Xuefeng Yin

Bio: Xuefeng Yin is an academic researcher from Tongji University. The author has contributed to research in topics: Communication channel & MIMO. The author has an hindex of 24, co-authored 170 publications receiving 2082 citations. Previous affiliations of Xuefeng Yin include Aalborg University.

Future railway services-oriented mobile communications network

Abstract: The future development of the railway is highly desired to evolve into a new era where infrastructure, trains, travelers, and goods will be increasingly interconnected to provide high comfort, with optimized door-to-door mobility at higher safety. For this vision, it is required to realize seamless high data rate wireless connectivity for railways. To improve the safety and comfort of future railways, wireless communications for railways are required to evolve from only voice and traditional train control signaling services to various high data rate services including critical high-definition (HD) video and other more bandwidth-intensive passenger services, such as onboard and wayside HD video surveillance, onboard real-time high data rate services, train multimedia dispatching video streaming, railway mobile ticketing, and the Internet of Things for railways. Corresponding mobile communications network architecture under various railway scenarios including inter-car, intra-car, inside station, train-to-infrastructure and infrastructure- to-infrastructure are proposed in this article. Wireless coverage based on massive MIMO for railway stations and train cars is proposed to fulfill the requirement of high-data-rate and high spectrum efficiency. The technical challenges brought by the massive MIMO technique are discussed as well.

Cluster Characteristics in a MIMO Indoor Propagation Environment

Abstract: Essential parameters of physical, propagation-based MIMO channel models are the fading statistics and the directional spread of multipath clusters. In this paper we determine these parameters in the azimuth-of-arrival/azimuth-of-departure (AoA/AoD) domain based on comprehensive indoor MIMO measurements at 5.2 GHz in a cluttered office environment using the SAGE algorithm for parameter estimation. Due to cluster identification in AoA/AoD-domain we found a greater number of clusters than those reported in previous publications. Regarding the fading statistics of clusters, so far not studied, strong (obstructed-)line-of-sight clusters show Rician fading, corresponding to few dominant propagation paths, whereas most clusters exhibit Rayleigh fading, corresponding to many paths with approximately equal powers and uncorrelated phases. Root-mean-square cluster azimuth spreads (CASs) were estimated with a novel method by appropriately restricting the support of the cluster azimuth distribution. We found that the estimated CASs are different when seen from transmitter or receiver, i.e. their ranges are from 2deg to 9deg and from 2deg to 7deg at the transmitter side and the receiver side, respectively

Ray-Tracing-Based mm-Wave Beamforming Assessment

Abstract: The use of large-size antenna arrays to implement pencil-beam forming techniques is becoming a key asset to cope with the very high throughput density requirements and high path-loss of future millimeter-wave (mm-wave) gigabit-wireless applications. Suboptimal beamforming (BF) strategies based on search over discrete set of beams (steering vectors) are proposed and implemented in present standards and applications. The potential of fully adaptive advanced BF strategies that will become possible in the future, thanks to the availability of accurate localization and powerful distributed computing, is evaluated in this paper through system simulation. After validation and calibration against mm-wave directional indoor channel measurements, a 3-D ray tracing model is used as a propagation-prediction engine to evaluate performance in a number of simple, reference cases. Ray tracing itself, however, is proposed and evaluated as a real-time prediction tool to assist future BF techniques.

An Empirical Air-to-Ground Channel Model Based on Passive Measurements in LTE

Abstract: In this paper, a recently conducted measurement campaign for unmanned-aerial-vehicle channels is introduced. The downlink signals of an in-service long-time-evolution network, which is deployed in a suburban scenario were acquired. Five horizontal and five vertical flight routes were considered. The channel impulse responses (CIRs) are extracted from the received data by exploiting the cell-specific signals, and the underlying physical propagation mechanisms are interpreted by exploiting the propagation graph modeling approach. Based on the CIRs, the parameters of multipath components are estimated by using a high-resolution algorithm derived according to the space-alternating generalized expectation-maximization (SAGE) principle. Based on the SAGE results, channel characteristics including the path loss, shadow fading, fast fading, delay spread, and Doppler frequency spread are thoroughly investigated for different heights and horizontal distances, which constitute a stochastic model.

A 3D Geometry-Based Stochastic Channel Model for UAV-MIMO Channels

Abstract: Unmanned Aerial Vehicles (UAVs) have been a promising platform in realizing high-speed wireless networks. As an emerging scenario, the UAV communication is distinct from widely used cellular systems or vehicular networks, requiring the development of practical yet easy-to-use channel models. In this paper, for the first time we introduce the geometry-based stochastic model (GBSM) to UAV channel modeling, and propose a new three- dimensional (3D) GBSM for UAV Multi-Input Multi- Output (UAV-MIMO) channels. Based on the proposed model, we derive and investigate the space-time correlation function (STCF) under a 3D moving and scattering environment. The usefulness of this model is verified by the comparison between the theoretical results and some measurement data.

Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling

Abstract: ‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels

Abstract: High-rate data communication over a multipath wireless channel often requires that the channel response be known at the receiver. Training-based methods, which probe the channel in time, frequency, and space with known signals and reconstruct the channel response from the output signals, are most commonly used to accomplish this task. Traditional training-based channel estimation methods, typically comprising linear reconstruction techniques, are known to be optimal for rich multipath channels. However, physical arguments and growing experimental evidence suggest that many wireless channels encountered in practice tend to exhibit a sparse multipath structure that gets pronounced as the signal space dimension gets large (e.g., due to large bandwidth or large number of antennas). In this paper, we formalize the notion of multipath sparsity and present a new approach to estimating sparse (or effectively sparse) multipath channels that is based on some of the recent advances in the theory of compressed sensing. In particular, it is shown in the paper that the proposed approach, which is termed as compressed channel sensing (CCS), can potentially achieve a target reconstruction error using far less energy and, in many instances, latency and bandwidth than that dictated by the traditional least-squares-based training methods.

Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond

Abstract: Unmanned aerial vehicles (UAVs) have found numerous applications and are expected to bring fertile business opportunities in the next decade. Among various enabling technologies for UAVs, wireless communication is essential and has drawn significantly growing attention in recent years. Compared to the conventional terrestrial communications, UAVs’ communications face new challenges due to their high altitude above the ground and great flexibility of movement in the 3-D space. Several critical issues arise, including the line-of-sight (LoS) dominant UAV-ground channels and induced strong aerial-terrestrial network interference, the distinct communication quality-of-service (QoS) requirements for UAV control messages versus payload data, the stringent constraints imposed by the size, weight, and power (SWAP) limitations of UAVs, as well as the exploitation of the new design degree of freedom (DoF) brought by the highly controllable 3-D UAV mobility. In this article, we give a tutorial overview of the recent advances in UAV communications to address the above issues, with an emphasis on how to integrate UAVs into the forthcoming fifth-generation (5G) and future cellular networks. In particular, we partition our discussion into two promising research and application frameworks of UAV communications, namely UAV-assisted wireless communications and cellular-connected UAVs, where UAVs are integrated into the network as new aerial communication platforms and users, respectively. Furthermore, we point out promising directions for future research.

Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications

Abstract: The availability of location information has become a key factor in today's communications systems allowing location based services. In outdoor scenarios, the mobile terminal position is obtained with high accuracy thanks to the global positioning system (GPS) or to the standalone cellular systems. However, the main problem of GPS and cellular systems resides in the indoor environment and in scenarios with deep shadowing effects where the satellite or cellular signals are broken. In this paper, we survey different technologies and methodologies for indoor and outdoor localization with an emphasis on indoor methodologies and concepts. Additionally, we discuss in this review different localization-based applications, where the location information is critical to estimate. Finally, a comprehensive discussion of the challenges in terms of accuracy, cost, complexity, security, scalability, etc. is given. The aim of this survey is to provide a comprehensive overview of existing efforts as well as auspicious and anticipated dimensions for future work in indoor localization techniques and applications.

UAV Communications for 5G and Beyond: Recent Advances and Future Trends

Abstract: Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important component of the upcoming wireless networks that can potentially facilitate wireless broadcast and support high rate transmissions. Compared to the communications with fixed infrastructure, UAV has salient attributes, such as flexible deployment, strong line-of-sight connection links, and additional design degrees of freedom with the controlled mobility. In this paper, a comprehensive survey on UAV communication toward 5G/B5G wireless networks is presented. We first briefly introduce essential background and the space–air–ground integrated networks, as well as discuss related research challenges faced by the emerging integrated network architecture. We then provide an exhaustive review of various 5G techniques based on UAV platforms, which we categorize by different domains, including physical layer, network layer, and joint communication, computing, and caching. In addition, a great number of open research problems are outlined and identified as possible future research directions.