Terahertz (THz) band unmanned aerial vehicle (UAV) links exploit ultra-wide spectra and high directivity to deliver multi-Gbps secure data for remote sensing and wireless backhaul, but their open three-dimensional flight paths increase vulnerability to covert detection and jamming. Altitude-dependent atmospheric loss, negligible in microwave or terrestrial THz studies, becomes critical in this band owing to triple selectivity, where propagation varies sharply with frequency, distance, and environment. In this paper, a spatially-aware transmission framework is proposed that jointly allocates spectrum and power according to node altitude and beam orientation to maximize jam-resilience covert throughput. Specifically, a three-dimensional propagation model incorporating altitude-dependent molecular absorption, weather loss, and turbulence is established, closed-form expressions for covert outage probability and throughput are derived, and the resulting nonconvex band-wise optimization is solved. Simulation results verify significant gains in covert throughput and jamming robustness and reveal that downward transmissions are more secure than upward counterparts, as their propagation path traverses denser and more absorptive air, whereas the upward path quickly rises into thinner layers that expose the signal to remote eavesdroppers. These analytical insights furnish a quantitative basis for altitude-aware spectrum planning and multilayer topology design in future space-air-ground integrated networks.

Millimeter-wave (mmWave) and Terahertz (THz)-band communications hold great promise in meeting the growing data-rate demands of next-generation wireless networks, offering abundant bandwidth. To mitigate the severe path loss inherent to these high frequencies and reduce hardware costs, ultra-massive multiple-input multiple-output (UM-MIMO) systems with hybrid beamforming architectures can deliver substantial beamforming gains and enhanced spectral efficiency. However, accurate channel estimation (CE) in mmWave and THz UM-MIMO systems is challenging due to high channel dimensionality and compressed observations from a limited number of RF chains, while the hybrid near- and far-field radiation patterns, arising from large array apertures and high carrier frequencies, further complicate CE. Conventional compressive sensing based frameworks rely on predefined sparsifying matrices, which cannot faithfully capture the hybrid near-field and far-field channel structures, leading to degraded estimation performance. This paper introduces DiffPace, a diffusion-based plug-and-play method for channel estimation. DiffPace uses a diffusion model (DM) to capture the channel distribution based on the hybrid spherical and planar-wave (HPSM) model. By applying the plug-and-play approach, it leverages the DM as prior knowledge, improving CE accuracy. Moreover, DM performs inference by solving an ordinary differential equation, minimizing the number of required inference steps compared with stochastic sampling method. Experimental results show that DiffPace achieves competitive CE performance, attaining -15 dB normalized mean square error (NMSE) at a signal-to-noise ratio (SNR) of 10 dB, with 90% fewer inference steps compared to state-of-the-art schemes, simultaneously providing high estimation precision and enhanced computational efficiency.

The Terahertz band holds a promise to enable both super-accurate sensing and ultra-fast communication. However, challenges arise that severe Doppler effects call for a waveform with high Doppler robustness while severe propagation path loss urges for an ultra-massive multiple-input multiple-output (UM-MIMO) structure. To tackle these challenges, hybrid beamforming with orthogonal delay-Doppler multiplexing modulation (ODDM) is investigated in this paper. First, the integration of delay-Doppler waveform and MIMO is explored by establishing a hybrid beamforming-based UM-MIMO ODDM input-output relation. Then, a multi-dimension sensing algorithm on target azimuth angle, elevation angle, range, and velocity is proposed, which features low complexity and high accuracy. Finally, an innovative decoupling of optimization goals is achieved by prioritizing sensing performance: Cramér-Rao lower bounds (CRLB) are minimized through dynamic beam scanning at the sensing combiner, which in turn allows the spectral efficiency to be independently maximized with stable beams at the precoder. Numerical results show that the sensing accuracy of the proposed sensing algorithm is sufficiently close to CRLB. Moreover, the proposed hybrid beamforming design allows us to achieve maximal spectral efficiency, millimeter-level range estimation accuracy and millidegree-level angle estimation accuracy.

Since decades ago, multi-antenna has become a key enabling technology in the evolution of wireless communication systems. In contrast to conventional multi-antenna systems that contain antennas at fixed positions, position-flexible antenna systems have been proposed to fully utilize the spatial variation of wireless channels. In this paper, fluid antenna systems (FAS) are analyzed by channel measurement, channel modeling, and performance evaluation. First, we fill the gap in experimental analysis on terahertz (THz) FAS by developing a broadband channel measurement with physical FAS operating in the THz band, for which the extremely high movable resolution reaches 0.02 mm and the temporal resolution is 16.7 ps. Channel measurement is conducted for a two-dimensional position-flexible antenna system across 32×32 planar port positions at 300 GHz. Then, in light of the measurement results, spatial-correlated channel models for the two-dimensional FAS are proposed, which is statistically parameterized by the complex covariance matrix extracted from the measurement. Furthermore, by applying either the signal-to-interference-and-noise ratio (SINR)-maximized position selection algorithm or the movable array scheme, FAS are verified to achieve 99% of the optimal performance in terms of spectral efficiency. Finally, the performance of different FAS types is evaluated and compared for both planar and linear FAS. Extensive results demonstrate the advantage of FAS over fixed-position antennas in coping with the multi-path fading and improving the spectral efficiency by over 10% in a 300 GHz measured channel.

Integrated sensing and communication (ISAC) at terahertz (THz) frequencies holds significant promise for unifying ultra-high-speed wireless connectivity with fine-grained environmental awareness. Realistic and interpretable channel modeling is essential to fully realize the potential of such systems. This work presents a comprehensive investigation of monostatic sensing channels at 300 GHz, based on an extensive measurement campaign conducted at 57 co-located transceiver (TRx) positions across three representative indoor scenarios. Multipath component (MPC) parameters, including amplitude, delay, and angle, are extracted using a high-resolution space-alternating generalized expectation-maximization (SAGE) algorithm. To cluster the extracted MPCs, an image-processing-based clustering method, i.e., connected component labeling (CCL), is applied to group MPCs based on delay-angle consistency. Based on the measurement data, an environment-aware channel modeling framework is proposed to establish mappings between physical scenario attributes (e.g., reflector geometry, surface materials, and roughness) and their corresponding channel-domain manifestations. The framework incorporates both specular and diffuse reflections and leverages several channel parameters, e.g., reflection loss, Lambertian scattering, and intra-cluster dispersion models, to characterize reflection behavior. Experimental results demonstrate that the proposed approach can reliably extract physical characteristics, e.g., structural and material information, from the observed channel characteristics, offering a promising foundation for advanced THz ISAC channel modeling.

Terahertz (THz) extremely large-scale MIMO (XL-MIMO) is considered a key enabling technology for 6G and beyond due to its advantages such as wide bandwidth and high beam gain. As the frequency and array size increase, users are more likely to fall within the near-field (NF) region, where the far-field plane-wave assumption no longer holds. This also introduces spatial non-stationarity (SnS), as different antenna elements observe distinct multipath characteristics. Conventional far-field stationary models with fixed path parameters fail to capture these variations. Therefore, this paper proposes a THz XL-MIMO channel model that accounts for both NF propagation and SnS, validated using channel measurement data. In this work, we first conduct THz XL-MIMO channel measurements at 100 GHz and 132 GHz using 301- and 531-element ULAs in indoor environments, revealing pronounced NF effects characterized by nonlinear inter-element phase variations, as well as element-dependent delay and angle shifts. Moreover, the SnS phenomenon is observed, arising not only from blockage but also from inconsistent reflection or scattering. Based on these observations, a hybrid NF channel modeling approach combining the scatterer-excited point-source model and the specular reflection model is proposed to capture nonlinear phase variation of different types of non-line-of-sight (NLoS) paths. For SnS modeling, amplitude attenuation factors (AAFs) are introduced to characterize the continuous variation of path power across the array. By analyzing the statistical distribution and spatial autocorrelation properties of AAFs, a statistical rank-matching-based method is proposed for their generation. Finally, the model is validated using measured data. Evaluation across metrics such as entropy capacity, condition number, spatial correlation, channel gain, Rician K-factor, and RMS delay spread confirms that the proposed model closely aligns with measurements and effectively characterizes the essential features of THz XL-MIMO channels.

The growing demand for ultra-high data rates in space-air–ground integrated networks (SAGINs) has rendered terahertz (THz) communications a promising technology due to its exceptionally broad and continuous spectrum resources. Nevertheless, in air–ground (AG) scenarios, the high mobility of aircraft induces intense and rapidly fluctuating turbulence, leading to additional propagation attenuation that is often overlooked in existing studies. To bridge this gap, an AI-empowered THz AG communication framework is proposed in this paper that models turbulence-induced attenuation and incorporates it into a joint power-attitude optimization. Specifically, a fluid-dynamics-informed attenuation model is established to characterize the turbulent impact on THz signal propagation. Building upon this model, a joint power-attitude optimization problem is formulated to adaptively allocate transmit power and adjust aircraft attitude for maximizing link capacity.The optimization is efficiently solved using a diffusion-based algorithm to adaptively allocate transmit power and adjust aircraft attitude for maximizing link capacity. Comprehensive numerical evaluations demonstrate that the turbulence-induced attenuation ranges from 18 to 28 dB under attacking angles between −10° and 10° at 0.7 Mach. Moreover, the proposed framework achieves an average capacity of 11.241 bps/Hz, outperforming existing strategies by 12.4% to 22.8%, and reaching approximately 98% of the theoretical capacity limit.

Terahertz (THz) communication is emerging as a pivotal enabler for 6G and beyond wireless systems owing to its multi-GHz bandwidth. One of its novel applications is in wireless data centers, where it enables ultra-high data rates while enhancing network reconfigurability and scalability. However, due to numerous racks, supporting walls, and densely deployed antennas, the line-of-sight (LoS) path in data centers is often instead of fully obstructed, resulting in quasi-LoS propagation and degradation of spectral efficiency. To address this issue, Airy beam-based hybrid beamforming is investigated in this paper as a promising technique to mitigate quasi-LoS propagation and enhance spectral efficiency in THz wireless data centers. Specifically, a cascaded geometrical and wave channel model (CGWCM) is proposed for quasi-LoS scenarios, which accounts for diffraction effects while being more simplified than conventional wave-based model. Then, the characteristics and generation of the Airy beam are analyzed, and beam search methods for quasi-LoS scenarios are proposed, including hierarchical focusing-Airy beam search, and low-complexity beam search. Simulation results validate the effectiveness of the CGWCM and demonstrate the superiority of the Airy beam over Gaussian beams in mitigating blockages, verifying its potential for practical THz wireless communication in data centers.

Terahertz (THz) communication is envisioned as a key technology for 6G and beyond wireless systems owing to its multi-GHz bandwidth. To maintain the same aperture area and the same link budget as the lower frequencies, ultra-massive multi-input and multi-output (UM-MIMO) with hybrid beamforming is promising. Nevertheless, the hardware imperfections particularly at THz frequencies, can degrade spectral efficiency and lead to a high symbol error rate (SER), which is often overlooked yet imperative to address in practical THz communication systems. In this paper, the hybrid beamforming is investigated for THz UM-MIMO systems accounting for comprehensive hardware imperfections, including DAC and ADC quantization errors, in-phase and quadrature imbalance (IQ imbalance), phase noise, amplitude and phase error of imperfect phase shifters and power amplifier (PA) nonlinearity. Then, a two-stage hardware imperfection compensation algorithm is proposed. In the first stage, a deep neural network (DNN) based unified hardware imperfection model is developed to represent the combined hardware imperfections. Furthermore, to balance the performance and model complexity, a tailored network slimming framework is proposed using three slimming methods including pruning, parameter sharing, and power-aware scheme to slim the network in the first stage. In the second stage, the digital precoder in the transmitter (Tx) or the combiner in the receiver (Rx) is designed using neural network (NN) to effectively compensate for these imperfections. Numerical results show that the Tx compensation can perform better than the Rx compensation. Additionally, using the combined slimming methods can reduce parameters by 97.2% and running time by 39.2% while maintaining nearly the same performance in both uncoded and coded systems.

Cell-free network architectures emerge as a prospective solution for Terahertz (THz) communication systems by deploying dense access points to simultaneously serve user equipments, which shorten communication distances and enhance link reliability. Meanwhile, abundant bandwidth and narrow beams of THz links improve the channel capacity and reduce interference in cell-free networks. However, the resource allocation problem in THz cell-free networks is yet an open issue, especially regarding long-term optimization in varying wireless environments. In light of this, a dynamic resource allocation problem established on dynamic array-of-subarrays hybrid beamforming is proposed to maximize the long-term sum-rate in THz cell-free ultra-massive multiple-input multiple-output (UM-MIMO) networks. Given the non-convex nature of this optimization objective and the requirement of dynamic programming, a multi-task based, multi-agent deep reinforcement learning algorithm (MTADRL) for resource allocation is developed. Simulation results validate that the THz cell-free network enhances the data rates compared to small cell and cellular counterparts. Furthermore, MTADRL demonstrates robust convergence, achieving a 19% and 46% improvement in long-term sum-rate over the benchmark DRL and equal allocation schemes with a total transmit power of 20dBm and 64 sub-arrays, respectively.

Vehicle-to-everything (V2X) technology has emerged as a key enabler of intelligent transportation systems, while the terahertz (THz) band offers abundant spectrum resources to support ultra-high-speed and low-latency V2X communications. This paper investigates the in-vehicle wireless channel at the 300 GHz band using ray-tracing (RT) simulations. A digital twin (DT) of the vehicle is constructed from high-resolution point cloud data and a measurement-based material property database. The DT is integrated into an open-source RT simulator, Sionna, to model multipath propagation. The simulation results are analyzed and compared with the measurement data, showing strong agreement and validating the feasibility of THz channel simulation. Leveraging the validated model, further wireless planning is carried out, including signal-to-interference-plus-noise ratio (SINR) analysis, coverage probability evaluation, and optimal transmitter placement. These findings provide valuable insights for the design and deployment of future THz in-vehicle communication systems.

Terahertz (THz) band ($0.1-10 \text{THz}$) possesses multi-gigahertz continuous bandwidth resources, making it a promising frequency band for high-speed wireless communications and environment sensing. The interaction between the THz wave and the external environment has been studied for various scenarios. However, it has recently been revealed that the friction forces in dust storms as well as the irradiation of sunlight and solar wind lead to the electrification of dust particles on Earth and the Moon. The THz wave propagation in these charged dust has not been fully investigated, which is essential for THz aerial communications in dust storms and lunar communications. In this paper, a channel model for THz wave propagation in charged dust is developed for wireless communications. Specifically, an extended Mie scattering model for charged dust is first introduced, which captures the electrodynamic feature of the interaction between THz wave and charged particles. Then, the diameter and density distributions of dust particles are modeled, based on which the propagation loss of THz wave in charged dust is modeled and elaborated. Finally, numerical results on the additional loss caused by these charged dust with different sizes in the THz band are evaluated and compared. Extensive results demonstrate that as the number of dust charges increases, the extinction cross section of smallersized particles significantly increases, and the overall attenuation led by charged dust increases by at most 50% at 0.3 THz.

This paper presents a new class of spatially coupled turbo-like codes (SC-TCs), namely half spatially coupled braided convolutional codes (HSC-BCCs) and half spatially coupled parallel concatenated codes (HSC-PCCs). Different from the conventional SC-TCs, the proposed codes have simpler and deterministic coupling structures. Most notably, the coupling of HSC-BCCs is performed by re-encoding the whole coupling sequence in the component encoder of one time instant, rather than spreading the coupling bits to component encoders of multiple time instants. This simplification not only addresses the window decoding threshold loss issue in existing BCCs, but also allows the proposed codes to attain very close-to-capacity performance with a coupling memory as small as 2. Both theoretical and numerical results are provided to demonstrate the performance advantages of the proposed codes over existing spatially coupled codes.

In-vehicle wireless networks hold significant promise for next-generation vehicle-to-everything (V2X) systems. Leveraging the terahertz (THz) band, with its vast untapped spectrum resources, future transportation systems could support ultrahigh-speed, low-latency applications. However, current research offers limited insights into THz band in-vehicle channel characteristics. In this paper, measurement campaigns in a passenger car across a frequency range of 290–310 GHz are conducted using a vector network analyzer (VNA)-based channel sounder. The transmitter (Tx) is mounted on the dashboard, while the receiver (Rx) is positioned at five locations within the vehicle’s seating and trunk areas, encompassing line-of-sight (LoS), obstructed line-of-sight (OLoS), and non-line-of-sight (NLoS) cases. To capture the three dimensional (3D) spatial channel profiles, a directional scanning scheme (DSS) is employed at the Rx, collecting data on both azimuth and elevation angles. The channel frequency responses (CFRs) are measured, providing power-angle-delay profile (PADP) and power-angle spectra (PAS). Based on measured data, a deterministic model for THz in-vehicle channels is subsequently proposed, where key channel parameters, such as path loss, delay spread, elevation-of-arrival (EoA) spread, and azimuth-of-arrival (AoA) spread, are calculated and analyzed. Additionally, material properties are measured using THz-TDS and cross-referenced with the reflection loss of each multipath component (MPC) in the channel measurement for material identification purposes. This study offers a foundational understanding of in-vehicle THz channels and material properties, supporting the development of high-speed, low-latency in-vehicle and V2X communication systems.

The demand for high-speed, long-range wireless communication systems has been steadily increasing, driven by the growing need for 6G and beyond networks in applications such as industry 4.0, Metaverse, holographic type communication, digital twins, etc. TeraHertz (THz) band communication has emerged as a promising solution to address these needs, offering ample bandwidth and high data rates. To extend the limited coverage and to ensure reliable and low-latency connectivity, this paper explores routing strategies for multi-hop outdoor communication within the THz band, taking into account the unique wireless channel effects associated with this frequency range, including significant path loss, interference, and scattering. A realistic channel model is developed using a hybrid modeling approach that incorporates both the randomness of the wireless channels, i.e., positions of scattering objects in the environment, and the fixed locations of terminals. By combining simulations with real-world measurement data, the performance of multihop THz communication is assessed in terms of connectivity, delay, and capacity. To overcome the limitations of THz band communication and enable longer transmission distances, innovative routing strategies are proposed for multi-hop communication. Global and local routing algorithms are proposed that jointly optimize routing based on end-to-end latency and path capacity, benchmarking them against standard methods such as the shortest path algorithm and local search techniques. Link delays and capacities are assessed using the established channel model, which is then integrated into the routing algorithms. Our approach significantly improves network performance by taking into account the unique characteristics of the THz band in outdoor applications, resulting in a 30% increase in path capacity and a 70% reduction in path delay compared to the local search method in the scenarios studied.

With multi-GHz bandwidth, Terahertz (THz) beamforming has drawn increasing attention in the sixth generation (6G) and beyond communications. Existing beamforming designs mainly focus on a compact antenna array where typical communication occurs in the far-field. However, in dense multi-user scenarios, only relying on far-field angle domain fails to distinguish users at similar angles. Therefore, a multi-user widely-spaced array (MU-WSA) is exploited in this paper, which enlarges the near-field region to introduce the additional distance domain, leading to a new paradigm of cross-near-and-far-field (CNFF) communication. Under this paradigm, the CNFF channel model is investigated, based on which the subarray spacing$d_{s}$and the number of subarrays K in MU-WSA are optimized to maximize the channel capacity. Then, in sub-connected (SC) systems, an subarray-based alternating optimization (S-AO) beamforming algorithm is proposed to deal with the special block-diagonal format of the analog precoder. For fully-connected (FC) systems, a low-complexity steering vector reconstruction (SVR)-based algorithm is proposed by constructing specialized steering vectors of MU-WSA. Numerical evaluations show that due to distance domain resolutions, the MU-WSA can improve the SE by over 60% at a power of 20 dBm compared to the compact array. Additionally, the proposed S-AO algorithm in the SC system can achieve over 80% of the sum (SE) of the FC system while reducing the number of phase shifters by$K^{2}$, thereby lowering power consumption. The SVR algorithm in the FC system can achieve over 95% of the upper bound of SE, but it takes only 10% of the running time of the singular value decomposition (SVD)-based algorithms.

Terahertz (THz) integrated sensing and communication (ISAC) enables simultaneous data transmission with Terabit-per-second (Tbps) rate and millimeter-level accurate sensing. To realize such a blueprint, ultra-massive antenna arrays with directional beamforming are used to compensate for severe path loss in the THz band. In this paper, the time-frequency-space transmit design is investigated for THz ISAC to generate time-varying scanning sensing beams and stable communication beams. Specifically, with the dynamic array-of-subarray (DAoSA) hybrid beamforming architecture and multi-carrier modulation, two ISAC hybrid precoding algorithms are proposed, namely, a vectorization (VEC) based algorithm that outperforms existing ISAC hybrid precoding methods and a low-complexity sensing codebook assisted (SCA) approach. Meanwhile, coupled with the transmit design, sensing algorithms are proposed to realize high-accuracy sensing, including a target discovery method, a wideband DAoSA MUSIC method for angle estimation and a sum-DFT-GSS approach for range and velocity estimation. Furthermore, to overcome the cyclic prefix limitation and Doppler effects, an inter-symbol interference- and inter-carrier interference-tackled sensing algorithm is developed. Numerical results indicate that the proposed sensing algorithms can realize centi-degree-level angle estimation accuracy and millimeter-level range estimation accuracy, which are one or two orders of magnitudes higher than existing methods in the millimeter-wave band.

Terahertz (THz) integrated sensing and communication (ISAC) aims to integrate novel functionalities, e.g., environmental sensing, into communication systems. Accurate channel modeling is crucial for the design and performance evaluation of future ISAC systems. This paper presents a novel hybrid channel model and a high-precision environment reconstruction framework for THz monostatic sensing. Vector network analyzer (VNA)-based channel measurements using the directional scanning sounding (DSS) scheme are performed in a laboratory environment at 300 GHz with a 20 GHz bandwidth. A low-complexity space-alternating generalized expectation-maximization (SAGE)-based algorithm is proposed to estimate the parameters of the multipath propagation components (MPCs) and to de-embed the antenna pattern. Leveraging geometric principles, the MPCs are classified into specular and diffuse components. In our proposed framework, the specular components are used for material detection and identification, while the diffuse components are leveraged to enhance geometric environment reconstruction. Demonstrations of both geometrical environment reconstruction and material identification are provided to validate the effectiveness of the proposed approach. This work offers valuable insights into THz monostatic sensing channel modeling and the design of future THz ISAC systems.

The Terahertz band (0.1-10 THz) is expected to meet Terabit-per-second (Tbps) data rate and high-precision sensing simultaneously, for which Terahertz integrated sensing and communication (THz ISAC) emerges as a promising technology for future wireless systems. However, fundamental challenges in the THz ISAC system include the severe Doppler effects due to the high carrier frequencies in the THz band. Delay-Doppler modulations such as orthogonal delay-Doppler division multiplexing (ODDM) modulation occur to overcome this challenge. In this paper, a general input/output relation of ODDM modulation is derived for the THz channel, which allows off-grid channel delay and Doppler shifts, and thus breaks the limit of sensing resolution imposed by the on-grid assumption in most existing studies. Then, a low-complexity multi-target estimation algorithm is proposed to achieve near optimal sensing accuracy. Simulation results show that the proposed algorithm is able to approach theoretical bounds and realize millimeter-level sensing. Moreover, ODDM has more reliable bit error rate performance than OFDM, especially in high Doppler spread scenarios.

Terahertz integrated sensing and communication (ISAC) is viewed as a game-changing technology to realize Terabit-per-second data rate and millimeter-level sensing in sixth-generation (6G) and beyond systems. To characterize the theo-retical performance of communication and sensing, an analytical framework for THz ISAC networks is developed by using the tool of stochastic geometry. In the presence of the blockage effects, channel fading and directional antenna radiation, the moment generating functions (MGFs) of the aggregated interference are derived. By utilizing the MGF of interference, the analytical expressions for coverage and capacity of THz ISAC networks are derived. Numerical results indicate that the coverage probabilities for THz ISAC networks are maximized at the access point (AP) density of 0.06 m-2, Moreover, it is verified that the fully-unified ISAC waveform is the most efficient scheme in contrast with frequency-division and time-division ISAC.

Terahertz (THz) communication is regarded as a key technology for 6G and beyond wireless systems due to its broad continuous bandwidth. However, the THz band suffers from a considerable propagation loss which limits the communication distance. Thanks to the submillimeter wavelength, ultra-massive multi-input multi-output (UM-MIMO) beamforming is able to enhance the received power and overcome the distance limitation. Nevertheless, hardware imperfections especially at THz frequencies, can lead to significant beamforming gain loss and degrade spectral efficiency, which are imperative to address in practical communication systems. In this paper, a user-by-user block-diagonalization (UBU-BD) algorithm in dynamic array-of-subarrays (DAoSA) architecture for multi-user UM-MIMO systems is firstly proposed under the ideal hardware assumption. Then, power losses as results of four kinds of critical hardware imperfectness, including digital-to-analog converter (DAC), analog-to-digital converter (ADC), phase shifter and switch, are modeled and evaluated. To overcome the spectral efficiency loss caused by hardware imperfectness, a switch-power algorithm is developed and assessed. Simulation results show that combinations of extra switches and transmit power are helpful to fully compensate for the spectral efficiency losses.

Terahertz (THz) wireless communications have the potential to realize ultra-high-speed data transfer with miniaturized devices for unmanned aerial vehicle (UAV) communications. Existing THz UAV channel models assume a homogeneous medium along the propagation path. However, the atmospheric turbulence due to random airflow leads to temporal and spatial inhomogeneity of the communication medium, motivating the analysis and modeling of the influence of atmospheric turbulence on $\mathbf{T H z}$ wave propagation. In this paper, we statistically modeled the attenuation effect of turbulence on THz UAV channels. Specifically, the refractive index structure constant, as a critical statistical parameter characterizing the influence of turbulence on channel medium, is first investigated. Then, the scintillation characteristic and attenuation of the THz communications caused by atmospheric turbulence are modeled, where the scintillation effect is characterized by a Gamma-Gamma distribution, and the turbulence attenuation as a function of altitude and frequency is derived. Numerical simulations on the refractive index structure constant, scintillation, and attenuation in the THz band are presented to quantitatively analyze the influence of turbulence for THz UAV channels. It is discovered that THz turbulence can lead to at most 10 dB attenuation with frequency less than 1 THz and distance less than $10 \mathbf{k m}$.

The Terahertz band, spanning from 0.1 THz to 10 THz, is envisioned as a key technology to realize ultrahigh data rates in the 6 G and beyond mobile communication systems, due to its abundant bandwidth resource. However, to realize $\mathbf{T H z}$ communications, one substantial step is to fully understand the THz channels, which relies on extensive channel measurements. In this paper, using a correlation-based time domain channel sounder, measurement campaigns are conducted in a laboratory at 140 GHz and 220 GHz. In the data postprocessing procedures, the time drift of clock signals is corrected using a linear interpolation/extrapolation method. Based on the measured results, the main objects that provide significant oncescattering clusters are found, based on which the scattering losses are calculated and analyzed. Furthermore, the channel characteristics, including path loss, shadow fading, K-factor, etc. are calculated and compared to 3GPP standard values. The propagation analysis and channel characteristics are helpful to study channel modeling and guide system design for $\mathbf{T H z}$ communications.

The Terahertz band, ranging from 0.1 THz to 10 THz, is envisioned as a key technology to realize ultra-high-speed communications in 6G and beyond wireless networks, attributed to its abundant bandwidth resource. Channel measurements and link-level analysis are still missing in a typical use case of THz picocells. In this paper, using a correlation-based time domain channel sounder, channel measurement campaigns are conducted on a university street at 220 GHz. Based on the measurement results, a full portrait of channel characteristics, including path loss, shadow fading, K-factor, delay and angular spreads, as well as cluster parameters, is calculated and analyzed. Comparison with existing 3GPP standard models shows weak multipath effects and strong sparsity in the THz picocell scenario. Moreover, small-scale fading is evaluated and fitted, where a Rician distribution among other competitors shows great fitting performance. Furthermore, considering realistic THz communication links, the ergodic capacity and outage probability are analyzed. Results have shown that more than 150 Gbps channel capacity can be achieved and reliable communication links can be guaranteed for coverage up to 40 m in the THz picocell. The results and analysis in this work offer guidance for effective system design for future THz picocell communications.

Emerging from the symbiotic combination of nanotechnology and communications, the field of nanonetworking has come a long way since its inception more than fifteen years ago. Significant progress has been achieved in several key communication technologies as enablers of the paradigm, as well as in the multiple application areas that it opens. In this paper, the focus is placed on the electromagnetic nanonetworking paradigm, providing an overview of the advances made in wireless nanocommunication technology from microwave through terahertz to optical bands. The characteristics and potential of the compared technologies are then confronted with the requirements and challenges of the broad set of nanonetworking applications in the Internet of NanoThings (IoNT) and on-chip networks paradigms, including quantum computing applications for the first time. Finally, a selection of cross-cutting issues and possible directions for future work are given, aiming to guide researchers and practitioners towards the next generation of electromagnetic nanonetworks.

Nanotechnology is enabling the development of devices on a scale ranging from one to a few hundred nanometers. At this scale, a nanomachine is defined as the most basic functional unit, integrated by nano-components which can carry out sensing and actuation. Coordination and information communication among several nanomachines expand the potential applications of individual devices both in terms of complexity and range of operation. The resulting nanonetworks can cover wide areas, to reach unprecedented locations in a non-invasive way. Moreover, the integration of nanonetworks with classical networks and ultimately with the Internet results in a new networking paradigm, which is referred to as the Internet of Nano-Things (IoNT) by Akyildiz and Jornet one and a half decades ago.

Supporting ultra-high data rates and flexible reconfigurability, Terahertz (THz) mesh networks are attractive for next-generation wireless backhaul systems that empower the integrated access and backhaul (IAB). In THz mesh backhaul networks, the efficient cross-layer routing and long-term resource allocation is yet an open problem due to dynamic traffic demands as well as possible link failures caused by the high directivity and high non-line-of-sight (NLoS) path loss of THz spectrum. In addition, unpredictable data traffic and the mixed integer programming property with the NP-hard nature further challenge the effective routing and long-term resource allocation design. In this paper, a deep reinforcement learning (DRL) based cross-layer design in THz mesh backhaul networks (DEFLECT) is proposed, by considering dynamic traffic demands and possible sudden link failures. In DEFLECT, a heuristic routing metric is first devised to facilitate resource efficiency (RE) enhancement regarding energy and sub-array usages. Furthermore, a DRL based resource allocation algorithm is developed to realize long-term RE maximization and fast recovery from broken links. Specifically in the DRL method, the exploited multi-task structure cooperatively benefits joint power and sub-array allocation. Additionally, the leveraged hierarchical architecture realizes tailored resource allocation for each base station and learned knowledge transfer for fast recovery. Simulation results show that DEFLECT routing consumes less resource, compared to the minimal hop-count metric. Moreover, unlike conventional DRL methods causing packet loss and second-level latency, DEFLECT DRL realizes the long-term RE maximization with no packet loss and millisecond-level latency, and recovers resource-efficient backhaul from broken links within 1s.

Ultra-massive multiple-input multiple-output (UM-MIMO) is the enabler of Terahertz (THz) communications in next-generation wireless networks. In THz UM-MIMO systems, a new paradigm of cross-field communications spanning from near-field to far-field is emerging, since the near-field range expands with higher frequencies and larger array apertures. Precise beam alignment in cross-field is critical but challenging. Specifically, unlike far-field beams that rely only on the angle domain, the incorporation of dual-domain (angle and distance) training significantly increases overhead. A natural question arises of whether far-field beam training can be deployed for cross-field beam alignment. In this paper, this question is answered, by demonstrating that the far-field training enables sufficient signal-to-noise ratio (SNR) in both far- and near-field scenarios, while exciting all channel dimensions. Based on that, we propose a subarray-coordinated hierarchical (SCH) training with greatly reduced overhead. To further obtain high-precision beam designs, we propose a two-phase angle and distance beam estimator (TPBE). Extensive simulations demonstrate the effectiveness of the proposed methods. Compared to near-field exhaustive search, the SCH possesses 0.2% training overhead. The TPBE achieves 0.16 degrees and 0.01 meters estimation root-mean-squared errors for angle and distance. Furthermore, with the estimated beam directions, a near-optimal SNR with 0.3 dB deviation is attained after beam alignment.

Terahertz (THz) communications are envisioned as a promising technology for sixth-generation (6G) and beyond systems, owing to its unprecedented multi-gigahertz (GHz) bandwidth. In this paper, channel measurement campaigns in indoor scenarios at low-THz frequencies, i.e., 201-209 GHz, are reported. Four different communication scenarios including 90 transmitter-receiver pairs are measured in two channel measurement campaigns of a meeting room and an office room, respectively. The two measurement campaigns contains four scenarios, namely, a meeting room, cubicle area, hallway and non-line-of-sight (NLoS) case. The propagation of multi-path components (MPCs) in the four scenarios is characterized by the power-delay-angular profiles. Based on them, the temporal and spatial consistency for varying receiver locations in the complex hallway and NLoS scenarios are verified. To characterize, the large-scale best-direction and omni-directional path losses in indoor scenarios are separately analyzed and modeled by the close-in (CI) model. Furthermore, the small-scale channel parameters, e.g., the number of clusters, delay spread, angular spread, and cluster time-of-arrival are analyzed and modeled by proper distributions. As a general framework, a ray-tracing-statistical hybrid model is proposed for wireless propagation at 201-209 GHz, although, admittedly, the measurement results and analysis reveal that the channel characteristics in various indoor scenarios exhibit noticeable differences that need tailored parameter settings.

Terahertz (THz) wireless communications have the potential to realize ultra-high-speed and secure data transfer with miniaturized devices for unmanned aerial vehicle (UAV) communications. The atmospheric turbulence due to random airflow leads to spatial inhomogeneity of the communication medium, which is yet missing in most existing studies, leading to additional propagation loss and even loss of spatial coherence (LoSC) in MIMO systems. In this paper, the attenuation and loss of spatial coherence for atmospheric turbulence are modeled in THz UAV MIMO channels. Specifically, the frequency- and altitude-dependency of the refractive index structure constant (RISC), as a critical statistical parameter characterizing the intensity of turbulence, is first investigated. Then, the LoSC, fading, and attenuation caused by atmospheric turbulence are modeled, where the turbulence-induced fading is modeled by a Gamma-Gamma distribution, and the turbulence attenuation as a function of altitude and frequency is derived. Numerical results show that the turbulence leads to at most 10 dB attenuation with frequency less than 1 THz and distance less than 10 km. Furthermore, when the distance is 10 km and the RISC is 10-9m-2/3, the loss of spatial coherence effect leads to 10 dB additional loss for a 1024 × 1024 ultra-massive MIMO system.

Reconfigurable intelligent surface (RIS) has drawn extensive attentions as a promising alternative for classical phased-array antennas at the massive multiple-input multiple-output (MIMO) transmitter, leading to cost-effective data transmission that is especially desirable at terahertz (THz) frequencies. In this article, we consider a multi-user MIMO (MU-MIMO) system equipped with a RIS-assisted transmitter: A RIS array is illuminated by unmodulated THz carriers through a feeding antenna, which is equally divided into a number of subarrays (SAs). Each activated SA serves one unique user equipment (UE) via directional beams. Then we develop a spectrum- and energy- efficient MU-MIMO scheme for THz communications by performing index modulation (IM) on the array-of-SA structure of the RIS, abbreviated as RIS-SA-IM. Specifically, the indices of the RIS-SAs allocated to different UEs, defined as SA allocation pattern (SAPs), are flexibly controlled by the information bits at each symbol period. Hence, aside from classical amplitude/phase modulation, additional energy-free bits (referred to asindex bits) can be conveyed implicitly by the chosen SAP at the transmitter, thus attaining superior enhancement on spectrum- and energy-efficiencies. Furthermore, we design a distributed mapping rule between the SAPs and index bits, which guarantees that the index information for each UE is exclusively determined by the index of its allocated RIS-SA. Hence, the proposed mapping rule can enable localized demodulation of the index bits without inter-UE data exchange. In particular, a general form of the distributed mapping rule is provided based on the binary-tree structure, which can be extended to arbitrary number of UEs and index bits. Additionally, the error performance of the proposed RIS-SA-IM is evaluated through pairwise error probability (PEP) calculations. Theoretical and simulation results demonstrate the superiority of our proposed RIS-SA-IM over its classical non-IM-aided counterpart.

Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) systems are promising in enabling next-generation wireless communications, offering high data rates with tens of GHz of continuous bandwidth and high spectral efficiency. In THz UM-MIMO systems, a new paradigm of cross-field communications is emerging, since THz transmission distances span from near-field to far-field. To achieve the benefits of THz UM-MIMO, precise beam alignment implemented through beam training or beam scanning is required. However, different from the traditional far-field alignment in the angle domain, the near-field angle and distance alignment should be considered in the cross-field. The additional distance domain searching brings higher training overhead and thus limits the system's performance. In this paper, a far-field training with estimation (FTE) framework for cross-field beam alignment is proposed. The far-field training enables the received signal-to-noise ratio (SNR) in both the far- and near-field for successful control signal reception. Moreover, a three-phase beam estimator (TPBE) is proposed for high-precision alignment. Extensive simulations demonstrate the effectiveness of the proposed methods. Specifically, the FTE possesses a near-optimal signal-to-noise ratio with only 0.5 dB deviation, with 3.3% training overhead and low complexity compared to near-field exhaustive search.

Owning abundant bandwidth resource, the Tera-hertz (0.1-10 THz) band is a promising spectrum to support sixth-generation (6G) and beyond communications. As the foundation of channel study in the spectrum, channel measurement is ongoing in covering representative 6G communication scenarios and promising THz frequency bands. In this paper, a wideband channel measurement in an L-shaped university campus street is conducted at 306–321 GHz and 356–371 GHz. In particular, ten line-of-sight (LoS) and eight non-line-of-sight (NLoS) points are measured at the two frequency bands, respectively. In total, 6480 channel impulse responses (CIRs) are obtained from the measurement, based on which multi-path propagation in the L-shaped roadway in the THz band is elaborated to identify major scatterers of walls, vehicles, etc. in the environment and their impact on multi-path components (MPCs). Furthermore, outdoor THz channel characteristics in the two frequency bands are analyzed, including path losses, shadow fading, cluster pa-rameters, delay spread and angular spread. In contrast with the counterparts in the similar outdoor scenario at lower frequencies, the results verify the sparsity of MPCs at THz frequencies and indicate smaller power spreads in both temporal and spatial domains in the THz band.

Providing links of rate over 100 Gbps and high energy density at the receiver, Terahertz (THz) simultaneous wireless information and power transfer (SWIPT) has huge potential to support the functionality of Internet of things (IoT) including distributed sensor networks and mobile robot systems. In this paper, a THz SWIPT system with ultra-massive MIMO (UM-MIMO) is proposed based on power splitting structure. By utilizing electromagnetic (EM) analysis, approximated closed-form expressions for energy distribution are derived to characterize the achievable rate and harvested energy of THz SWIPT system. Furthermore, the impact of finite-resolution phase shifter (FRPS) is analyzed, which cause the decline of energy density at the receiver and thus received power. Simulation results are provided to validate the derivations and demonstrate that decline of received power caused by FRPS can be locally compensated by increasing the inter-element spacing of antenna arrays. Moreover, compared with SWIPT at 1 THz and SWIPT at 28 GHz, SWIPT at 300 GHz balances the achievable rate and the harvested power, which allows the user to achieve rate of 200 Gbps and harvest power over 0.01 mW simultaneously.

The Terahertz (0.1-10 THz) band has been envisioned as one of the promising spectrum bands to support ultra-broadband sixth-generation (6G) and beyond communications. In this paper, a wideband channel measurement campaign in a 500-square-meter indoor lobby at 306-321 GHz is presented. The measurement system consists of a vector network analyzer (VNA)-based channel sounder, and a directional antenna equipped at the receiver to resolve multi-path components (MPCs) in the angular domain. In particular, 21 positions and 3780 channel impulse responses (CIRs) are measured in the lobby, including the line-of-sight (LoS), non-line-of-sight (NLoS) and obstructed-line-of-sight (OLoS) cases. The multi-path characteristics are summarized as follows. First, the main scatterers in the lobby include the glass, the pillar, and the LED screen. Second, best direction and omnidirectional path losses are analyzed. Compared with the close-in path loss model, the optimal path loss offset in the alpha-beta path loss model exceeds 86 dB in the LoS case, and accordingly, the exponent decreases to 1.57 and below. Third, more than 10 clusters are observed in OLoS and NLoS cases, compared to 2.17 clusters on average in the LoS case. Fourth, the average power dispersion of MPCs is smaller in both temporal and angular domains in the LoS case, compared with the NLoS and OLoS counterparts. Finally, in contrast to hallway scenarios measured in previous works at the same frequency band, the lobby which is larger in dimension and square in shape, features larger path losses and smaller delay and angular spreads.

Terahertz (THz) communications are envisioned as a key technology of next-generation wireless systems due to its ultra-broad bandwidth. One step forward, THz integrated sensing and communication (ISAC) system can realize both unprecedented data rates and millimeter-level accurate sensing. However, THz ISAC meets stringent challenges on waveform and receiver design to fully exploit the peculiarities of THz channel and transceivers. In this work, a sensing integrated discrete Fourier transform spread orthogonal frequency division multiplexing (SI-DFT-s-OFDM) system is proposed for THz ISAC, which can provide lower peak-to-average power ratio than OFDM and is adaptive to flexible delay spread of the THz channel. Without compromising communication capabilities, the proposed SI-DFT-s-OFDM realizes millimeter-level range estimation and decimeter-per-second-level velocity estimation accuracy. In addition, the bit error rate (BER) performance is improved by 5 dB gain at the 10°3 BER level compared with OFDM. At the receiver, a deep learning based ISAC receiver with two neural networks is developed to recover transmitted data and estimate target range and velocity, while mitigating the imperfections and non-linearities of THz systems. Extensive simulation results demonstrate that the proposed deep learning methods can realize mutually enhanced performance for communication and sensing, and is robust against Doppler effects, phase noise and multi-target estimation.

Integrated ultra-massive multiple-input multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems are promising for 6G and beyond Terahertz (0.1-10 THz) communications, to effectively bypass the barriers of limited coverage and line-of-sight blockage. However, excessive dimensions of UM-MIMO and IRS enlarge the near-field region, while strong THz channel sparsity in the far-field is detrimental to spatial multiplexing. Moreover, channel estimation (CE) requires recovering the large-scale channel from severely compressed observations due to limited RF-chains. To tackle these challenges, a hybrid spherical- and planar-wave channel model (HSPM) is introduced for the cascaded channel of the integrated system. The spatial multiplexing gains under near-field and far-field regions are analyzed, which are found to be limited by the segmented channel with a lower rank. Furthermore, a compressive sensing-based CE framework is developed, including a sparse channel representation method, a separate-side estimation (SSE) and a dictionary-shrinkage estimation (DSE) algorithms. Numerical results verify the effectiveness of the HSPM, the capacity of which is only$5\times 10^{-4}$bits/s/Hz deviated from that obtained by the ground-truth spherical-wave-model, with 256 elements. While the SSE achieves improved accuracy for CE than benchmark algorithms, the DSE is more attractive in noisy environments, with 1 dB lower normalized-mean-square error than SSE.

Millimeter-wave (mmWave) and Terahertz (THz)-band communications exploit the abundant bandwidth to fulfill the increasing data rate demands of 6G wireless communications. To compensate for the high propagation loss with reduced hardware costs, ultra-massive multiple-input multiple-output (UM-MIMO) with a hybrid beamforming structure is a promising technology in the mmWave and THz bands. However, channel estimation (CE) is challenging for hybrid UM-MIMO systems, which requires recovering the high-dimensional channels from severely few channel observations. In this paper, a Pruned Approximate Message Passing (AMP) Integrated Deep Convolutional-neural-network (DCNN) CE (PRINCE) method is firstly proposed, which enhances the estimation accuracy of the AMP method by appending a DCNN network. Moreover, by truncating the insignificant feature maps in the convolutional layers of the DCNN network, a pruning method including training with regularization, pruning and refining procedures is developed to reduce the network scale. Simulation results show that the PRINCE achieves a good trade-off between the CE accuracy and significantly low complexity, with normalized-mean-square-error (NMSE) of −10 dB at signal-to-noise-ratio (SNR) as 10 dB after eliminating 80% feature maps.

Reconfigurable intelligent surfaces (RISs) have emerged as a prospective technology for next-generation wireless networks due to their potential in coverage and capacity enhancement. Previous works on achievable rate analysis of RIS-assisted communication systems have mainly focused on the rich-scattering environment where Rayleigh and Rician channel models can be applied. This work studies the ergodic achievable rate of RIS-assisted multiple-input multiple-output communication systems in the millimeter-wave band with limited scattering under the Saleh-Valenzuela channel model. Firstly, we derive an upper bound of the ergodic achievable rate by means of majorization theory and Jensen’s inequality. The upper bound shows that the ergodic achievable rate increases logarithmically with the number of antennas at the base station (BS) and user, the number of the reflection units at the RIS, and the eigenvalues of the steering matrices associated with the BS, user and RIS. Then, we aim to maximize the ergodic achievable rate by jointly optimizing the transmit covariance matrix at the BS and the reflection coefficients at the RIS. Specifically, the transmit covariance matrix is optimized by the water-filling algorithm and the reflection coefficients are optimized using the Riemannian conjugate gradient algorithm. Simulation results validate the effectiveness of the proposed optimization algorithms.

Terahertz (THz) integrated sensing and communication (ISAC) is a promising interdisciplinary technology that realizes simultaneously transmitting Terabit-per-second (Tbps) and millimeter-level accurate environment or human activity sensing. However, both communication performance and sensing accuracy are influenced by the Doppler effects, which are especially severe in the THz band. Moreover, peak-to-average power ratio (PAPR) degrades the THz power amplifier (PA) efficiency. In this paper, a discrete Fourier transform spread orthogonal time frequency space (DFT-s-OTFS) system with superimposed pilots is proposed to improve the robustness to Doppler effects and reduce PAPR for THz ISAC. Then, a two-phase sensing parameter estimation algorithm is developed to integrate sensing functionality into the DFT-s-OTFS waveform. Meanwhile, a low-complexity iterative channel estimation and data detection method with a conjugate gradient based equalizer is proposed to recover the data symbols of DFT-s-OTFS. The proposed DFT-s-OTFS waveform can improve the PA efficiency by 10% on average compared to OTFS. Simulation results demonstrate that the proposed two-phase sensing estimation algorithm for THz DFT-s-OTFS systems is able to realize millimeter-level range estimation accuracy and decimeter-per-second-level velocity estimation accuracy. Moreover, the effectiveness of the iterative method for data detection aided by superimposed pilots in DFT-s-OTFS systems is validated by the simulations and the bit error rate performance is not degraded by the Doppler effects.

Terahertz (THz) communications are regarded as a pillar technology for the 6G systems, by offering multi-ten-GHz bandwidth. To overcome the huge propagation loss, THz ultra-massive MIMO systems with hybrid beamforming are proposed to offer high array gain. Notably, the adjustable phase shifters considered in most existing hybrid beamforming studies are power-hungry and difficult to realize in the THz band. Moreover, due to the ultra-massive antennas, full channel-state-information (CSI) is challenging to obtain. To address these practical concerns, in this paper, an energy-efficient dynamic-subarray with fixed phase shifters (DS-FPS) architecture is proposed for THz hybrid beamforming. To compensate for the spectral efficiency loss caused by the fixed phase of FPS, a switch network is inserted to enable dynamic connections. In addition, by considering the partial CSI, we propose a row-successive-decomposition (RSD) algorithm to design the hybrid beamforming matrices for DS-FPS. A row-by-row (RBR) algorithm is further proposed to reduce the computational complexity. Extensive simulation results show that, the proposed DS-FPS architecture with the RSD and RBR algorithms achieves much higher energy efficiency than the existing architectures. Moreover, the spectral efficiency of the DS-FPS architecture with the proposed algorithms is robust to the CSI error.

The Terahertz (0.1-10 THz) band wireless data center networks (DCNs) are promising to provide high data rates and low latency for next-generation cloud applications. However, one research gap that is still existed is the lack of measurement data and thorough characterization of the THz wave propagation in data centers. To address this problem, in this paper, two sets of measurement campaigns are conducted in a data center scenario at 130–140 GHz band, by using a vector network analyzer (VNA)-based channel sounder system with different receiver heights. The measured data is further processed to extract the multi path components (MPCs) and classify the MPCs into clusters. Furthermore, the channel characteristics, including the path loss, shadow fading, K-factor, delay and angular spreads are calculated and analyzed. Clustering results and MPCs propagation are analyzed and examined in light of the real geometry in the data center. Interestingly, comparison with measured results in meeting room scenarios at 140 GHz shows that the reflections and scattering from metal racks in the data center are more significant, resulting in lower path loss, smaller K-factor, and larger delay spreads. The measured results in this work substantiate guidelines for system design of THz wireless DCNs.

Terahertz (0.1-10 THz) communications are envisioned as a key technology for 6G ultra-high-speed wireless systems, by offering an ultra-broad bandwidth. Integrated ultramassive multiple-input multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems are promising for THz communications, to effectively bypass the barrier of limited coverage and line-of-sight blockage. Two challenges arise. First, the huge dimension of the antenna array in UM-MIMO and IRS in contrast with the sub-millimeter wavelength enlarge the nearfield region. Second, strong channel sparsity in THz channels could be detrimental to spatial multiplexing gain and thereby capacity. In this work, a hybrid spherical- and planar-wave channel model (HSPM) is developed for the cascaded channel of the THz integrated UM-MIMO and IRS system. Furthermore, the spatial multiplexing gain under near-field and far-field cases are analyzed, which is proved to be limited by the segment of the cascaded channel with a lower rank, and can be improved based on the widely-space architecture design of UM-MIMO and IRS. Performance evaluation reveals that the proposed HSPM can accurately capture the propagation features of the THz integrated UM-MIMO and IRS system. Numerically, when the array size is 256, the capacity based on the HSPM is only 3 × 10−4bits/s/Hz less than that obtained by the ground-truth spherical-wave model.

The TeraHertz (THz) band, spanning the spectrum from 0.1 THz to 10 THz, is envisioned as a key technology in the next generation mobile communication systems. However, the much higher frequencies in the THz band prevents the effective utilization of channel models dedicated for microwave or millimeter-wave frequency bands. To address this problem, numerous measurement campaigns are needed to fully investigate the characteristics of the THz channels. In this paper, a measurement campaign is conducted in an indoor corridor scenario at 306-321 GHz with a frequency-domain Vector Network Analyzer (VNA)-based sounder. The measured data are further processed to obtain the channel impulse response (CIR) and power-delay-angle profile (PDAP), based on which the multipath components (MPCs) are further extracted. Furthermore, the MPCs are clustered using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and the clusters are matched with propagation paths by considering the real geometry. Moreover, the channel characteristics, including the path loss, delay spread, angular spreads, and cluster parameters are calculated and analyzed. The resulting numerology is helpful to guide system design for THz communications.

We propose a new spectrum allocation strategy for terahertz (THz) band communication (THzCom) systems. Specifically, we design multi-band-based spectrum allocation with adaptive sub-band bandwidth (ASB), by allowing to divide the spectrum of interest into sub-bands with unequal bandwidths. Due to the frequency and distance-dependent nature of the molecular absorption loss, the variation in this loss between the sub-bands would be very high at the THz band when equal sub-band bandwidth (ESB) is considered, as in the literature. The proposed strategy reduces this variation by allowing changes in the sub-band bandwidth, which leads to an overall improvement in the data rate performance. To study the impact of our strategy, we formulate an optimization problem, with the main focus on spectrum allocation, to determine the optimal sub-band bandwidth and transmit power. Thereafter, we propose reasonable approximations and transformations to solve the formulated problem. Aided by numerical results, we show that by enabling and optimizing ASB, a significantly higher data rate can be achieved by our strategy, compared to adopting ESB, and it is more beneficial to adopt ASB when the spectrum with the highest average molecular absorption loss within the THz transmission window is selected during spectrum allocation.

The TeraHertz (THz) band (0.1-10 THz), which supports terabit-per-second (Tbps) data rates, has been envisioned as one of the promising spectrum bands for ultra-broadband sixth-generation (6G) communications. In this paper, an angular-resolvable ultra-wideband channel measurement campaign in an indoor L-shaped hallway at 306-321 GHz is presented, by using a frequency-domain vector network analyzer (VNA)-based channel sounder. In particular, four points in the line-of-sight (LoS) case and nine points in the non-line-of-sight (NLoS) case are measured, with a directional antenna equipped at the receiver (Rx) side to resolve multi-path components (MPCs) in the angular domain. The multi-path propagation in the L-shaped hallway in the THz band is elaborated in terms of power delay angular profiles (PDAPs), based on the multi-path component distance (MCD)-based Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. Indoor THz channel characteristics are analyzed in depth. Specifically, the path loss exponents (PLEs) of the LoS case are 1.7222 for the best direction and 1.3910 for the omni-directional path losses. Moreover, in the LoS case, the average logarithmic values of root-mean-square (RMS) delay spread (DS) and azimuth spread of angle (ASA) are -7.7464 and 1.52, while the NLoS case yields larger average RMS DS and ASA of -7.5501 and 1.68, respectively. Besides, the cluster delay difference follows an exponential distribution, for which the average values of cluster delay difference are 37.15 ns in the LoS and 22.59 ns in the NLoS case.

Terahertz (THz) integrated sensing and communication (ISAC) is a promising interdisciplinary technology that realizes simultaneously transmitting Terabit-per-second (Tbps) and millimeter-level accurate environment or human activity sensing. However, both communication performance and sensing accuracy are influenced by the Doppler effects and peak-to-average power ratio (PAPR), which are especially severe in the THz band. In this paper, a discrete Fourier transform spread orthogonal time frequency space (DFT-s-OTFS) system for THz ISAC is proposed with a two-stage sensing parameter estimation algorithm. The proposed sensing algorithm can realize millimeter-level range estimation accuracy and decimeter-per-second velocity estimation accuracy. Moreover, the proposed DFT-s-OTFS can improve the power amplifier efficiency by 10% on average compared to OTFS and enhance the sensing accuracy by one order of magnitude and the bit error rate performance by two orders of magnitude in high-mobility scenarios in contrast with orthogonal frequency division multiplexing (OFDM) and discrete Fourier transform spread OFDM (DFT-s-OFDM).

The quality of experience (QoE) requirements of wireless virtual reality (VR) can only be satisfied with high data rate, high reliability, and low VR interaction latency. This high data rate over short transmission distances may be achieved via the abundant bandwidth in the terahertz (THz) band. However, THz waves experience severe signal attenuation, which may be compensated by the reconfigurable intelligent surface (RIS) technology with programmable reflecting elements. Meanwhile, the low VR interaction latency can be achieved with the mobile edge computing (MEC) network architecture due to its computation capabilities. Motivated by these considerations, in this paper, we propose an MEC-enabled and RIS-assisted THz VR network in an indoor scenario, by taking into account the uplink viewpoint prediction and position transmission, the MEC rendering, and the downlink transmission. We propose two methods, which are referred to as centralized online gated recurrent unit (GRU) and distributed federated averaging (FedAvg), to predict the viewpoints of the VR users. In the uplink, an algorithm that integrates online long-short term memory (LSTM) and convolutional neural networks (CNN) is deployed to predict the locations and the line-of-sight and non-line-of-sight statuses of the VR users over time. In the downlink, we develop a constrained deep reinforcement learning algorithm to select the optimal phase shifts of the RIS under latency constraints. Simulation results show that our proposed learning architecture achieves near-optimal QoE as that of the genie-aided benchmark algorithm, and about two times improvement in QoE compared to the random phase shift selection scheme.

Hybrid beamforming for Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) systems is a promising technology for 6G space-air-ground integrated networks, which can overcome huge propagation loss and offer unprecedented data rates. With ultra-wide bandwidth and ultra-large-scale antennas array in THz band, the beam squint becomes one of the critical problems which could reduce the array gain and degrade the data rate substantially. However, the traditional phase-shifters-based hybrid beamforming architectures cannot tackle this issue due to the frequency-flat property of the phase shifters. In this paper, to combat the beam squint while keeping high energy efficiency, a novel dynamic-subarray with fixed true-time-delay (DS-FTTD) architecture is proposed. Compared to the existing studies which use the complicated adjustable TTDs, the DS-FTTD architecture has lower power consumption and hardware complexity, thanks to the low-cost FTTDs. Furthermore, a low-complexity row-decomposition (RD) algorithm is proposed to design hybrid beamforming matrices for the DS-FTTD architecture. Extensive simulation results show that, by using the RD algorithm, the DS-FTTD architecture achieves near-optimal array gain and significantly higher energy efficiency than the existing architectures. Moreover, the spectral efficiency of DS-FTTD architecture with the RD algorithm is robust to the imperfect channel state information.

Terahertz (THz) band communications are envisioned as a key technology for 6G and Beyond. As a fundamental wireless infrastructure, THz communication can boost abundant promising applications. In 2014, our team published two comprehensive roadmaps for the development and progress of THz communication networks, which helped the research community to start research on this subject afterwards. The topic of THz communications became very important and appealing to the research community due to 6G wireless systems design and development in recent years. Many papers are getting published covering different aspects of wireless systems using the THz band. With this paper, our aim is looking back to the last decade and revisiting the old problems and pointing out what has been achieved in the research community so far. Furthermore, in this paper, open challenges and new research directions still to be investigated for the THz band communication systems are presented, by covering diverse topics ranging from devices, channel behavior, communication and networking, to physical testbeds and demonstration systems. The key aspects presented in this paper will enable THz communications as a pillar of 6G and Beyond wireless systems in the next decade.

The convergence of radar sensing and communication applications in the millimeter-wave (mmWave) and low terahertz (THz) bands has been envisioned as a promising technology, since it incorporates high-rate data transmission of hundreds of gigabits per second (Gbps) and mm-level radar sensing in a spectrum- and cost-efficient manner, by sharing both the frequency and hardware resources. However, the joint radar sensing and communication (JRC) system faces considerable challenges in the mmWave and low-THz scale, due to the peculiarities of the propagation channel and radio-frequency (RF) front ends. To this end, the waveform design for the JRC systems in mmWave and low-THz bands with ultra-broad bandwidth is investigated in this paper. Firstly, by considering the JRC design based on the co- existence concept, where both functions operate in a time-domain duplex (TDD) manner, a novel multi-subband quasi-perfect (MS-QP) sequence, composed of multiple perfect subsequences on different subbands, is proposed for target sensing, which achieves accurate target ranging and velocity estimation, whilst only requiring cost-efficient low-rate analog-to-digital converters (A/Ds) for sequence detection. Furthermore, the root index of each perfect subsequence is designed to eliminate the influence of strong Doppler shift on radar sensing. Finally, a data-embedded MS-QP (DE-MS-QP) waveform is constructed through time-domain extension of the MS-QP sequence, generating null frequency points on each subband for data transmission. Unlike the co- existence-based JRC system in TDD manner, the proposed DE-MS-QP waveform enables simultaneous interference-free sensing and communication, whilst inheriting all the merits from MS-QP sequences. Numerical results validate the superiority of the proposed waveforms regarding the communication and sensing performances, hardware cost as well as flexibility of the resource allocation between the dual functions.

We study spectrum allocation for terahertz (THz) band communication (THzCom) systems, while considering the frequency and distance-dependent nature of THz channels. Different from existing studies, we explore multi-band-based spectrum allocation with adaptive sub-band bandwidth (ASB) by allowing the spectrum of interest to be divided into sub-bands with unequal bandwidths. Also, we investigate the impact of sub-band assignment on multi-connectivity (MC) enabled THzCom systems, where users associate and communicate with multiple access points simultaneously. We formulate resource allocation problems, with the primary focus on spectrum allocation, to determine sub-band assignment, sub-band bandwidth, and optimal transmit power. Thereafter, we propose reasonable approximations and transformations, and develop iterative algorithms based on the successive convex approximation technique to analytically solve the formulated problems. Aided by numerical results, we show that by enabling and optimizing ASB, significantly higher throughput can be achieved as compared to adopting equal sub-band bandwidth, and this throughput gain is most profound when the power budget constraint is more stringent. We also show that our sub-band assignment strategy in MC-enabled THzCom systems outperforms the state-of-the-art sub-band assignment strategies and the performance gain is most profound when the spectrum with the lowest average molecular absorption coefficient is selected during spectrum allocation.

Terahertz (THz) communications with multi-GHz bandwidth are envisioned as a key technology for 6G systems. Ultra-massive (UM) MIMO with hybrid beamforming architectures are widely investigated to provide a high array gain to overcome the huge propagation loss at THz band. However, most of the existing hybrid beamforming architectures can only utilize the multiplexing offered by the multipath components, i.e., inter-path multiplexing, which is very limited due to the spatially sparse THz channel. In this paper, a widely-spaced multi-subarray (WSMS) hybrid beamforming architecture is proposed, which improves the multiplexing gain by exploiting a new type of intra-path multiplexing provided by the spherical-wave propagation among$k$widely-spaced subarrays, in addition to the inter-path multiplexing. The resulting multiplexing gain of WSMS architecture is$k$times of the existing architectures. For WSMS architecture, a novel design problem is formulated by optimizing the number of subarrays, subarray spacing, and hybrid beamforming matrices to maximize the spectral efficiency, which is decomposed into two subproblems. An optimal closed-form solution is derived for the first hybrid beamforming subproblem, while a dominant-line-of-sight-relaxation algorithm is proposed for the second array configuration subproblem. Extensive simulation results demonstrate that the WSMS architecture and proposed algorithms enhance the spectral efficiency substantially.

We propose a cluster-based multi-carrier beam division multiple access (MC-BDMA) scheme to enable massive device terahertz (THz) communications with the dynamic-subarray hybrid beamforming (HBF) architecture. This scheme is motivated by a limitation of conventional HBF architectures, i.e., the number of users cannot exceed the number of radio frequency (RF) chains. By exploiting the unique properties of THz channels, such as high distance-and-frequency dependence, high sparsity, and small angular spread, we propose multiple users in the same cluster to be supported by a single RF chain with distance-aware multi-carrier modulation. Moreover, we propose different clusters to be divided by BDMA that is accomplished through HBF design. In our proposed scheme, we first design a novel antenna selection and subarray partition algorithm for the dynamic-subarray HBF architecture to compensate for performance loss caused by diverse channels among users. We then design an algorithm for multi-carrier HBF which maximizes the achievable throughput and eliminates the inter-beam interference. Numerical results show that our proposed cluster-based MC-BDMA scheme with the dynamic-subarray HBF architecture provides an almost 100% spectral efficiency gain and a 60% energy efficiency gain over the conventional non-cluster HBF scheme in massive device communications.

Terahertz (0.1-10 THz) wireless communications are expected to meet 100+ Gbps data rates for 6G communications. Being able to combat the distance limitation with reduced hardware complexity, ultra-massive multiple-input multiple-output (UM-MIMO) systems with hybrid dynamic array-of-subarrays (DAoSA) beamforming are a promising technology for THz wireless communications. However, fundamental challenges in THz DAoSA systems include millidegree-level three-dimensional direction-of-arrival (DoA) estimation and millisecond-level beam tracking with reduced pilot overhead. To address these challenges, an off-grid subspace-based DAoSA-MUSIC and a deep convolutional neural network (DCNN) methods are proposed for DoA estimation. Furthermore, by exploiting the temporal correlations of the channel variation, an augmented DAoSA-MUSIC-T and a convolutional long short-term memory (ConvLSTM) solutions are further developed to realize DoA tracking. Extensive simulations and comparisons on the proposed subspace- and deep-learning-based algorithms are conducted. Results show that both DAoSA-MUSIC and DCNN achieve super-resolution DoA estimation and outperform existing solutions, while DCNN performs better than DAoSA-MUSIC at a high signal-to-noise ratio. Moreover, DAoSA-MUSIC-T and ConvLSTM can capture fleeting DoA variation with an accuracy of 0.1° within milliseconds, and reduce 50% pilot overhead. Compared to DAoSA-MUSIC-T, ConvLSTM can tolerate large angle variation and remain robust over a long duration.

Despite the narrowbeam nature of Terahertz (THz) communications, the physical layer security in the THz band is challenging when eavesdroppers are inside the beam radiation sector. In this paper, a deep neural network (DNN)-based self-interference cancellation (SIC)-free receiver artificial noise (AN) assisted mechanism is proposed to address the in-beam security challenge, by considering randomly distributed eavesdroppers in THz secure communications. By exploiting the different temporal broadening effects of the AN signals at distinct distances, the SIC can be saved with a proper signal detection design rather than using conventional high-complexity cancellation techniques. To combat the non-linearity and non-convexity of the optimization problem, the system parameters including carrier frequency, power of transmission signal and AN signal power, and frame time are designed by an efficient deep neural network (DNN) algorithm to minimize the secrecy outage probability. Numerical results demonstrate that the maximum secrecy rate of our proposed DNN-powered SIC-free receiver AN scheme is up to 3.3 bps/Hz over 10 m transmission when the eavesdropper is in close proximity. Moreover, the secrecy outage probability is less than 0.5% when the eavesdropper density is 0.001 per square meter, which is approximately 33% lower than that of conventional transmitter AN schemes.

Terahertz (THz) communication is considered as an attractive way to overcome the bandwidth bottleneck and satisfy the ever-increasing capacity demand in the future. Due to the high directivity and propagation loss of THz waves, a massive MIMO system using beamforming is envisioned as a promising technology in THz communication to realize high-gain and directional transmission. However, pilots, which are the fundamentals for many beamforming schemes, are challenging to be accurately detected in the THz band owing to the severe propagation loss. In this paper, a unified 3D beam training and tracking procedure is proposed to effectively realize the beamforming in THz communications, by considering the line-of-sight (LoS) propagation. In particular, a novel quadruple-uniform planar array (QUPA) architecture is analyzed to enlarge the signal coverage, increase the beam gain, and reduce the beam squint loss. Then, a new 3D grid-based (GB) beam training is developed with low complexity, including the design of the 3D codebook and training protocol. Finally, a simple yet effective grid-based hybrid (GBH) beam tracking is investigated to support THz beamforming in an efficient manner. The communication framework based on this procedure can dynamically trigger beam training/tracking depending on the real-time quality of service. Numerical results are presented to demonstrate the superiority of our proposed beam training and tracking over the benchmark methods.

The quality of experience (QoE) requirement of wireless virtual reality (VR) can only be satisfied with high data rate, high reliability, and low VR interaction latency. This high data rate over short transmission distances may be achieved via the abundant spectrum in the terahertz (THz) band. However, THz waves suffer from severe signal attenuation, which may be compensated by the reconfigurable intelligent surface (RIS) technology with adjustable phase-shift of each reflecting element. Motivated by these considerations, in this paper, we propose an RIS-assisted THz VR network in an indoor scenario, taking into account the viewpoint prediction and downlink transmission. We first propose a genie-aided online gated recurrent unit (GRU) and integration of online long-short term memory (LSTM) and convolutional neural network (CNN) algorithm to predict the viewpoint, location, and the line-of-sight (LoS) and non-line-of-sight (NLoS) statuses of the VR users over time, with the aim to optimize the long-term QoE of the VR users. We then develop a constrained deep reinforcement learning algorithm to select the optimal phase shifts of the RIS for the downlink transmission under latency constraints. Simulation results show that the proposed ensemble learning architecture achieves near-optimal QoE as that of an exhaustive algorithm, and about two times improvement in QoE compared to the random phase shift selection scheme.

Terahertz (THz) band communication is a promising pillar technology to satisfy the demands of intelligent information society. The ultra-broad bandwidth in the THz band provides a great potential of a plethora of applications and services. However, THz wireless communication systems encounter stringent challenges, including more severe Doppler effects and more strict peak-to-average power ratio (PAPR) requirements. In this work, a discrete Fourier transform spread orthogonal time frequency space (DFT-s-OTFS) modulation scheme is proposed to address these issues of THz communications. The proposed DFT-s-OTFS can improve the bit error rate (BER) performance by two orders of magnitude compared to orthogonal frequency division multiplexing (OFDM) in presence of high Doppler spread, and reduce the PAPR by approximately 3 dB in contrast with OTFS.

Hybrid beamforming for Terahertz (THz) ultra-massive MIMO (UM-MIMO) systems is a promising technology for 6G networks, which can overcome huge propagation loss and offer unprecedented data rates. With ultra-wide band-width in THz band, the beam squint becomes one of critical problems which could reduce the array gain and degrade the data rate. However, the traditional phase-shifters-based hybrid beamforming architectures cannot tackle this issue due to the frequency-flat property of the phase shifters. In this paper, to combat this beam squint yet with reduced power consumption, a novel dynamic-subarray with fixed-true-time-delay (DS-FTTD) architecture is proposed. Furthermore, a low-complexity row-decomposition (RD) algorithm is developed for the DS-FTTD architecture. Extensive simulation results show that, by using the RD algorithm, the DS-FTTD architecture achieves signifi-cantly higher array gain and spectral efficiency than the phase-shifters-based architectures. Meanwhile, the energy efficiency is substantially improved thanks to the low-cost FTTDs.

TeraHertz (THz) communications are envisioned as a promising technology, owing to its unprecedented multi-GHz bandwidth. One fundamental challenge when moving to new spectrum is to understand the science of radio propagation and develop an accurate channel model. In this paper, a wideband channel measurement campaign between 130 GHz and 143 GHz is conducted in an office room. The channel measurement campaign in the office room scenario consists of three cases: 1) LoS case in the office area 2) Line-of-Sight (LoS) case in the hallway and 3) NLoS case. Directional antennas are utilized and rotated for resolving the multi-path components (MPCs) in the angular domain. With careful system calibration that eliminates system errors and antenna effects, realistic power delay angular profiles (PDAP) are developed. In light of the measurement results, channel parameters and insights in the THz indoor channel are comprehensively analyzed, including the path loss, delay spread, angular, and correlations among the channel parameters. Furthermore, the propagation of NLoS multipath components (MPCs) in the office room scenario and its impact on the THz channel are discussed and compared with the channel measurement in the meeting at 140 GHz. Our analysis shows that the MPCs that reflect from the partitions dominate in NLoS propagation in office room.

Unmanned Aerial Vehicles (UAVs) are currently playing an important role in both military and commercial applications. While UAVs possess potential to enhance network coverage with their high flexibility, combining with the Tera-hertz (THz) band is promising to enhance the wireless data rate with abundant spectrum resources and ultra-high bandwidth. As a fundamental challenge, air-ground (AG) channel modeling and analysis in the THz band are investigated in this paper, based on ray-tracing simulation and hybrid modeling approaches. The channel statistics are extracted and analyzed based on ray-tracing simulated data, including path loss, excess delay, among others. In particular, the height dependence of statistical parameters is thoroughly analyzed, which shows a clear trend of increasing channel sparsity with high-altitude UAVs. In light of the simulated data and analysis, a hybrid channel model including the line-of-sight, ground-reflection path, and stochastically generated multi-path, is proposed to characterize the THz AG propagation, for which the fading characteristics are validated.

Terahertz (0.1-10 THz) band is envisioned to enable ultra-broadband communications for beyond fifth generation (B5G). Although recent efforts focus on high-speed wireless communications, the transmission of THz electromagnetic (EM) waves in free space experiences high path loss and severe molecular absorption effect and is vulnerable to eavesdropping. It is therefore motivated to explore polymer fiber-based THz wireline transmission, which is promising for short-range, ultrafast, and secure communications in intra-vehicle scenarios. In this work, an end-to-end propagation of a THz wireline transmission system is modeled and characterized, by accounting for solid-core circular polymer fiber as the medium. A case study of a 2-mm-diameter solid-core circular polytetrafluoroethylene (PTFE) fiber is provided, which demonstrates the feasibility of the attenuation constant smaller than 6.5 dB/m and dispersion parameter smaller than 1.8 ps/GHz/m between 100 GHz and 160 GHz. Simulation results indicate that when a polymer fiber features a 5-dB/m attenuation constant and a 2-ps/GHz/m dispersion parameter, the system with this polymer fiber can reach a signal-to-interferenceplus-noise ratio (SINR) of 14 dB, corresponding to BER of ten to the power of -11 with the input power of -10 dBm.

Terahertz (THz) communications are envisioned as a key technology of next-generation wireless systems due to its ultra-broad bandwidth. By integrating communication and sensing, the the THz joint communication and sensing (JCS) system can realize both unprecedented data rates and ubiquitously accurate sensing. However, THz JCS meets stringent challenges due to the peculiarities of THz channel and devices. In this work, a sensing integrated discrete Fourier transform spread orthogonal frequency division multiplexing (SI-DFT-s-OFDM) system is proposed for THz JCS. The proposed system is able to provide lower peak-to-average power ratio than OFDM. Without compromising communication capabilities, SI-DFT-s-OFDM can realize millimeter-level range estimation accuracy and improve the velocity estimation accuracy by 10 times than OFDM. Finally, SI-DFT-s-OFDM achieves 18% improvement of data rate over DFT-s-OFDM.

Recently researchers have been attracted by the joint communication and sensing (JCS) techniques, due to their diverse benefits in communication-sensing applications. By sharing the spectrum and hardware components, the advantages of JCS systems include enhanced spectrum efficiency and reduced device costs. Following the trend of scaling up the carrier frequencies for 5G and beyond, Terahertz (THz) band is envisioned as a promising chunk of spectrum featuring multi-GHz bandwidth windows. However, despite the great promise, the waveform design for THz JCS is still not explored enough. In this work, the design guidelines for THz JCS waveform are presented. With the help of these guidelines, a non-uniform multi-wideband orthogonal frequency division multiplexing (NMW-OFDM) THz system is proposed to overcome the limitations of OFDM based JCS. The proposed NMW-OFDM system is able to realize sub-millimeter-level accuracy of the range estimation by using a multi-stage sensing algorithm, which is three orders of magnitude improvement compared to the OFDM-based JCS system. In addition, the accuracy of velocity estimation can be enhanced by 10 times within a short frame time. Finally, the system can achieve unprecedented communication data rate of 100 Gbps without sacrificing the maximum detectable distance.

High-accuracy localization technology has gained increasing attention in gesture and motion control and many diverse applications. Due to multi-path fading and blockage effects in indoor propagation, 0.1m-level precise localization is still challenging. Promising for 6G wireless communications, the Terahertz (THz) spectrum provides multi-GHz ultra-broad bandwidth. Applying the THz spectrum to indoor localization, the channel state information (CSI) of THz signals, including angle of arrival (AoA), received power, and delay, has unprecedented resolution that can be explored for positioning. In this paper, a Structured Intra-Attention Bidirectional Recurrent (SIABR) deep learning method is proposed to solve the CSI-based three-dimensional (3D) THz indoor localization problem with significantly improved accuracy. As a two-level structure, the features of individual multi-path rays are first analyzed in the recurrent neural network with the attention mechanism at the lower level. Furthermore, the upper-level residual network (ResNet) of the constructed SIABR network extracts hidden information to output the geometric coordinates. Simulation results demonstrate that the 3D localization accuracy in the metric of mean distance error is within 0.25m. The developed SIABR network has very fast convergence and is robust against THz indoor line-of-sight blockage, multi-path fading, channel sparsity and CSI estimation error.

Directional antennas and beamforming techniques that bring promising transmission gain to the wireless links are widely incorporated in the system-level analysis of wireless networks. In many existing studies, the beamforming gain model to calculate the beamforming gain considers beamforming pattern and aligned as well as misaligned cases. However, the channel properties, e.g., the$K$factor and the spatial distribution of multi-paths, are neglected, which could significantly influence the beamforming gain. In this paper, a general beamforming gain model is appropriately defined, while the traditional beamforming gain model is proved to be only a special case in the proposed general model by considering an oversimplified channel with no angular spread. In light of this, expressions of the received signal amplitude and the beamforming gain are rigorously derived for narrowband fading and wideband statistical mmWave channels, respectively. Thorough comparison between the proposed beamforming gain model and the traditional beamforming gain is provided, which demonstrates and validates that the traditional model incorrectly captures the beamforming gain and thereby, leads to inaccurate system-level network analysis. To this end, the effectiveness and importance of the proposed general beamforming gain model are revealed, particularly for millimeter-wave wideband systems.

The Terahertz band is envisioned to meet the demanding 100 Gbps data rates for 6G wireless communications. Aiming at combating the distance limitation problem with low hardware-cost, ultra-massive MIMO with hybrid beamforming is promising. However, relationships among wavelength, array size and antenna spacing give rise to the inaccuracy of planar-wave channel model (PWM), while an enlarged channel matrix dimension leads to excessive parameters of applying spherical-wave channel model (SWM). Moreover, due to the adoption of hybrid beamforming, channel estimation (CE) needs to recover high-dimensional channels from severely compressed channel observation. In this paper, a hybrid spherical- and planar-wave channel model (HSPM) is investigated and proved to be accurate and efficient by adopting PWM within subarray and SWM among subarrays. Furthermore, a two-phase HSPM CE mechanism is developed. A deep convolutional-neural-network (DCNN) is designed in the first phase for parameter estimation of reference subarrays, while geometric relationships of the remaining channel parameters between reference subarrays are leveraged to complete CE in the second phase. Extensive numerical results demonstrate the HSPM is accurate at various communication distances, array sizes and carrier frequencies. The DCNN converges fast and achieves high accuracy with 5.2 dB improved normalized-mean-square-error compared to literature methods, and owns substantially low complexity.

TeraHertz (THz) communications are envisioned as a promising technology, owing to its unprecedented multi-GHz bandwidth. One fundamental challenge when moving to new spectrum is to understand the science of radio propagation and develop an accurate channel model. In this paper, a wideband channel measurement campaign between 130 GHz and 143 GHz is investigated in a typical meeting room. Directional antennas are utilized and rotated for resolving the multi-path components (MPCs) in the angular domain. With careful system calibration that eliminates system errors and antenna effects, a realistic power delay profile is developed. Furthermore, a combined MPC clustering and matching procedure with ray-tracing techniques is proposed to investigate the cluster behavior and wave propagation of THz signals. In light of the measurement results, physical parameters and insights in the THz indoor channel are comprehensively analyzed, including the line-of-sight path loss, power distributions, temporal and spatial features, and correlations among THz multi-path characteristics. Finally, a hybrid channel model that combines ray-tracing and statistical methods is developed for THz indoor communications. Numerical results demonstrate that the proposed hybrid channel model shows good agreement with the measurement and outperforms the conventional statistical and geometric-based stochastic channel model in terms of the temporal-spatial characteristics.

The Terahertz (THz) band is envisioned as a promising technique to support bandwidth-hungry and secure applications. Although the significant path loss and strong directivity make THz communications secure naturally, the information security is still imperfect at near regions along the beam propagation path. In this paper, a novel distance-adaptive absorption peak modulation (DA-APM) is developed for THz covert communications, by exploring the unique spectrum features of frequency-dependent molecular absorption. Although high-attenuation molecular absorption is unfavored for communications, the main principle to enhance covertness or equivalently, minimize the eavesdroppable distance, is dynamically modulating signals under the molecular absorption peaks in the THz spectrum, where the eavesdroppable distance is defined as the threshold distance within which an eavesdropper can wiretap the transmission. Furthermore, an optimization framework is proposed to minimize the eavesdroppable distance, to which the sub-optimal solutions are derived for the multi-wideband waveform by controlling carrier frequencies, power allocation, and rate distribution on each sub-band. Extensive numerical results show that the THz-spectrum-based DA-APM approach can reduce the eavesdroppable distance by 60% compared with random spectrum selection methods, which significantly reduce the insecure area and enhance the covertness of THz wireless transmission.

Providing high-bandwidth and fast-speed links, wireless local area networks (WLANs) in the Terahertz (THz) band have huge potential for various bandwidth-intensive indoor applications. However, due to the specific phenomena in the THz band, including severe reflection loss, indoor blockage effects, multi-path fading, the analysis on the interference and coverage probability at a downlink is challenging. In this paper, indoor blockage effects caused by the walls and human bodies are analyzed. Next, a statistical THz channel model is proposed to characterize the THz indoor propagation. In light of these, the moment generating functions of the aggregated interference and theoretical expressions for the mean interference power are derived. As a result, the approximated coverage probability and average network throughput are derived. Extensive numerical results show that for the nearest access point (nearest-AP) user association scheme, the optimal AP density is 0.15/m2, which results in the coverage probability reaches 93% and the average network throughput is 30 Gbps/m2. In addition, by adopting a novel line-of-sight access point (LoS-AP) user association mechanism, the coverage probability and the average network throughput can be further improved by 3 percent and 2 Gbps/m2, respectively.

The Terahertz (0.1-10 THz) band is envisioned to meet the demanding 100 Gbps data rates for 6G wireless communications. Aiming at combating the distance limitation problem in THz communications, the ultra-massive MIMO with array-of-subarrays (AoSA) hybrid beamforming is adopted as a promising technology. On the downside, an enlarged channel dimension gives rise to the high-complexity of channel estimation (CE). Furthermore, the distinctive spherical-wave propagation characteristic restricts the applicability of most existing CE techniques. To address these challenges, a deep convolutional neural network (DCNN)-based spherical-wave CE method for THz AoSA communication systems is developed in this paper. A fifteen-layer DCNN structure is designed, within which the spherical-wave channel parameters including the azimuth and elevation angles, the amplitude of the channel gain, and the phase shift matrix are carefully processed to be training labels. After leveraging supervised learning with a self-defined loss function from the labeled data, the DCNN is trained offline and deployed online to conduct CE. Extensive simulation results demonstrate that compared to existing on-grid and off-grid methods, the proposed DCNN converges fast with reduced complexity. Moreover, the proposed DCNN algorithm can achieve outstanding accuracy with the normalized mean-square-error (NMSE) of -13.8 dB at SNR=10 dB.

Although with narrow-beam transmissions, physical layer security of Terahertz (THz) communications faces great challenges with the presence of eavesdroppers in close proximity inside the Terahertz beam sector. This paper proposes a novel self-interference cancellation (SIC)-free receiver artificial noise (AN) assisted mechanism to address this challenge for THz secure communications. By exploiting the different temporal broadening effects of the artificial noise signals at the receiver side versus the eavesdropper side, the high-complexity SIC part can be mitigated with a proper receiver design. Moreover, the system parameters including power allocation, carrier frequency, transmit power, symbol time, pulse waveform type, and receiver parameter that maximize the secrecy rate of the THz communication system are solved, based on an efficient deep neural network (DNN) algorithm. Numerical results demonstrate that our proposed SIC-free receiver artificial noise scheme achieves 4 bps/Hz secrecy rate, with substantially lower hardware complexity than SIC-based receiver AN systems and reduced computational complexity than exhaustive search.

Hybrid beamforming for terahertz (THz) communications is a promising technology for beyond 5G wireless systems, which has great potential to overcome very high propagation loss, mitigate hardware complexity, and achieve unprecedented data rates. In this paper, a dynamic-subarray (DS) architecture is investigated for THz hybrid beamforming systems. Specifically, we analyze both quantized-phase shifters (QPS) with finite phase levels, and fixed-phase shifters (FPS) with unaltered phases in the DS architecture, which significantly reduce hardware complexity and power consumption compared to using the infinite-resolution phase shifters (IPS). Furthermore, a generic low-complexity row-by-row (RBR) algorithm is derived for the proposed DS-structured hybrid beamforming with QPS and FPS. Extensive simulation results demonstrate that the RBR algorithm improves spectral efficiency and substantially reduces computational complexity. Compared to the DS-IPS, the DS-QPS architecture can achieve 98% spectral efficiency and 136% energy efficiency. In addition, we show that while the spectral efficiency of the DS-FPS architecture is 21% lower than the DS-QPS counterpart, the low-cost FPS provides 30% higher energy efficiency than QPS.

We derive new expressions for the connection probability and the average ergodic capacity to evaluate the performance achieved by multi-connectivity (MC) in an indoor ultra-wideband terahertz (THz) communication system. In this system, the user is affected by both self-blockage and dynamic human blockers. We first build up a three-dimensional propagation channel in this system to characterize the impact of molecular absorption loss and the shrinking usable bandwidth nature of the ultra-wideband THz channel. We then carry out new performance analysis for two MC strategies: 1) Closest line-of-sight (LOS) access point (AP) MC (C-MC), and 2) Reactive MC (R-MC). With numerical results, we validate our analysis and show the considerable improvement achieved by both MC strategies in the connection probability. We further show that the C-MC and R-MC strategies provide significant and marginal capacity gain relative to the single connectivity strategy, respectively, and increasing the number of the user's associated APs imposes completely different affects on the capacity gain achieved by the C-MC and R-MC strategies. Additionally, we clarify that our analysis allows us to determine the optimal density of APs in order to maximize the capacity gain.

High-accuracy localization technology has gained increasing attention in gesture and motion control and many diverse applications. Due to the shadowing, multi-path fading, blockage effects in indoor propagation, 0.1m-level precise localization is still challenging. Promising for 6G wireless communications, the Terahertz (THz) spectrum provides ultra-broad bandwidth for indoor applications. Applying to indoor localization, the channel state information (CSI) of THz wireless signals, including angle of arrival (AoA), received power, and delay, has unprecedented resolution that can be explored for positioning. In this paper, a Structured Bidirectional Long Short-term Memory (SBi-LSTM) recurrent neural network (RNN) architecture is proposed to solve the CSI-based three-dimensional (3D) THz indoor localization problem with significantly improved accuracy. As a two-level structure, the features of individual multi-path ray are first analyzed in the Bi-LSTM network at the base level. Furthermore, the upper level residual network (ResNet) of the constructed SBi-LSTM network extracts for the geometric coordinates. Simulation results validate the convergence of our SBi-LSTM method and the robustness against indoor non-line-of-sight (NLoS) blockage. Specifically, the localization accuracy in the metric of mean distance error is within 0.27m under the NLoS environment, which demonstrates 60% enhancement over the state-of-the-art techniques.

The Terahertz (0.1-10 THz) band is envisioned to meet the rapid growth of wireless data rates. Achieving high beamforming gain and reduced hardware complexity, the array-of-subarrays (AoSA) hybrid beamforming is a promising technology to be adopted for THz communications. The generated razor-sharp beam can compensate for the severe path loss and overcome the distance limitation. However, major challenges in the THz hybrid beamforming system include millidegree-level three-dimensional (3D) angle estimation, and overhead reduction beam tracking. To solve these challenges, an off-grid ultra-high-resolution direction-of-arrival (DoA) estimation method that matches the AoSA architecture, namely, AoSA-MUSIC, is developed in this paper, which involves coarse and refine training. Furthermore, an extended DoA tracking method, namely, AoSA-MUSIC-T, is developed, which employs a subspace tracking scheme with the overhead reduced tracking observation to replace the high-complexity eigenvalue decomposition (EVD) process in the AoSA-MUSIC method. Simulation results show that the proposed AoSA-MUSIC can obtain millidegree-level precise DoA estimation. Moreover, the AoSA-MUSIC-T tracking algorithm can capture the fleeting DoA variation in millisecond with fifty-percent reduced training overhead.

We propose a novel hybrid beamforming (BF) scheme with distance-aware multi-carrier (DAMC) modulation and beam division multiple access (BDMA) to enable massive connections in terahertz (THz) micro-scale networks. This scheme breaks a fundamental limitation in hybrid BF, i.e., the number of users that are simultaneously supported cannot exceed the number of RF chains. Some unique properties of THz channels, such as high distance-and-frequency dependence, high sparsity, and small angular spread, are exploited in this scheme. First, we propose a user grouping scheme with rough beam pre-scanning and a DAMC spectrum allocation scheme to eliminate intragroup interference. Then, we propose a wideband hybrid BF designing algorithm using the principles of BDMA to control inter-group interference. Furthermore, we propose an iterative power allocation strategy to maximize the achievable sum-rate of the network. Simulation results are presented to show that our proposed hybrid BF DAMC-BDMA scheme achieves higher sum-rate than the fully digital BF scheme in the high transmit power regime, due to the high sparsity of THz channels. Simulation results also demonstrate that our iterative power allocation strategy has strong robustness against uncertain interferences.

Terahertz (THz) communications are envisioned as a key technology for 6G wireless systems, owing to an unprecedented promised multi-GHz bandwidth. While THz band suffers from huge propagation losses, large arrays of sub-millimeter wavelength antennas can be realized in ultra-massive multiple-input multiple-output (UM-MIMO) systems to enhance the received power and overcome the distance limitation. In this paper, a dynamic array-of-subarrays (DAoSA) hybrid precoding architecture is proposed to reduce the power consumption while meeting the data rate requirement in THz UM-MIMO systems. The connections between RF chains and subarrays are intelligently adjusted through a network of switches. First, to solve the intractable DAoSA hybrid precoding problem, element-by-element (EBE) and vectorization-based (VEC) algorithms are derived. Moreover, to determine the connections of the switches, near-optimal progressive stage-by-stage (PSBS), low-complexity alternating-selection (AS) and block-diagonal-search (BDS) algorithms are developed. Extensive simulation results show that both the EBE and VEC algorithms have higher spectral efficiency than existing hybrid precoding algorithms. Furthermore, the power consumption of the DAoSA architecture is substantially lessened, with PSBS, AS and BDS algorithms, respectively. The developed DAoSA architecture associated with proposed hybrid precoding and switch network design algorithms demonstrates a superior capability on balancing the spectral efficiency and power consumption.

We propose novel hybrid beamforming schemes for the terahertz (THz) wireless system where a multi-antenna base station (BS) communicates with a multi-antenna user over frequency selective fading. Here, we assume that the BS employs sub-connected hybrid beamforming and multi-carrier modulation to deliver ultra high data rate. We consider a three-dimensional wideband THz channel by incorporating the joint effect of molecular absorption, high sparsity, and multi-path fading, and consider the carrier frequency offset in multi-carrier systems. With this model, we first propose a two-stage wideband hybrid beamforming scheme which includes a beamsteering codebook searching algorithm for analog beamforming and a regularized channel inversion method for digital beamforming. We then propose a novel wideband hybrid beamforming scheme with two digital beamformers. In this scheme, an additional digital beamformer is developed to compensate for the performance loss caused by the constant-amplitude hardware constraints and the difference of channel matrices among subcarriers. Furthermore, we consider imperfect channel state information (CSI) and propose a probabilistic robust hybrid beamforming scheme to combat channel estimation errors. Numerical results demonstrate the benefits of our proposed schemes for the sake of practical implementation, especially considering its high spectral efficiency, low complexity, and robustness against imperfect CSI.

In this paper, the V2I channel in a typical urban scenario is analyzed by the ray tracing technique at 110 GHz. The channel statistics, including the path loss, time-of-arrival (ToA), and direction-of-arrival (DoA) are thoroughly characterized. To capture the channel non- stationarity, a continuous-time birth and death (B-D) process is utilized to model the dynamic behavior of multiple path components (MPCs). On the basis of the channel statistics from the ray tracing combining the B-D process, a geometric-based stochastic time- varying model (GBSTM) is developed for the low-THz urban V2I scenario, which considers the spherical wave propagation and specular MPCs. The closed-form expressions for the critical statistical quantities of non-stationary channels, e.g., the four- dimensional (4D) time-frequency correlation function (TF-CF) and time- frequency dependent power delay profile (TF-PDP) are derived. The analysis reveals that spherical wave propagation will cause non- linear temporal-spatial correlation and extra non- stationarity of the channel in the time domain.

Covert communication, aiming at concealing the existence of data transmission from an eavesdropper, is attracting increasing concerns for communication security. With the trend of moving to higher carrier frequencies, Terahertz (THz) band communication, i.e., wavelength at 0.03-3mm, is envisioned as a promising technique to support bandwidth-hungry applications, as well as improve physical layer security due to its naturally strong directivity and high path loss. Narrow-beam transmission widely adopted in THz communications can effectively prevent from eavesdropping outside the beam sector. However, the challenge still remains when an eavesdropper resides inside the beam sector. To ensure the covertness under such condition, in this paper, a distance-adaptive absorption peak hopping (DA-APH) modulation scheme is proposed for THz covert communications, which takes advantages of distance- and frequency-selective spectral windows, and the frequency-hopping mechanism over the THz spectrum. In particular, the pulse waveform model with polarization is developed to guarantee the reliability of transmission and covertness from eavesdropping. Furthermore, a distance-adaptive carrier frequency selection scheme is designed to choose optimal hopping frequencies at molecular absorption peaks in the THz band.

Wireless networks-on-chip (WiNoC) communications are envisioned as a promising technology to support the interconnection of hundreds of cores in the chip multi-processor design. To meet the future demand for Tera-bit-per-second (Tbps) ultra-fast links in the WiNoC, the millimeter wave (mmWave) and Terahertz (THz) bands with ultra-broad spectrum resource are proposed for WiNoC communications. In this paper, a hybrid WiNoC architecture and the stratified chip design are described, in which the flip-chip package and heat sink are considered. The electromagnetic fields in the WiNoC stratified medium are theoretically analyzed and verified with full-wave simulation. Based on the developed channel model, the WiNoC propagation is characterized by analyzing the path loss, the channel capacity and the reliability. Furthermore, the impact and guideline of the chip design on the WiNoC wave propagation are extensively evaluated and investigated. In particular, the wave propagation performance in THz WiNoC channel can be improved, by decreasing the underfill thickness, proper choice of the silicon thickness and inserting a bottom layer below the silicon substrate.

Non-orthogonal multiple access (NOMA) scheme has been regarded as one of the promising solutions to realize a flexible and robust multiple access scheme in next generation wireless communication system. However, the inter-carrier interference caused by time-varying fading is not considered in conventional NOMA. In this paper, a novel multi-user access scheme, adaptive subcarrier-spacing multi-carrier non-orthogonal multiple access (ASMC- NOMA), is proposed to provide robust multi-user downlink transmission in time-varying channels and support user velocities up to 500 km/h. Based on the filtered-OFDM waveform, ASMC-NOMA allows flexible power-time- frequency three-dimensional resource allocation and subcarrier spacing adaptation according to the channel state and user velocities. With the user-specific adaption and coexistence of different parameters, ASMC-NOMA is able to repel the impact of high-range Doppler effects and control the signal-to-interference ratio for every downlink user. The pre-grouped resource adaptive allocation scheme is designed with the consideration of reducing the transmission overhead and receiver-end implementation complexity. Transceiver structure and signal model are discussed in detail. Theoretical analysis on the signal properties and numerical system-level simulation results prove that the proposed ASMC-NOMA effectively enhances the transmission robustness, reduces the transmission outage due to the high mobility of users, and provides increased transmission efficiency over conventional OFDM- based NOMA and multi-carrier orthogonal multiple access.

We propose a novel hybrid beamforming (BF) scheme for the Terahertz (THz) wireless communication system over frequency selective channels. In the system, a multi-antenna base station which employs the sub-connected architecture adopts orthogonal frequency division multiplexing to serve a multi- antenna user. By building a wideband THz channel model, we design a beamsteering codebook searching algorithm for analog BF in which the channel state information of all subcarriers in the radio frequency domain is considered. We then design the digital BF by using the regularized channel inversion method for eliminating inter-band interference at the baseband. Numerical results demonstrate that our proposed hybrid BF scheme achieves a significant spectral efficiency advantage over the existing hybrid BF scheme which adopted the zero-forcing digital beamformer. The results also demonstrate that the spectral efficiency achieved by our proposed low-complexity scheme is very close to that achieved by the high- complexity fully digital BF scheme, especially when the average received power at the user is low.

Terahertz (THz)-band communication (0.1-10 THz) is envisioned as a key wireless technology to satisfy the in- creasing demand for faster data-rates in beyond 5G systems, thanks to its ultra-broad bandwidth. The very high path loss at THz frequencies and the limited transmission power of THz transceivers impose a major distance limitation for THz wireless communications. To increase the communication distance and the achievable data rates at THz-band frequencies, the concept of Ultra-Massive MIMO (UM-MIMO) has been introduced, which integrates a very large number of nano-antennas (e.g., 1024) in very small footprints (e.g., 1 mm^2). In this paper, an end-to-end model for UM-MIMO communication in the THz band is developed, by accounting for the properties of graphene- based plasmonic nano-antenna arrays and the peculiarities of three- dimensional THz propagation. The developed model is utilized to investigate the performance of the UM- MIMO channel. In particular, the path gain, the array factor and the the wideband capacity for both spatial multiplexing and beamforming regimes are analyzed. The results show that multi-Terabit-per-second links are feasible at distances of up to 20 m when utilizing 1024 × 1024 UM-MIMO systems at 0.3 THz and 1 THz.

Interference and coverage is a critical factor affecting the performance of nanonetworks in the terahertz (THz) band. In this paper, on the basis of THz channel model, the interferences from surrounding omnidirectional nanosensors (NSs) and beamforming Base Stations (BSs) are derived in closed forms by using stochastic geometry methods respectively. Furthermore, the corresponding Signal-to-Interference-plus-Noise-Ratio (SINR) and the coverage probabilities are investigated based on the proposed interference model. Simulation results, observed from the spectral windows at 1.0 THz, 4.5 THz and 9.1 THz, demonstrate that high density of BSs, beamforming antenna with small beam-width and low density of NSs are recommended to mitigate the interference and improve the coverage performance. Moreover, low frequency in THz band with low absorption coefficient is advocated to guarantee the correct reception with enough high received signal strength.

This paper presents a time-varying channel model in three- dimensional environments for the 5G wireless system. Using the continuous-time Markov chain, the proposed model captures the statistical movement of the transceiver, the transition between line-of-sight and non-line-of-sight propagation scenarios, and the dynamic variation of propagation parameters. Moreover, a novel frequency- dependent factor that describes the dynamic path behavior is described in this model. According to the simulation results based on ray-tracing techniques and field measurements from the literature, the proposed time- varying channel model is validated at 5.2, 10, and 60 GHz. Furthermore, under realistic 5G device-to-device communication scenario, the simulation results and time- varying channel characteristics are highlighted, including the number of paths, path gain, delay spread, delay variation, Rician K-factor, and coherence bandwidth.

Terahertz (0.1-10 THz) band communication is envisioned as a key technology to satisfy the increasing demand for ultra-high-speed wireless links. In this paper, a three dimensional (3D) end-to-end model is developed, which includes the graphene-based antenna response and the channel model in the THz band. The developed theoretical model is validated with COMSOL simulations. By using the developed 3D end-to-end model, an in-depth analysis on the 3D channel characteristics is carried out. In particular, the use of a 13-dB-gain antenna leads to the decrease of the delay spread from 0.2 ns to 3.2 ps, and the decrease of the angular spread by a factor of 20. The resulting coherence bandwidth reaches 63 GHz. A target capacity of 100 Gbps can be achieved with the directional antenna for the distance of 0.4m over 0.8-0.9 THz, which is unreachable with the isotropic antenna. However, the directivity is at the cost of the strict antenna alignment, and the deviation needs to be smaller than 12.4o. The provided analysis lays out the foundation for reliable and efficient ultra-high-speed wireless communications in the THz band.

Terahertz (0.06-10 THz) Band communication is envisioned as a key technology for satisfying the increasing demand for ultra-high-speed wireless links. In this paper, first, a unified multi-ray channel model in the THz Band is developed based on ray tracing techniques, which incorporates the propagation models for the line-of-sight, reflected, scattered, and diffracted paths. The developed theoretical model is validated with the experimental measurements (0.06-1 THz) from the literature. Then, using the developed propagation models, an in-depth analysis on the THz channel characteristics is carried out. In particular, the distance-varying and frequency-selective nature of the Terahertz channel is analyzed. Moreover, the coherence bandwidth and the significance of the delay spread are studied. Furthermore, the wideband channel capacity using flat and water-filling power allocation strategies is characterized. Additionally, the temporal broadening effects of the Terahertz channel are studied. Finally, distance-adaptive and multi-carrier transmissions are suggested to best benefit from the unique relationship between distance and bandwidth. The provided analysis lays out the foundation for reliable and efficient ultra-high-speed wireless communications in the (0.06-10) THz Band.

Terahertz Band (0.1-10 THz) communication is envisioned as a key technology to satisfy the increasing demand for ultra-broadband wireless communication. THz Band communication will alleviate the spectrum scarcity and capacity limitations of current wireless systems, and enable new applications both in classical networks and novel nanoscale networks. In this paper, a novel distance-aware multi-carrier (DAMC) modulation scheme is developed for both single-transmitter single-receiver and single-transmitter multiple-receiver cases in THz Band communication. The developed DAMC modulation scheme takes advantage of the distance- and frequency-dependent channel peculiarities, and provides adaptive utilization of the ultra-broad bandwidth in the THz Band. Furthermore, the data rates of the DAMC scheme are analytically investigated, numerically evaluated, and compared with existing single-band pulse-based modulation and fixed-bandwidth adaptive modulation. The results show that data rates can be improved by one order of magnitude by using the DAMC scheme, at the costs of design complexity for the control unit, multi-carrier modulator and channel feedback path.