arXiv subjects

Ke Guan

Publications and source records attributed to Ke Guan.

At least 19 recordsLinked to original sources

arXiv2025

Terahertz Signal Coverage Enhancement in Hall Scenarios Based on Single-Hop and Dual-Hop Reconfigurable Intelligent Surfaces

Terahertz (THz) communication offers ultra-high data rates and has emerged as a promising technology for future wireless networks. However, the inherently high free-space path loss of THz waves significantly limits the coverage range of THz communication systems. Therefore, extending the effective coverage area is a key challenge for the practical deployment of THz networks. Reconfigurable intelligent surfaces (RIS), which can dynamically manipulate electromagnetic wave propagation, provide a solution to enhance THz coverage. To investigate multi-RIS deployment scenarios, this work integrates an antenna array-based RIS model into the ray-tracing simulation platform. Using an indoor hall as a representative case study, the enhancement effects of single-hop and dual-hop RIS configurations on indoor signal coverage are evaluated under various deployment schemes. The developed framework offers valuable insights and design references for optimizing RIS-assisted indoor THz communication and coverage estimation.

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arXiv2025

Measurement-Based Modeling and Analysis of UAV Air-Ground Channels at 1 and 4 GHz

In the design of unmanned aerial vehicle (UAV) wireless communications, a better understanding of propagation characteristics and an accurate channel model are required. Measurements and comprehensive analysis for the UAV-based air-ground (AG) propagation channel in the vertical dimension are presented in this letter. Based on the measurement data at 1 and 4 GHz, the large-scale and small-scale channel parameters are extracted in the line-of-sight (LOS) and nonLOS case, respectively. The altitude-dependent path loss model is proposed herein. Furthermore, shadow fading and fast fading are statistically analyzed for comprehensively describing the fading behavior. Our results will be useful in the modeling of AG channels and the performance analysis for UAV-enabled wireless communication systems.

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arXiv2025

5G Channel Models for Railway Use Cases at mmWave Band and the Path Towards Terahertz

High-speed trains are one of the most relevant scenarios for the fifth-generation (5G) mobile communications and the "smart rail mobility" vision, where a high-data-rate wireless connectivity with up to several GHz bandwidths will be required. This is a strong motivation for the exploration of millimeter wave (mmWave) band. In this article, we identify the main challenges and make progress towards realistic 5G mmWave channel models for railway use cases. In order to cope with the challenge of including the railway features in the channel models, we define reference scenarios to help the parameterization of channel models for railway use at mmWave band. Simulations and the subsequent measurements used to validate the model reflect the detailed influence of railway objects and the accuracy of the simulations. Finally, we point out the future directions towards the full version of the smart rail mobility which will be powered by terahertz (THz) communications.

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arXiv2023

6G Enabled Advanced Transportation Systems

With the emergence of communication services with stringent requirements such as autonomous driving or on-flight Internet, the sixth-generation (6G) wireless network is envisaged to become an enabling technology for future transportation systems. In this paper, two ways of interactions between 6G networks and transportation are extensively investigated. On one hand, the new usage scenarios and capabilities of 6G over existing cellular networks are firstly highlighted. Then, its potential in seamless and ubiquitous connectivity across the heterogeneous space-air-ground transportation systems is demonstrated, where railways, airplanes, high-altitude platforms and satellites are investigated. On the other hand, we reveal that the introduction of 6G guarantees a more intelligent, efficient and secure transportation system. Specifically, technical analysis on how 6G can empower future transportation is provided, based on the latest research and standardization progresses in localization, integrated sensing and communications, and security. The technical challenges and insights for a road ahead are also summarized for possible inspirations on 6G enabled advanced transportation.

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arXiv2023

A 3D Modeling Method for Scattering on Rough Surfaces at the Terahertz Band

The terahertz (THz) band (0.1-10 THz) is widely considered to be a candidate band for the sixth-generation mobile communication technology (6G). However, due to its short wavelength (less than 1 mm), scattering becomes a particularly significant propagation mechanism. In previous studies, we proposed a scattering model to characterize the scattering in THz bands, which can only reconstruct the scattering in the incidence plane. In this paper, a three-dimensional (3D) stochastic model is proposed to characterize the THz scattering on rough surfaces. Then, we reconstruct the scattering on rough surfaces with different shapes and under different incidence angles utilizing the proposed model. Good agreements can be achieved between the proposed model and full-wave simulation results. This stochastic 3D scattering model can be integrated into the standard channel modeling framework to realize more realistic THz channel data for the evaluation of 6G.

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arXiv2023

A Ray-tracing and Deep Learning Fusion Super-resolution Modeling Method for Wireless Mobile Channel

Mobile channel modeling has always been the core part for design, deployment and optimization of communication system, especially in 5G and beyond era. Deterministic channel modeling could precisely achieve mobile channel description, however with defects of equipment and time consuming. In this paper, we proposed a novel super resolution (SR) model for cluster characteristics prediction. The model is based on deep neural networks with residual connection. A series of simulations at 3.5 GHz are conducted by a three-dimensional ray tracing (RT) simulator in diverse scenarios. Cluster characteristics are extracted and corresponding data sets are constructed to train the model. Experiments demonstrate that the proposed SR approach could achieve better power and cluster location prediction performance than traditional interpolation method and the root mean square error (RMSE) drops by 51% and 78% relatively. Channel impulse response (CIR) is reconstructed based on cluster characteristics, which could match well with the multi-path component (MPC). The proposed method can be used to efficiently and accurately generate big data of mobile channel, which significantly reduces the computation time of RT-only.

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arXiv2023

Super-resolution of Ray-tracing Channel Simulation via Attention Mechanism based Deep Learning Model

As an emerging approach, deep learning plays an increasingly influential role in channel modeling. Traditional ray tracing (RT) methods of channel modeling tend to be inefficient and expensive. In this paper, we present a super-resolution (SR) model for channel characteristics. Residual connection and attention mechanism are applied to this convolutional neural network (CNN) model. Experiments prove that the proposed model can reduce the noise interference generated in the SR process and solve the problem of low efficiency of RT. The mean absolute error of our channel SR model on the PL achieves the effect of 2.82 dB with scale factor 2, the same accuracy as RT took only 52\% of the time in theory. Compared with vision transformer (ViT), the proposed model also demonstrates less running time and computing cost in SR of channel characteristics.

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arXiv2022

Reconfigurable Intelligent Surface Enabled Spatial Multiplexing with Fully Convolutional Network

Reconfigurable intelligent surface (RIS) is an emerging technology for future wireless communication systems. In this work, we consider downlink spatial multiplexing enabled by the RIS for weighted sum-rate (WSR) maximization. In the literature, most solutions use alternating gradient-based optimization, which has moderate performance, high complexity, and limited scalability. We propose to apply a fully convolutional network (FCN) to solve this problem, which was originally designed for semantic segmentation of images. The rectangular shape of the RIS and the spatial correlation of channels with adjacent RIS antennas due to the short distance between them encourage us to apply it for the RIS configuration. We design a set of channel features that includes both cascaded channels via the RIS and the direct channel. In the base station (BS), the differentiable minimum mean squared error (MMSE) precoder is used for pretraining and the weighted minimum mean squared error (WMMSE) precoder is then applied for fine-tuning, which is nondifferentiable, more complex, but achieves a better performance. Evaluation results show that the proposed solution has higher performance and allows for a faster evaluation than the baselines. Hence it scales better to a large number of antennas, advancing the RIS one step closer to practical deployment.

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arXiv2022

A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics

Channel modeling has always been the core part in communication system design and development, especially in 5G and 6G era. Traditional approaches like stochastic channel modeling and ray-tracing (RT) based channel modeling depend heavily on measurement data or simulation, which are usually expensive and time consuming. In this paper, we propose a novel super resolution (SR) model for generating channel characteristics data. The model is based on multi-task learning (MTL) convolutional neural networks (CNN) with residual connection. Experiments demonstrate that the proposed SR model could achieve excellent performances in mean absolute error and standard deviation of error. Advantages of the proposed model are demonstrated in comparisons with other state-of-the-art deep learning models. Ablation study also proved the necessity of multi-task learning and techniques in model design. The contribution in this paper could be helpful in channel modeling, network optimization, positioning and other wireless channel characteristics related work by largely reducing workload of simulation or measurement.

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arXiv2022

Performance and Optimization of Reconfigurable Intelligent Surface Aided THz Communications

TeraHertz (THz) communications can satisfy the high data rate demand with massive bandwidth. However, severe path attenuation and hardware imperfection greatly alleviate its performance. Therefore, we utilize the reconfigurable intelligent surface (RIS) technology and investigate the RIS-aided THz communications. We first prove that the small-scale amplitude fading of THz signals can be accurately modeled by the fluctuating two-ray distribution based on two THz signal measurement experiments conducted in a variety of different scenarios. To optimize the phase-shifts at the RIS elements, we propose a novel swarm intelligence-based method that does not require full channel estimation. We then derive exact statistical characterizations of end-to-end signal-to-noise plus distortion ratio (SNDR) and signal-to-noise ratio (SNR). Moreover, we present asymptotic analysis to obtain more insights when the SNDR or the number of RIS's elements is high. Finally, we derive analytical expressions for the outage probability and ergodic capacity. The tight upper bounds of ergodic capacity for both ideal and nonideal radio frequency chains are obtained. It is interesting to find that increasing the number of RIS's elements can significantly improve the THz communications system performance. For example, the ergodic capacity can increase up to 25% when the number of elements increases from 40 to 80, which incurs only insignificant costs to the system.

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arXiv2021

Cluster-based Characterization and Modeling for UAV Air-to-Ground Time-Varying Channels

With the deep integration between the unmanned aerial vehicle (UAV) and wireless communication, UAV-based air-to-ground (AG) propagation channels need more detailed descriptions and accurate models. In this paper, we aim to perform cluster-based characterization and modeling for AG channels. To our best knowledge, this is the first study that concentrates on the clustering and tracking of multipath components (MPCs) for time-varying AG channels. Based on measurement data at 6.5 GHz with 500 MHz of bandwidth, we first estimate potential MPCs utilizing the space-alternating generalized expectation-maximization (SAGE) algorithm. Then, we cluster the extracted MPCs considering their static and dynamic characteristics by employing K-Power-Means (KPM) algorithm under multipath component distance (MCD) measure. For characterizing time-variant clusters, we exploit a clustering-based tracking (CBT) method, which efficiently quantifies the survival lengths of clusters. Ultimately, we establish a cluster-based channel model, and validations illustrate the accuracy of the proposed model. This work not only promotes a better understanding of AG propagation channels but also provides a general cluster-based AG channel model with certain extensibility.

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arXiv2021

Coverage Analysis of Cellular-Connected UAV Communications with 3GPP Antenna and Channel Models

For reliable and efficient communications of aerial platforms, such as unmanned aerial vehicles (UAVs), the cellular network is envisioned to provide connectivity for the aerial and ground user equipment (GUE) simultaneously, which brings challenges to the existing pattern of the base station (BS) tailored for ground-level services. Thus, we focus on the coverage probability analysis to investigate the coexistence of aerial and terrestrial users, by employing realistic antenna and channel models reported in the 3rd Generation Partnership Project (3GPP). The homogeneous Poisson point process (PPP) is used to describe the BS distribution, and the BS antenna is adjustable in the down-tilted angle and the number of the antenna array. Meantime, omnidirectional antennas are used for cellular users. We first derive the approximation of coverage probability and then conduct numerous simulations to evaluate the impacts of antenna numbers, down-tilted angles, carrier frequencies, and user heights. One of the essential findings indicates that the coverage probabilities of high-altitude users become less sensitive to the down-tilted angle. Moreover, we found that the aerial user equipment (AUE) in a certain range of heights can achieve the same or better coverage probability than that of GUE, which provides an insight into the effective deployment of cellular-connected aerial communications.

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arXiv2021

Channel Modeling for UAV Communications: State of the Art, Case Studies, and Future Directions

As essential aerial platforms, unmanned aerial vehicles (UAVs) play an increasingly important role in broad wireless connectivity and high-data-rate transmission for future communication systems. Notably, various communication scenarios are involved in UAV communications, such as intercommunications between UAVs and communications with the ground user equipment, the cellular base station, and the ground station, to name a few. However, existing works mostly focus on a single communication scenario, a designated channel type, and a specific operating frequency, thus urgently requiring a comprehensive understanding of multi-scenario, multi-frequency, and multi-type UAV channels. This article pours attention into the essentials of corresponding air-to-air (A2A) and air-to-ground (A2G) channels in UAV communications. We first identify the latest key challenges of channel modeling for UAV communications. We then provide the state of the art for A2A and A2G channel properties and models based on extensive measurement campaigns. In particular, we conduct realistic case studies to further demonstrate critical channel characterizations and machine learning-based modeling methods. Last but not least, potential directions are widely discussed for paving the way towards more accurate and effective channel models for UAV communications.

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arXiv2021

Scoring the Terabit/s Goal:Broadband Connectivity in 6G

This paper explores the road to vastly improving the broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, with peak data rates up to 1 Tbps. Several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be mainly used for pushing the peak rates of point-to-point links. Finally, at the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latency, higher reliability, and reduced complexity.

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arXiv2020

Coverage Probability Analysis of IRS-Aided Communication Systems

The intelligent reflective surface (IRS) technology has received many interests in recent years, thanks to its potential uses in future wireless communications, in which one of the promising use cases is to widen coverage, especially in the line-of-sight-blocked scenarios. Therefore, it is critical to analyze the corresponding coverage probability of IRS-aided communication systems. To our best knowledge, however, previous works focusing on this issue are very limited. In this paper, we analyze the coverage probability under the Rayleigh fading channel, taking the number and size of the array elements into consideration. We first derive the exact closed-form of coverage probability for the unit element. Afterward, with the method of moment matching, the approximation of the coverage probability can be formulated as the ratio of upper incomplete Gamma function and Gamma function, allowing an arbitrary number of elements. Finally, we comprehensively evaluate the impacts of essential factors on the coverage probability, such as the coefficient of fading channel, the number and size of the element, and the angle of incidence. Overall, the paper provides a succinct and general expression of coverage probability, which can be helpful in the performance evaluation and practical implementation of the IRS.

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arXiv2020

Satellite-Terrestrial Channel Characterization in High-Speed Railway Environment at 22.6 GHz

The integration of satellite and terrestrial communication systems plays a vital role in the fifth-generation mobile communication system (5G) for the ubiquitous coverage, reliable service and flexible networking. Moreover, the millimeter wave (mmWave) communication with large bandwidth is a key enabler for 5G intelligent rail transportation. In this paper, the satellite-terrestrial channel at 22.6 GHz is characterized for a typical high-speed railway (HSR) environment. The three-dimensional model of the railway scenario is reconstructed and imported into the Cloud Ray-Tracing (CloudRT) simulation platform. Based on extensive ray-tracing simulations, the channel for the terrestrial HSR system and the satellite-terrestrial system with two weather conditions are characterized, and the interference between them are evaluated. The results of this paper can help for the design and evaluation for the satellite-terrestrial communication system enabling future intelligent rail transportation.

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arXiv2020

White Paper on Broadband Connectivity in 6G

This white paper explores the road to implementing broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, from extreme capacity with peak data rates up to 1 Tbps, to raising the typical data rates by orders-of-magnitude, to support broadband connectivity at railway speeds up to 1000 km/h. To achieve these goals, not only the terrestrial networks will be evolved but they will also be integrated with satellite networks, all facilitating autonomous systems and various interconnected structures. We believe that several categories of enablers at the infrastructure, spectrum, and protocol/ algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric and scalable cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be used for pushing the peak rates of point-to-point links. The latter path will lead to THz communications complemented by visible light communications in specific scenarios. At the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latencies, higher reliability, and reduced complexity. Different options will be needed to optimally support different use cases. The resource efficiency can be further improved by using various combinations of full-duplex radios, interference management based on rate-splitting, machine-learning-based optimization, coded caching, and broadcasting.

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arXiv2019

Probabilistic Two-Ray Model for Air-to-Air Channel in Built-Up Areas

In this paper, we present a probabilistic two-ray (PTR) path loss model for air-to-air (AA) propagation channel in built-up areas. Based on the statistical model of city deployment, the PTR path loss model can be applied to suburban, urban, dense urban, and high-rise urban. The path loss is optimally fitted as the Weibull distribution and its fluctuation is fitted as the Normal distribution in ray-tracing simulations. The good agreements between our model and ray tracing indicate the proposed model can provide a useful tool for accurate and quick prediction for aerial platforms. As an extended research of PTR model, we extract the shadowing factor by numerous simulations and propose the altitude-dependent shadowing model. The result shows that the proposed shadowing model has very good consistent with the measurement-based model, which indicates that our research performs well in the extensibility and generality.

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