arXiv subjects

Cheng-Xiang Wang

Publications and source records attributed to Cheng-Xiang Wang.

At least 73 records · Page 4Linked to original sources

arXiv2023

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed.

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arXiv2022

Channel Acquisition for HF Skywave Massive MIMO-OFDM Communications

In this paper, we investigate channel acquisition for high frequency (HF) skywave massive multiple-input multiple-output (MIMO) communications with orthogonal frequency division multiplexing (OFDM) modulation. We first introduce the concept of triple beams (TBs) in the space-frequency-time (SFT) domain and establish a TB based channel model using sampled triple steering vectors. With the established channel model, we then investigate the optimal channel estimation and pilot design for pilot segments. Specifically, we find the conditions that allow pilot reuse among multiple user terminals (UTs), which significantly reduces pilot overhead and increases the number of UTs that can be served. Moreover, we propose a channel prediction method for data segments based on the estimated TB domain channel. To reduce the complexity, we formulate the channel estimation as a statistical inference problem and then obtain the channel by the proposed constrained Bethe free energy minimization (CBFEM) based channel estimation algorithm, which can be implemented with low complexity by exploiting the structure of the TB matrix together with the chirp z-transform (CZT). Simulation results demonstrate the superior performance of the proposed channel acquisition approach.

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arXiv2022

Fingerprint Based mmWave Positioning System Aided by Reconfigurable Intelligent Surface

Reconfigurable intelligent surface (RIS) is a promising technique for millimeter wave (mmWave) positioning systems. In this paper, we consider multiple mobile users (MUs) positioning problem in the multiple-input multiple-output (MIMO) time-division duplex (TDD) mmWave systems aided by the RIS. We derive the expression for the space-time channel response vector (STCRV) as a novel type of fingerprint. The STCRV consists of the multipath channel characteristics, e.g., time delay and angle of arrival (AOA), which is related to the position of the MU. By using the STCRV as input, we propose a novel residual convolution network regression (RCNR) learning algorithm to output the estimated three-dimensional (3D) position of the MU. Specifically, the RCNR learninng algorithm includes a data processing block to process the input STCRV, a normal convolution block to extract the features of STCRV, four residual convolution blocks to further extract the features and protect the integrity of the features, and a regression block to estimate the 3D position. Extensive simulation results are also presented to demonstrate that the proposed RCNR learning algorithm outperforms the traditional convolution neural network (CNN).

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arXiv2022

Channel Modeling for UAV-to-Ground Communications with Posture Variation and Fuselage Scattering Effect

Unmanned aerial vehicle (UAV)-to-ground (U2G) channel models play a pivotal role for reliable communications between UAV and ground terminal. This paper proposes a three-dimensional (3D) non-stationary hybrid model including both large-scale and small-scale fading for U2G multiple-input-multiple-output (MIMO) channels. Distinctive channel characteristics under U2G scenarios, i.e., 3D trajectory and posture of UAV, fuselage scattering effect (FSE), and posture variation fading (PVF), are incorporated into the proposed model. The channel parameters, i.e., path loss (PL), shadow fading (SF), path delay, and path angle, are generated incorporating machine learning (ML) and ray tracing (RT) techniques to capture the structure-related characteristics. In order to guarantee the physical continuity of channel parameters such as Doppler phase and path power, the time evolution methods of inter- and intra- stationary intervals are proposed. Key statistical properties , i.e., temporal autocorrection function (ACF), power delay profile (PDP), level crossing rate (LCR), average fading duration (AFD), and stationary interval (SI) are given, and the impact of the change of fuselage and posture variation is analyzed. It is demonstrated that both posture variation and fuselage scattering have crucial effects on channel characteristics. The validity and practicability of the proposed model are verified by comparing the simulation results with the measured ones.

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arXiv2022

An SBR Based Ray Tracing Channel Modeling Method for THz and Massive MIMO Communications

Terahertz (THz) communication and the application of massive multiple-input multiple-output (MIMO) technology have been proved significant for the sixth generation (6G) communication systems, and have gained global interests. In this paper, we employ the shooting and bouncing ray (SBR) method integrated with acceleration technology to model THz and massive MIMO channel. The results of ray tracing (RT) simulation in this paper, i.e., angle of departure (AoD), angle of arrival (AoA), and power delay profile (PDP) under the frequency band supported by the commercial RT software Wireless Insite (WI) are in agreement with those produced by WI. Based on the Kirchhoff scattering effect on material surfaces and atmospheric absorption loss showing at THz frequency band, the modified propagation models of Fresnel reflection coefficients and free-space attenuation are consistent with the measured results. For massive MIMO, the channel capacity and the stochastic power distribution are analyzed. The results indicate the applicability of SBR method for building deterministic models of THz and massive MIMO channels with extensive functions and acceptable accuracy.

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arXiv2022

A Weighted Random Forest Based PositioningAlgorithm for 6G Indoor Communications

Due to the indoor none-line-of-sight (NLoS) propagation and multi-access interference (MAI), it is a great challenge to achieve centimeter-level positioning accuracy in indoor scenarios. However, the sixth generation (6G) wireless communications provide a good opportunity for the centimeter-level positioning. In 6G, the millimeter wave (mmWave) and terahertz (THz) communications have ultra-broad bandwidth so that the channel state information (CSI) will have a high resolution. In this paper, a weighted random forest (WRF) based indoor positioning algorithm using CSI based channel fingerprint feature is proposed to achieve high-precision positioning for 6G indoor communications. In addition, ray-tracing (RT) is used to improve the efficiency of establishing channel fingerprint database. The simulation results demonstrate the accuracy and robustness of the proposed algorithm. It is shown that the positioning accuracy of the algorithm is stable within 6 cm in different indoor scenarios with the channel fingerprint database established at 0.2 m intervals.

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arXiv2022

An Improved Ray Tracing Acceleration Algorithm Based on Bounding Volume Hierarchies

Ray tracing is an efficient channel modeling method. However, the traditional ray tracing method has high computation complexity. To solve this problem, an improved bounding volume hierarchies (BVH) algorithm is proposed in this paper. Based on surface area heuristic (SAH) and spatial distance, the proposed algorithm can effectively reduce the number of unnecessary intersection tests between ray and triangular facets. In addition, the algorithm fully considers the influence of ray action range, which can not only make up for the defects of spatial division based on uniform grid method and k-dimensional (KD) tree, but also solve the problem of unsatisfactory spatial division based on traditional BVH algorithm. The simulation results show that compared with the traditional BVH algorithm, the proposed algorithm can improve the computation efficiency by 20% to 35% while ensuring the computation accuracy.

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arXiv2022

An Improved Equiangular Division Algorithm for SBR based Ray Tracing Channel Modeling

Compared with image method (IM) based ray tracing (RT), shooting and bouncing ray (SBR) method is characterized by fast speed but low accuracy. In this paper, an iterative precise algorithm based on equiangular division is proposed to make rough paths accurate, allowing SBR to calculate exact channel information. Different ray launching methods are compared to obtain a better launching method. By using equiangular division, rays are launched more uniformly from transmitter (Tx) compared with the current equidistant division method. With the proposed iterative precise algorithm, error of angle of departure (AOD) and angle of arrival (AOA) is below 0.01 degree. The relationship between the number of iterations and error reduction is also given. It is illustrated that the proposed method has the same accuracy as IM by comparing the power delay profile (PDP) and angle distribution of paths. This can solve the problem of low accuracy brougth by SBR.

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arXiv2022

Integrating Satellites and Mobile Edge Computing for 6G Wide-Area Edge Intelligence: Minimal Structures and Systematic Thinking

The sixth-generation (6G) network will shift its focus to supporting everything including various machine-type devices (MTDs) in an everyone-centric manner. To ubiquitously cover the MTDs working in rural and disastrous areas, satellite communications become indispensable, while mobile edge computing (MEC) also plays an increasingly crucial role. Their sophisticated integration enables wide-area edge intelligence which promises to facilitate globally-distributed customized services. In this article, we present typical use cases of integrated satellite-MEC networks and discuss the main challenges therein. Inspired by the protein structure and the systematic engineering methodology, we propose three minimal integrating structures, based on which a complex integrated satellite-MEC network can be treated as their extension and combination. We discuss the unique characteristics and key problems of each minimal structure. Accordingly, we establish an on-demand network orchestration framework to enrich the hierarchy of network management, which further leads to a process-oriented network optimization method. On that basis, a case study is utilized to showcase the benefits of on-demand network orchestration and process-oriented network optimization. Finally, we outline potential research issues to envision a more intelligent, more secure, and greener integrated network.

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arXiv2022

Reconfigurable intelligent surfaces: Channel characterization and modeling

Reconfigurable intelligent surfaces (RISs) are two dimensional (2D) metasurfaces which can intelligently manipulate electromagnetic waves by low-cost near passive reflecting elements. RIS is viewed as a potential key technology for the sixth generation (6G) wireless communication systems mainly due to its advantages in tuning wireless signals, thus smartly controlling propagation environments. In this paper, we aim at addressing channel characterization and modeling issues of RIS-assisted wireless communication systems. At first, the concept, principle, and potential applications of RIS are given. An overview of RIS based channel measurements and experiments is presented by classifying frequency bands, scenarios, system configurations, RIS constructions, experiment purposes, and channel observations. Then, RIS based channel characteristics are studied, including reflection and transmission, Doppler effect and multipath fading mitigation, channel reciprocity, channel hardening, rank improvement, far field and near field, etc. RIS based channel modeling works are investigated, including largescale path loss models and small-scale multipath fading models. At last, future research directions related to RIS-assisted channels are also discussed.

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arXiv2022

Pervasive wireless channel modeling theory and applications to 6G GBSMs for all frequency bands and all scenarios

In this paper, a pervasive wireless channel modeling theory is first proposed, which uses a unified channel modeling method and a unified equation of channel impulse response (CIR), and can integrate important channel characteristics at different frequency bands and scenarios. Then, we apply the proposed theory to a three dimensional (3D) space-time-frequency (STF) non-stationary geometry-based stochastic model (GBSM) for the sixth generation (6G) wireless communication systems. The proposed 6G pervasive channel model (6GPCM) can characterize statistical properties of channels at all frequency bands from sub-6 GHz to visible light communication (VLC) bands and all scenarios such as unmanned aerial vehicle (UAV), maritime, (ultra-)massive multiple-input multiple-output (MIMO), reconfigurable intelligent surface (RIS), and industry Internet of things (IIoT) scenarios. By adjusting channel model parameters, the 6GPCM can be reduced to various simplified channel models for specific frequency bands and scenarios. Also, it includes standard fifth generation (5G) channel models as special cases. In addition, key statistical properties of the proposed 6GPCM are derived, simulated, and verified by various channel measurement results, which clearly demonstrates its accuracy, pervasiveness, and applicability.

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arXiv2022

Geometry-Based Stochastic Probability Models for the LoS and NLoS Paths of A2G Channels under Urban Scenario

Path probability prediction is essential to describe the dynamic birth and death of propagation paths, and build the accurate channel model for air-to-ground (A2G) communications. The occurrence probability of each path is complex and time-variant due to fast changeable altitudes of UAVs and scattering environments. Considering the A2G channels under urban scenarios, this paper presents three novel stochastic probability models for the line-of-sight (LoS) path, ground specular (GS) path, and building-scattering (BS) path, respectively. By analyzing the geometric stochastic information of three-dimensional (3D) scattering environments, the proposed models are derived with respect to the width, height, and distribution of buildings. The effect of Fresnel zone and altitudes of transceivers are also taken into account. Simulation results show that the proposed LoS path probability model has good performance at different frequencies and altitudes, and is also consistent with existing models at the low or high altitude. Moreover, the proposed LoS and NLoS path probability models show good agreement with the ray-tracing (RT) simulation method.

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arXiv2022

Spectrum-Energy-Economy Efficiency Trade-off of Wireless Communication Systems with Separated Indoor/Outdoor Scenarios for 5G and B5G

In this paper, we consider a heterogeneous 5G cellular architecture that separates the outdoor and indoor scenarios and in particular study the trade-off between the spectrum efficiency (SE), energy efficiency (EE), economy efficiency (ECE). Mathematical expressions for the system capacity, EE, SE, and ECE respectively are derived using a proposed realistic power consumption model. The comparison of system performance in terms of SE, EE, and ECE, results in the observation that the proposed network architecture, which separates the outdoor and indoor scenarios, offers a promising solution for future communication systems that have strict requirements on the data rate and efficiency.

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arXiv2022

A Novel 3D Non-Stationary Channel Model for 6G Indoor Visible Light Communication Systems

The visible light communication (VLC) technology has attracted much attention in the research of the sixth generation (6G) communication systems. In this paper, a novel three dimensional (3D) space-time-frequency non-stationary geometry-based stochastic model (GBSM) is proposed for indoor VLC channels. The proposed VLC GBSM can capture unique indoor VLC channel characteristics such as the space-time-frequency non-stationarity caused by large light-emitting diode (LED) arrays in indoor scenarios, long travelling paths, and large bandwidths of visible light waves, respectively. In addition, the proposed model can support special radiation patterns of LEDs, 3D translational and rotational motions of the optical receiver (Rx), and can be applied to angle diversity receivers (ADRs). Key channel properties are simulated and analyzed, including the space-time-frequency correlation function (STFCF), received power, root mean square (RMS) delay spread, and path loss (PL). Simulation results verify the space-time-frequency non-stationarity in indoor VLC channels. Finally, the accuracy and practicality of the proposed model are validated by comparing the simulation result of channel 3dB bandwidth with the existing measurement data. The proposed channel model will play a supporting role in the design of future 6G VLC systems.

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arXiv2021

Artificial intelligence enabled radio propagation for communications-Part I: Channel characterization and antenna-channel optimization

To provide higher data rates, as well as better coverage, cost efficiency, security, adaptability, and scalability, the 5G and beyond 5G networks are developed with various artificial intelligence techniques. In this two-part paper, we investigate the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. It firstly provides a comprehensive overview of ML for channel characterization and ML-based antenna-channel optimization in this first part, and then it gives a state-of-the-art literature review of channel scenario identification and channel modeling in Part II. Fundamental results and key concepts of ML for communication networks are presented, and widely used ML methods for channel data processing, propagation channel estimation, and characterization are analyzed and compared. A discussion of challenges and future research directions for ML-enabled next generation networks of the topics covered in this part rounds off the paper.

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arXiv2021

Artificial intelligence enabled radio propagation for communications-Part II: Scenario identification and channel modeling

This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. In Part I, we introduced AI and ML as well as provided a comprehensive survey on ML enabled channel characterization and antenna-channel optimization, and in this part (Part II) we review state-of-the-art literature on scenario identification and channel modeling here. In particular, the key ideas of ML for scenario identification and channel modeling/prediction are presented, and the widely used ML methods for propagation scenario identification and channel modeling and prediction are analyzed and compared. Based on the state-of-art, the future challenges of AI/ML-based channel data processing techniques are given as well.

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arXiv2021

A Geometry-Based Stochastic Model for Truck Communication Channels in Freeway Scenarios

Vehicle-to-vehicle (V2V) wireless communication systems are fundamental in many intelligent transportation applications, e.g., traffic load control, driverless vehicle, and collision avoidance. Hence, developing appropriate V2V communication systems and standardization require realistic V2V propagation channel models. However, most existing V2V channel modeling studies focus on car-to-car channels; only a few investigate truck-to-car (T2C) or truck-to-truck (T2T) channels. In this paper, a hybrid geometry-based stochastic model (GBSM) is proposed for T2X (T2C or T2T) channels in freeway environments. Next, we parameterize this GBSM from the extensive channel measurements. We extract the multipath components (MPCs) by using a joint maximum likelihood estimation (RiMAX) and then cluster the MPCs based on their evolution patterns.We classify the determined clusters as line-of-sight, multiple-bounce reflections from static interaction objects (IOs), multiple-bounce reflections from mobile IOs, multiple-bounce reflections, and diffuse scattering. Specifically, we model multiple-bounce reflections as double clusters following the COST 273/COST2100 method. This article presents the complete parameterization of the channel model. We validate this model by contrasting the root-mean-square delay spread and the angular spreads of departure/arrival derived from the channel model with the outcomes directly derived from the measurements.

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arXiv2021

Multi-Frequency Wireless Channel Measurements and Characteristics Analysis in Indoor Corridor Scenarios

In this paper, we conduct wireless channel measurements in indoor corridor scenarios at 2.4, 5 and 6 GHz bands with bandwidth of 320 MHz. The measurement results of channel characteristics at different frequency bands such as average power delay profile (APDP), path loss (PL), delay spread (DS), and Ricean K factor (KF) are presented and analyzed. It is found that the PL exponent (PLE) and PL offset βin the floating-intercept (FI) model tend to increase with the increase of frequency. The DS and KF values of the three frequency bands in line of sight (LOS) scenario are basically the same. These results are significant for the design of communication systems.

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