaneous channel measurement and link-level performance analysis, followed by verification and validation in a laboratory environment. Utilizing this platform, we conduct wideband channel measurement and performance analysis work in indoor scenarios at 2.6 GHz band. Multiple RIS phase shift codebooks are employed, including the 1-bit discrete Fourier transform (DFT) codebook, the Ring-type codebook, and the conditional sample mean (CSM) codebook. Based on these measurements, two empirical path loss (PL) models, namely the floating-intercept (FI) model and the close-in (CI) model, are fitted to the measured data. Furthermore, we comprehensively analyze and compare the channel characteristics of RIS-assisted communications, including shadow fading (SF), multipath components (MPCs) statistics, the Rician K-factor (KF), and root mean square (RMS) delay spread. Finally, we evaluate and compare the wireless coverage and link-level performance of various RIS reflection schemes. The findings on propagation characteristics and communication performance provide essential insights that can support the future application and deployment of RIS-assisted communication systems.

As next-generation wireless communication systems need to be able to operate in high-frequency bands and high-mobility scenarios, delay-Doppler (DD) domain multicarrier (DDMC) modulation schemes, such as orthogonal time frequency space (OTFS), demonstrate superior reliability over orthogonal frequency division multiplexing (OFDM). Accurate DD domain channel modeling is essential for DDMC system design. However, since traditional channel modeling approaches are mainly confined to time, frequency, and space domains, the principles of DD domain channel modeling remain poorly studied. To address this issue, we propose a systematic DD domain channel measurement and modeling methodology in high-speed railway (HSR) scenarios. First, we design a DD domain channel measurement method based on the long-term evolution for railway (LTE-R) system. Second, for DD domain channel modeling, we investigate quasi-stationary interval, statistical power modeling of multipath components, and particularly, the quasi-invariant intervals of DD domain channel fading coefficients. Third, via LTE-R measurements at 371 km/h, taking the quasi-stationary interval as the decision criterion, we establish DD domain channel models under different channel time-varying conditions in HSR scenarios. Fourth, the accuracy of proposed DD domain channel models is validated via bit error rate comparison of OTFS transmission. In addition, simulation verifies that in HSR scenario, the quasi-invariant interval of DD domain channel fading coefficient is on millisecond (ms) order of magnitude, which is much smaller than the quasi-stationary interval length on 100 ms order of magnitude. This study could provide theoretical guidance for DD domain modeling in high-mobility environments, supporting future DDMC and integrated sensing and communication designs for 6G and beyond.

Deep learning (DL) has become pivotal in advancing integrated sensing and communication (ISAC) systems. However, conventional DL models often require frequent updating or retraining to adapt to dynamic ISAC environments. To address these limitations, this work creatively proposes a large language model (LLM)-based ISAC system, called LLM-ISAC, to enable concurrent sensing-communication processing in a unified framework, with enhanced generalization and environmental robustness. To realize LLM-ISAC, we design a novel signal encoder to transform ISAC signals into LLM-compatible representations through a delay-Doppler-spatial transformer, enabling discriminative cross-domain signal feature extraction for downstream tasks. Moreover, we develop an innovative ISAC-specific context prompt to construct structured machine-readable prompts, dynamically guiding the LLM’s reasoning without retraining and ensuring robust generalization to unseen scenarios. To the best of the authors’ knowledge, this is the first work leveraging the property of LLM in ISAC systems. Extensive simulations demonstrate that LLMI-SAC achieves significant superiority in sensing accuracy, communication reliability, and environmental robustness, compared to state-of-the-art DL-based ISAC methods.

In user-generated-content (UGC) applications, non-expert users often rely on image-to-3D generative models to create 3D assets. In this context, primitive-based shape abstraction offers a promising solution for UGC scenarios by compressing high-resolution meshes into compact, editable representations. Towards this end, effective shape abstraction must therefore be structure-aware, characterized by low overlap between primitives, part-aware alignment, and primitive compactness. We present Light-SQ, a novel superquadric-based optimization framework that explicitly emphasizes structure-awareness from three aspects. (a) We introduce SDF carving to iteratively udpate the target signed distance field, discouraging overlap between primitives. (b) We propose a block-regrow-fill strategy guided by structure-aware volumetric decomposition, enabling structural partitioning to drive primitive placement. (c) We implement adaptive residual pruning based on SDF update history to surpress over-segmentation and ensure compact results. In addition, Light-SQ supports multiscale fitting, enabling localized refinement to preserve fine geometric details. To evaluate our method, we introduce 3DGen-Prim, a benchmark extending 3DGen-Bench with new metrics for both reconstruction quality and primitive-level editability. Extensive experiments demonstrate that Light-SQ enables efficient, high-fidelity, and editable shape abstraction with superquadrics for complex generated geometry, advancing the feasibility of 3D UGC creation. Project Page: https://johann.wang/Light-SQ/ .

In the high-speed railway (HSR) scenario, handover (HO) reliability is constrained by the high-speed movement and weak coverage at cell edges, posing a threat to the "always online" transmission requirement. To address this, we propose a dynamic beamforming scheme to mitigate HO failures and improve data rates. First, a beamforming-based HO model is established, quantifying the impact of beam direction on data rate and HO reliability. Based on this, an optimization problem is formulated, aiming to enhance data rate, reduce HO failure probability, and minimize beam adjustment overhead. Subsequently, a dynamic beam adjustment algorithm based on deep reinforcement learning is designed, leveraging its real-time decision-making capability to adaptively optimize the beam direction under rapidly changing channel conditions. Simulation results demonstrate that the proposed scheme requires only 23% of the beam adjustment overhead of the ideal real-time precise beamforming, while achieves nearly identical HO performance and 98.9% of its data rate.

In this paper, a measurement campaign is conducted to investigate unmanned surface vehicle (USV) communication channels in complex nearshore environments. The experiment setup includes a fixed offshore platform as the transmitter and a mobile vessel as the receiver. Based on the collected data, this study analyzes and models the stationarity and fading characteristics of the channel. The results show that the values for the 1st percentile, 50th percentile, and 90th percentile of the channel’s stationary distance (threshold=0.8) are 0.412 m, 5.99 m, and 23.19 m, respectively. Path loss analysis indicates that the close-in free-space reference path loss with a path loss exponent of 2.407 provides an accurate representation, while shadow fading follows a normal distribution with a mean of zero and a standard deviation of 4.55 dB. To better capture the autocorrelation of shadow fading, a novel model is proposed, improving accuracy by 35% compared to the conventional exponential model. Additionally, small-scale fading envelope analysis using the Akaike information criterion (AIC) confirms that the Rician distribution is the most suitable model. The K-factor of the Rician distribution can be statistically modeled as a bimodal Gaussian distribution, with a goodness-of-fit (GoF) value of 0.026.

In satellite communication systems, the Doppler effect caused by the high-speed motion of satellites significantly impacts the stability and performance of communication links. This is especially evident in pseudo-random code modulation systems, where the Doppler effect induces a frequency offset in the pseudo-code rate, thereby degrading signal demodulation performance. Focusing on the code Doppler effect in satellite communication scenarios, this paper investigates a channel simulation method adapted to the code Doppler effect and verifies its effectiveness.

In high-speed railway (HSR) scenarios, it is essential to ensure reliable handover for sustaining always-online communications of trains. However, this reliability is challenged by limited wireless coverage at cell edges and frequent handovers. To tackle these challenges, this paper explores the potential of dynamic beamforming to simultaneously improve the probability of successful handover and mitigate communication disruptions. First, we establish a beamforming-based transmission model for trains during handovers. Based on this model, we derive the impact of the beam directions of the serving and target cells on communication performance. Second, we formulate an optimization problem aiming at maximizing the conditional data rate of the train within handover regions, where the impacts of handover failure, rapid mobility, and beamforming overhead are considered. Third, to solve this optimization problem, we propose a dynamic beam direction adjustment algorithm by leveraging the property of deep reinforcement learning. The algorithm efficiently determines the optimal beam direction adjustment strategy based on the dynamic channel conditions. Finally, compared to state-of-the-art deep learning methods and beamforming strategies, simulation results demonstrate that the proposed method achieves superiority in communication quality at cell edges and handover performance, providing an efficient and reliable technical solution for HSR communications.

The orthogonal delay-Doppler (DD) division multiplexing (ODDM) modulation has been recently proposed as a promising modulation scheme for next-generation communication systems with high mobility. Despite its benefits, ODDM modulation and other DD domain modulation schemes face the challenge of excessive equalization complexity. To address this challenge, we propose time domain Tomlinson-Harashima precoding (THP) for the ODDM transmitter, to make the DD domain single-tap equalizer feasible, thereby reducing the equalization complexity. In our design, we first pre-cancel the inter-symbol-interference (ISI) using the linear time-varying (LTV) channel information. Second, different from classical THP designs, we introduce a modified modulo operation with an adaptive modulus, by which the joint DD domain data multiplexing and time-domain ISI pre-cancellation can be realized without excessively increasing the bit errors. We then analytically study the losses encountered in this design, namely the power loss, the modulo noise loss, and the modulo signal loss. Based on this analysis, BER lower bounds of the ODDM system with time domain THP are derived when 4-QAM or 16-QAM modulations are adopted for symbol mapping in the DD domain. Finally, through numerical results, we validate our analysis and then demonstrate that the ODDM system with time domain THP is a promising solution to realize better BER performance over LTV channels compared to orthogonal frequency division multiplexing systems with single-tap equalizer and ODDM systems with maximum ratio combining.

Orthogonal delay-Doppler (DD) division multiplexing (ODDM) modulation has recently emerged as a promising candidate for ensuring reliable communications over high mobility channels. One of the key challenges faced by systems based on ODDM modulation and other DD domain modulation schemes (e.g., orthogonal time frequency space modulation), is the excessive receiver complexity. To address this challenge, we propose time domain Tomlinson-Harashima precoding (THP) for the ODDM systems to make the single-tap equalizer feasible, thereby significantly reducing the receiver complexity. Different from previous THP designs, we first propose intersymbol-interference (ISI) pre-cancellation based on the linear time-varying (LTV) channel information. Second, we propose a modified modulo operation with an adaptive modulus to realize DD domain data modulation and time domain ISI precancellation. We analytically investigate the bit error rate (BER) performance of our proposed ODDM system with time domain THP. Particularly, we investigate three types of losses that can degrade the performance, namely the modulo signal loss, the power loss, and the modulo noise loss. Based on these, a lower bound for the BER of our proposed ODDM system with time domain THP under the DD domain single-tap equalizer is derived. Through numerical simulations, our analysis is first validated and finally, we show the significance of our design to attain a low complex receiver and superior BER performance over LTV channels.

In order to satisfy the increasingly massive connection in mMTC system, multiple access technology is a key enabler in the future 6G mMTC. Recently, an emerging multiple access scheme named resource hopping based multiple access (RHMA) has been proposed to achieve reliable user identification and data detection in grant-free random access for mMTC. However, the collision resolution of RHMA is still limited for the future 6G mMTC requirements. Therefore, an improved design is proposed in this paper to enhance the collision resolution capability of RHMA. Specifically, successive interference cancellation (SIC) is combined with user identification and segment decoding at the receiver of RHMA. Also, the user identification of RHMA is improved to eliminate the false alarm user caused by collision and blind channel estimation is considered to recover the signal on the colliding segments. The simulation results show that the improved design is able to achieve a higher collision resolution capability of RHMA.

The cellular-vehicle-to-everything (C-V2X) communication network is constantly evolving and changing the way people travel. To realize connected automated vehicles, both precise positioning and reliable communications of vehicles and associated terminals are demanding. Since the orthogonal frequency division multiplexing (OFDM) scheme is vulnerable to Doppler spread under high-mobility, the orthogonal time frequency space (OTFS) modulation is proposed recently to tackle this challenge based on the sparsity and stability of the channel spreading function. To this end, this article proposes a waveform design for V2X based on OTFS modulation, named orthogonal time frequency code space modulated waveform (OTFCSMW). The waveform design is able to realize random access and positioning simultaneously. In detail, the transceiver design of OTFCSMW is introduced, where orthogonal spreading sequences are utilized to provide spreading gain and represent terminal identifications based on the proposed orthogonal spreading combinations. Then a joint time-of-arrival (ToA) estimation and channel estimation strategy is proposed. The ToAs of terminals are estimated based on the sparsity of taps in the channel spreading function, and remaining unknown channel parameters are estimated based on the minimum-mean-square-error (MMSE) principle. Finally, the equalization scheme for OTFCSMW based on MMSE principle is proposed. Simulation results demonstrate that OTFCSMW can realize similar positioning performance to OFDM and outperforms the orthogonal-spreading-based-OFDM-waveform (S-OFDMW) scheme on bit error rate (BER) in different V2X channel environments.

Orthogonal time frequency space (OTFS) modulation is a promising technology for communications under high mobility in the sixth-generation (6G) communications system. To enable machine-type communications (MTC) with high mobility in 6G, researchers have considered designing multiple access (MA) technologies based on OTFS modulation. The reliability and connectivity of OTFS-MA are highly correlated with the characteristics of the channel spreading function. In the spectrum-limited MA system where the channel spreading function is not sparse and compact enough, the system device capacity of OTFS-MA schemes is limited. To this end, a grant-free MA scheme, named orthogonal time frequency code space modulation enabled multiple access (OTFCSMA) is proposed in this article. In general, orthogonal code domain resources are introduced into OTFCSMA to enhance device connectivity and transmission reliability of MA systems based on OTFS modulation. In detail, firstly, the characteristic of the realistic channel spreading function is described, especially the reduced sparsity and compactness of the channel in the spectrum-limited system. Secondly, the principles for designing OTFCSMA are described, including orthogonal spreading/despreading, data interleaving/deinterleaving, device identification, two-stage channel estimation, and data recovery strategies. Thirdly, the system device capacity and the system complexity of OTFCSMA are analyzed. Fourthly, a date-block-wise device connectivity scaling-up scheme for OTFCSMA is proposed, based on which the exponential system user capacity growth is realized. Finally, the performances of OTFCSMA on transmission reliability and device connectivity are demonstrated, and the gain brought by orthogonal spreading is analyzed.

With the emergence of various IoT applications, a large-scale IoT system is set to revolutionize the various industry. Massive machine type communication will play a crucial role in providing robust support to this system. However, in mMTC, implementing user access control to block malicious users remains a critical issue that needs to be addressed. To this end, this paper proposes a user access control scheme based on resource hopping multiple access (RHMA). This scheme utilizes the unique resource hopping patterns of different users to control user access. The controllability of these resource hopping patterns effectively prevents malicious users from intruding into the system. Moreover, the proposed user access control scheme is implemented in practice with USRP platform. The experimental results confirm the reliability and effectiveness of the proposed access control system.

With the massive deployment of 5G commercial applications, the Internet of Everything promotes the transformation and upgrading of the society production mode. The Internet of Things (IoT) is supported by the massive Machine-Type Communications (mMTCs), which is one of the three major application scenarios of 5G. Recently, a novel spreading-based nonorthogonal multiple access (NOMA) scheme named tandem spreading multiple access (TSMA) has been proposed for grant-free random access in mMTC. However, TSMA only considers the case of single antenna, the connectivity expansion on spatial domain has not been considered. In this article, a multiantenna system scheme of TSMA (MIMO-TSMA) is proposed to scale up user connections. In this scheme, spectrum efficiency can be promoted by sharing the time–frequency resources in different beams. In the meantime, scheme against channel deep fading is considered in this work. The simulation results show that MIMO-TSMA can effectively take advantage of multiple-input–multiple-output and TSMA to enhance the mMTC system performance.

Recently, grant-free orthogonal time–frequency space-based tandem spreading multiple access (OTFS-TSMA) is proposed for machine-type communications (mMTCs) in smart railways environmental sensing. To achieve massive connections with scarce radio resources, OTFS-TSMA combines the advantages of OTFS and TSMA. It shows high connectivity and reliability under time–frequency-selective fading channels. Meanwhile, smart railways require over-horizon and all-weather environmental sensing based on mMTC, and the implementation of both would cost a lot in terrestrial networks. With the development of low-Earth orbit (LEO) satellites, enabling smart railways mMTC over LEO satellite is a potential diagram. However, in this scenario, due to the larger transmission delay and Doppler frequency shift, the time–frequency resource requirements of the OTFS modulation-based system increase significantly and are difficult to meet. To this end, OTFS-TSMA based on differential Doppler shift is proposed in this article. Specifically, in this article, the satellite-to-ground communication system model consisting of three sections is introduced, and the Doppler shift and differential Doppler shift characteristics of access points (APs) are investigated. Next, it is proven that designing OTFS-based multiple access schemes over the LEO satellite based on differential Doppler shift is not only resource-friendly but also has the advantages of service continuity and controllable multiuser interference. Then, the transceiver of differential-Doppler-shift-based OTFS-TSMA and its improved designs are proposed. Finally, the simulation results demonstrate that the proposed transceiver realizes high resource efficiency, collision resolution capability, and reliability for smart railways mMTC over the LEO satellite.

Orthogonal time frequency space (OTFS) modulation is an emerging technology to tackle time-frequency (TF) selective channel in high mobility scenarios. In OTFS, resource is multiplexed in the delay-Doppler (DD) domain. Based on the potential sparsity, separability, stability and compactness of the channel spreading function, OTFS is able to realize lower complexity of channel estimation, higher diversity and higher reliability compared with orthogonal frequency division multiplexing (OFDM). However, the channel spreading function for practical communication systems is rarely considered in the current OTFS-related literature. High-speed railway (HSR) is a typical high mobility scenario with trains travelling at over 200km/h, which has the potential to employ OTFS. To this end, the HSR channel spreading function is characterized and the performance of OTFS in HSR is evaluated based on the realistic channel measurement in this article. Firstly, the HSR channel in TF domain is measured based on the long term evolution railway (LTE-R) network. Then, the characteristics of the channel spreading function are analyzed. In particular, the impact of time domain channel fading on the spreading function is investigated. The characteristics of the measured spreading function are analyzed with the proposed metrics in railway viaduct and tunnel scenarios. Based on the above analysis, an algorithm for generating the channel spreading function is proposed. Feasibility of the proposed DD domain channel generation algorithm is verified through comparing metrics of which to those of the measured channel. By simulating the bit error rate (BER) and mean square channel estimation error performances of OTFS modulation in the practical band-limited systems, it is shown that the impacts of Doppler shift, delay, SFFT and time domain channel fading need be considered for the application of OTFS modulation, in contrast to the state-of-art DD domain channel generation scheme based on tap delay link (TDL) model. For example, compared to OTFS modulation under the ideal channel spreading function, OTFS modulation requires a signal gain greater than 5 dB under the practical channel spreading function affected by above factors, to achieve the same BER less than 10−2 under parameters defined in simulation.

With the massive deployment of 5G commercial, the interconnection of all things promotes the transformation and upgrading of the social production mode. The Internet of Things (IoT) is supported by the massive machine-type communications (mMTC), which is one of the three major application scenarios of 5G. Recently, a novel spreading based non-orthogonal multiple access (NOMA) scheme named tandem spreading multiple access (TSMA) has been proposed for grant-free random access in mMTC. However, TSMA only considers the case of single antenna. In this article, a multi-antenna system scheme of TSMA with MIMO (MIMO-TSMA) is proposed to scale up user connections. In this scheme, spectrum efficiency can be promoted by sharing the non-orthogonal resources in different beams. The simulation results show that MIMO-TSMA can effectively take advantage of MIMO and TSMA to enhance the mMTC system performance.

Massive internet of things (mIoT) could play an important role in the future smart high-speed railway (HSR), where grant-free multiple access technologies are required. Recently, tandem spreading multiple access (TSMA) has been raised for mIoT without mobility which achieves high connectivity and reliability. Meanwhile, orthogonal time frequency space (OTFS) modulation shows its potential to combat high mobility in point-to-point communication systems. To this end, in this article, we jointly design OTFS and TSMA, and propose OTFS-TSMA for HSR mIoT. The principle of OTFS-TSMA transceiver is described, where OTFS and TSMA are improved respectively. Especially, two-dimension cyclic shift of DD domain elements in OTFS is transformed into cyclic shift of Doppler elements, segments, symbols and chips by the proposed novel resource allocation and interleaving schemes. Data recovery approaches of the four categories of cyclic shift are given, thus massive user interference is mitigated. Simulation results illustrate that both high user connectivity and transmission reliability in HSR massive IoT can be achieved by OTFS-TSMA.

As the paradigm of the next high-speed railway (HSR) evolution, the smart railway attracts increasing attention from various professionals. With the maturity of 5G technologies, numerous intelligent applications are expected to be enabled. Therein, the Internet of Things (IoT) for railway can be supported by the massive machine-type communications (mMTCs) system. Recently, a novel multiple access scheme named tandem spreading multiple access (TSMA) has been proposed for the grant-free random access procedure in mMTC. However, high mobility has not been considered in TSMA so that it cannot be employed in IoT for railway currently. In this article, multicarrier TSMA (MC-TSMA) is introduced and the high-speed adaptability is investigated. Particularly, the impact of Doppler shift and time-varying channel is analyzed. In the meantime, the corresponding improvement designs are proposed. The simulation results show that the proposed scheme can effectively mitigate the impact of high mobility on MC-TSMA.