| 1. |
- Wen, Fuxi, 1982, et al.
(author)
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A survey on 5G massive MIMO Localization
- 2019
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In: Digital Signal Processing: A Review Journal. - : Elsevier BV. - 1051-2004 .- 1095-4333. ; 94:November 2019, s. 21-28
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Journal article (peer-reviewed)abstract
- Massive antenna arrays can be used to meet the requirements of 5G, by exploiting different spatial signatures of users. This same property can also be harnessed to determine the locations of those users. In order to perform massive MIMO localization, refined channel estimation routines and localization methods have been developed. This paper provides a brief overview of this emerging field.
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| 2. |
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| 3. |
- Guan, Ke, et al.
(author)
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Channel Characterization for Intra-Wagon Communication at 60 and 300 GHz Bands
- 2019
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In: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 68:6, s. 5193-5207
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Journal article (peer-reviewed)abstract
- © 1967-2012 IEEE. In this paper, the intra-wagon channels at 60 and 300 GHz bands are characterized through measurement-validated ray-tracing (RT) simulations. To begin with, an in-house-developed three-dimensional RT simulator is calibrated and validated by a series of millimeter-wave and Terahertz channel measurements inside a high-speed train wagon. Then, the validated RT simulator is used to conduct extensive simulations with different transmitter (Tx) and receiver deployments. At low frequencies, the channel is strongly influenced by the line of sight (LOS), and therefore, is usually classified into LOS and non-LOS (NLOS) regions. However, the simulation results at 60 and 300 GHz bands show that the first-order reflection also imposes a significant impact on the channel characteristics. This motivates us to further classify the NLOS region into light-NLOS (L-NLOS) and deep-NLOS (D-NLOS) according to the existence of the first-order reflection. Through analyzing the area ratios of LOS, L-NLOS, and D-NLOS regions, we evaluate the Tx deployment strategies and suggest the optimum one. Based on RT simulation results, totally 12 cases (three propagation regions with two Tx deployments at two frequencies) are characterized in terms of path loss, shadow fading, root-mean-square delay spread, Rician K-factor, azimuth/elevation angular spread of arrival/departure, cross-polarization ratio, and their cross correlations. All these parameters are fed into the 3GPP-like quasi-deterministic radio channel generator (QuaDRiGa). The good agreement between QuaDRiGa and RT proves that the 13 tables provided in this paper effectively parameterize the intra-wagon scenario for the standard channel model family. These results provide valuable insights into the system design and evaluation for intra-wagon communications.
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| 4. |
- Guan, Ke, et al.
(author)
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Channel Sounding and Ray Tracing for Train-to-Train Communications at the THz Band
- 2019
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In: 13th European Conference on Antennas and Propagation, EuCAP 2019. ; March 2019
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Conference paper (peer-reviewed)abstract
- In order to increase railway capacity for passengers and freight, it is necessary to realize virtual coupling technology through train-to-train (T2T) communications. This T2T link requires large bandwidth for high-data rate and low latency, forming a strong motivation to explore terahertz (THz) band. In this paper, the T2T channel is characterized through ultrawideband (UWB) channel sounding and ray tracing at THz band for the first time. To begin with, a series of T2T channel sounding measurements are performed in a train test center at 300 GHz with 8 GHz bandwidth. Correspondingly, Rician K-factor and root-mean-square (RMS) delay spread are extracted from the measured power-delay profile (PDP). After validated by the measurements, a self-developed ray-tracing (RT) simulator is used to physically interpret the propagation mechanism constitution and significant objects in the target scenario. This provides the first hand information of how the communicating trains themselves influence the T2T channel, and therefore, lays the foundation for channel modeling through extended RT simulations in the future.
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| 5. |
- Guan, Ke, et al.
(author)
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Measurement, simulation, and characterization of train-To-infrastructure inside-station channel at the terahertz band
- 2019
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In: IEEE Transactions on Terahertz Science and Technology. - 2156-342X .- 2156-3446. ; 9:3, s. 291-306
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Journal article (peer-reviewed)abstract
- © 2011-2012 IEEE. In this paper, we measure, simulate, and characterize the train-To-infrastructure (T2I) inside-station channel at the terahertz (THz) band for the first time. To begin with, a series of channel measurements is performed in a train test center at 304.2 GHz with 8 GHz bandwidth. Rician K-factor and root-mean-square (RMS) delay spread are extracted from the measured power-delay profile. With the aid of an in-house-developed ray-Tracing (RT) simulator, the multipath constitution is physically interpreted. This provides the first hand information of how the communicating train itself and the other train on site influence the channel. Using this measurement-validated RT simulator, we extend the measurement campaign to more realistic T2I inside-station channel through extensive simulations with various combinations of transmitter deployments and train conditions. Based on RT results, all cases of the target channel are characterized in terms of path loss, shadow fading, RMS delay spread, Rician K-factor, azimuth/elevation angular spread of arrival/departure, cross-polarization ratio, and their cross correlations. All parameters are fed into and verified by the 3GPP-like quasi-deterministic radio channel generator. This can provide the foundation for future work that aims to add the T2I inside-station scenario into the standard channel model families, and furthermore, provides a baseline for system design and evaluation of THz communications.
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| 6. |
- Guan, Ke, et al.
(author)
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Millimeter-wave communications for smart rail mobility: From channel modeling to prototyping
- 2019
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In: 2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019 - Proceedings.
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Conference paper (peer-reviewed)abstract
- In this paper, we present an integration solution from channel modeling to prototyping, to realize millimeter-wave (mmWave) communications for smart rail mobility. In order to involve the railway features in the channel models, two mmWave channel models are established based on ray-tracing simulations in realistic railway scenarios. Moreover, the challenges raised by mmWave directional network under high mobility is overcome by our solutions concerning handover scheme, random access procedure, and beamforming strategies. By integrating these key enabling technologies, we prototype the mobile hotspot network (MHN) system which realizes 1.25 Gbps downlink data throughput in a subway line with the train speed of 80 km/h.
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| 7. |
- Guan, Ke, et al.
(author)
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Towards realistic high-speed train channels at 5G millimeter-wave band - Part I: Paradigm, significance analysis, and scenario reconstruction
- 2018
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In: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 67:10, s. 9112-9128
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Journal article (peer-reviewed)abstract
- The upcoming fifth-generation (5G) mobile communication system is expected to support high mobility up to 500 km/h, which is envisioned in particular for high-speed trains. Millimeter wave (mmWave) spectrum is considered as a key enabler for offering the 'best experience' to highly mobile users. Despite that channel characterization is necessary for the mmWave system design and validation, it is still not feasible to directly do extensive mmWave mobile channel measurements on moving high-speed trains (HST) at a speed up to 500 km/h in the present. Thus, rather than conducting mmWave HST channel sounding directly with high mobility, this study proposes a viable paradigm for realizing the realistic HST channels at the 5G mmWave band. We first propose the whole paradigm. Then, we define the scenario of interest and select the main objects and materials. Afterwards, the electromagnetic and scattering parameters of the materials are measured and estimated between 26.5 GHz and 40 GHz. With this information, the most influential materials are determined through significance analysis. Correspondingly, we reconstruct the three-dimensional mmWave outdoor HST and tunnel scenario models. Through extensive ray-tracing simulations, we determine the main propagation mechanisms in these two scenarios, the channel models based on that are validated by measurements. This verifies the whole paradigm proposed in this paper.
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| 8. |
- Guan, Ke, et al.
(author)
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Towards realistic high-speed train channels at 5G millimeter-wave band - Part II: Case study for paradigm implementation
- 2018
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In: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 67:10, s. 9129-9144
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Journal article (peer-reviewed)abstract
- © 1967-2012 IEEE. In this paper, we present two case studies for generating realistic high-speed train (HST) channels at fifth-generation (5G) millimeter-wave (mmWave) band. The first one is the tunnel environment at relatively low 5G mmWave band, 30 GHz band, whereas the second one is the outdoor HST environment at relatively high 5G mmWave band, 90 GHz band. Both case studies include the following steps: ray-tracing simulations, stochastic channel modeling and realization, verification with ray-tracing simulations, and validation with a reduced set of measurements. A profound and insightful conclusion is reached that by employing the proposed paradigm, realistic channels can be realized for the design and evaluation of 5G mmWave communication systems in high-speed railways, even without the support of sufficient channel sounding data.
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| 9. |
- Keskin, Furkan, 1988, et al.
(author)
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Altruistic Control of Connected Automated Vehicles in Mixed-Autonomy Multi-Lane Highway Traffic
- 2020
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In: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 53:2, s. 14966-14971
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Conference paper (peer-reviewed)abstract
- We consider the problem of altruistic control of connected automated vehicles (CAVs) on mixed-autonomy multi-lane highways to mitigate moving traffic jams resulting from car-following dynamics of human-driven vehicles (HDVs). In most of the existing studies on CAVs in multi-lane settings, vehicle controller design philosophy is based on a selfish driving strategy that exclusively addresses the ego vehicle objectives. To improve overall traffic smoothness, we propose an altruistic control strategy for CAVs that aims to maximize the driving comfort and traffic efficiency of both the ego vehicle and surrounding HDVs. We formulate the problem of altruistic control under a model predictive control (MPC) framework to optimize acceleration and lane change sequences of CAVs. In order to efficiently solve the resulting non-convex mixed-integer nonlinear programming (MINLP) problem, we decompose it into three non-convex subproblems, each of which can be transformed into a convex quadratic program via penalty based reformulation of the optimal velocity with relative velocity (OVRV) car-following model. Simulation results demonstrate significant improvements in traffic flow via altruistic CAV actions over selfish strategies on both single- and multi-lane roads.
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| 10. |
- Keskin, Furkan, 1988, et al.
(author)
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Freeway Traffic Jam Mitigation via Connected Automated Vehicles
- 2019
-
Conference paper (other academic/artistic)abstract
- We consider the problem of altruistic control of connected automated vehicles (CAVs) on multi-lane highways to mitigate phantom traffic jams resulting from car-following dynamics of human-driven vehicles (HDVs). In most of the existing studies on CAVs in multi-lane settings, vehicle controller design philosophy is based on a selfish driving strategy that exclusively addresses the ego vehicle objectives. To improve overall traffic smoothness, we propose an altruistic control strategy for CAVs that aims to maximize the driving comfort and traffic efficiency of both the ego vehicle and surrounding HDVs. We formulate the problem of altruistic control under a model predictive control (MPC) framework to optimize acceleration and lane change sequences of CAVs. Simulation results demonstrate significant improvements in traffic flow via altruistic CAV actions over selfish strategies.
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| 11. |
- Larsson, Jacob, et al.
(author)
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Pro-social control of connected automated vehicles in mixed-autonomy multi-lane highway traffic
- 2021
-
In: Communications in Transportation Research. - : Elsevier BV. - 2772-4247. ; 1:December
-
Journal article (peer-reviewed)abstract
- We propose pro-social control strategies for connected automated vehicles (CAVs) to mitigate jamming waves in mixed-autonomy multi-lane traffic, resulting from car-following dynamics of human-driven vehicles (HDVs). Different from existing studies, which focus mostly on ego vehicle objectives to control CAVs in an individualistic manner, we devise a pro-social control algorithm. The latter takes into account the objectives (i.e., driving comfort and traffic ef ficiency) of both the ego vehicle and surrounding HDVs to improve smoothness of the entire observable traffic. Under a model predictive control (MPC) framework that uses acceleration and lane change sequences of CAVs as optimization variables, the problem of individualistic, altruistic, and pro-social control is formulated as a non-convex mixed-integer nonlinear program (MINLP) and relaxed to a convex quadratic program through converting the piece-wise-linear constraints due to the optimal velocity with relative velocity (OVRV) car-following model into linear constraints by introducing slack variables. Low-fidelity simulations using the OVRV model and high-fidelity simulations using PTV VISSIM simulator show that pro-social and altruistic control can provide significant performance gains over individualistic driving in terms of efficiency and comfort on both single- and multi-lane roads.
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| 12. |
- Peng, Bile, 1985, et al.
(author)
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Communication Scheduling by Deep Reinforcement Learning for Remote Traffic State Estimation with Bayesian Inference
- 2022
-
In: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 71:4, s. 4287-4300
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Journal article (peer-reviewed)abstract
- Traffic awareness is the prerequisite of autonomous driving. Given the limitation of on-board sensors (e.g., precision and price), remote measurement from either infrastructure or other vehicles can improve traffic safety. However, the wireless communication carrying the measurement result undergoes fading, noise and interference and has a certain probability of outage. When the communication fails, the vehicle state can only be predicted by Bayesian filtering with a low precision. Higher communication resource utilization (e.g., transmission power) reduces the outage probability and hence results in an improved estimation precision. The power control subject to an estimate variance constraint is a difficult problem due to the complicated mapping from transmit power to vehicle-state estimate variance. In this paper, we develop an estimator consisting of several Kalman filters (KFs) or extended Kalman filters (EKFs) and an interacting multiple model (IMM) to estimate and predict the vehicle state. We propose to apply deep reinforcement learning (DRL) for the transmit power optimization. In particular, we consider an intersection and a lane-changing scenario and apply proximal policy optimization (PPO) and soft actor-critic (SAC) to train the DRL model. Testing results show satisfactory power control strategies confining estimate variances below given threshold. SAC achieves higher performance compared to PPO.
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| 13. |
- Peng, Bile, 1985, et al.
(author)
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Connected autonomous vehicles for improving mixed traffic efficiency in unsignalized intersections with deep reinforcement learning
- 2021
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In: Communications in Transportation Research. - : Elsevier BV. - 2772-4247.
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Journal article (peer-reviewed)abstract
- Human driven vehicles (HDVs) with selfish objectives cause low traffic efficiency in an un-signalized intersection. On the other hand, autonomous vehicles can overcome this inefficiency through perfect coordination. In this paper, we propose an intermediate solution, where we use vehicular communication and a small number of autonomous vehicles to improve the transportation system efficiency in such intersections. In our solution, two connected autonomous vehicles (CAVs) lead multiple HDVs in a double-lane intersection in order to avoid congestion in front of the intersection. The CAVs are able to communicate and coordinate their behavior, which is controlled by a deep reinforcement learning (DRL) agent. We design an altruistic reward function which enables CAVs to adjust their velocities flexibly in order to avoid queuing in front of the intersection. The proximal policy optimization (PPO) algorithm is applied to train the policy and the generalized advantage estimation (GAE) is used to estimate state values. Training results show that two CAVs are able to achieve significantly better traffic efficiency compared to similar scenarios without and with one altruistic autonomous vehicle.
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| 14. |
- Peng, Bile, 1985, et al.
(author)
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Cooperative dynamic angle of arrival estimation considering space-time correlations for terahertz communications
- 2018
-
In: IEEE Transactions on Wireless Communications. - 1558-2248 .- 1536-1276. ; 17:9, s. 6029-6041
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Journal article (peer-reviewed)abstract
- © 2002-2012 IEEE. Angle of arrival (AoA) estimation is required by adaptive directive antennas in order to realize a high antenna gain, which is necessary for future indoor terahertz communications due to its extremely high path loss. This paper proposes an AoA estimation algorithm using belief propagation in a dynamic scenario, where the user equipment (UE) is moving during the data transmission, based on the space-time correlations of AoA change. The temporal correlation of AoA change is due to the limited moving speed and statistical movement pattern. Furthermore, if we have distributed antennas or hybrid massive multiple-input-multiple-output (MIMO) array, the AoA changes of different antennas reveal spatial correlation because all the AoA changes are caused by the same spatial displacement of UE. This spatial correlation is utilized in this paper to further improve the estimation accuracy by passing messages between antennas and combining the intrinsic estimate by each antenna and extrinsic information from other antennas. In order to demonstrate the algorithm performance, a distributed antenna system and a hybrid massive MIMO array (an array of multiple directive antenna arrays) are considered as application scenarios. The simulation results show that the cooperative estimation brings significant advantage in both scenarios in respect of mean effective antenna gain and level crossing rate.
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| 15. |
- Peng, Bile, 1985, et al.
(author)
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Decentralized Scheduling for Cooperative Localization With Deep Reinforcement Learning
- 2019
-
In: IEEE Transactions on Vehicular Technology. - : Institute of Electrical and Electronics Engineers Inc.. - 0018-9545 .- 1939-9359. ; 68:5, s. 4295-4305
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Journal article (peer-reviewed)abstract
- Cooperative localization is a promising solution to the vehicular high-accuracy localization problem. Despite its high potential, exhaustive measurement and information exchange between all adjacent vehicles are expensive and impractical for applications with limited resources. Greedy policies or hand-engineering heuristics may not be able to meet the requirement of complicated use cases. In this paper, we formulate a scheduling problem to improve the localization accuracy (measured through the Cramér-Rao lower bound) of every vehicle up to a given threshold using the minimum number of measurements. The problem is cast as a partially observable Markov decision process and solved using decentralized scheduling algorithms with deep reinforcement learning, which allow vehicles to optimize the scheduling (i.e., the instants to execute measurement and information exchange with each adjacent vehicle) in a distributed manner without a central controlling unit. Simulation results show that the proposed algorithms have a significant advantage over random and greedy policies in terms of both required numbers of measurements to localize all nodes and achievable localization precision with limited numbers of measurements.
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| 16. |
- Peng, Bile, 1985, et al.
(author)
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Power-Angular Spectra Correlation Based Two Step Angle of Arrival Estimation for Future Indoor Terahertz Communications
- 2019
-
In: IEEE Transactions on Antennas and Propagation. - 0018-926X .- 1558-2221. ; 67:11
-
Journal article (peer-reviewed)abstract
- The future terahertz (THz) communication is a promising solution to the high-data-rate and short-range communication due to its broad available bandwidth. However, the high propagation path loss and the limited output power of the amplifier require highly directive antennas with high antenna gain in order to realize a reasonable signal-to-noise ratio (SNR). An angle of arrival (AoA) estimation is necessary to adjust the main lobe direction of the antenna. A major challenge of the AoA estimation is the compromise between accuracy and time consumption due to the big number of main lobe directions. This paper proposes a novel efficient AoA algorithm, which utilizes the fact that the power angular spectra (PAS) of different frequencies are highly correlated and the THz communication devices are equipped with radio frequency (RF) frontends of lower frequency. By means of a rough and quick estimation at the lower frequency, the range of the true AoA can be confined significantly and the precise estimation can be carried out efficiently. To begin with, an antenna model with discrete main lobe directions is proposed and the relationship between antenna gain, half power beam width (HPBW) and number of main lobe directions is analyzed. The PAS correlation is then validated with channel sounding measurement. The two-step AoA estimation algorithm is derived, formulated and finally validated with hardware demonstration.
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| 17. |
- Peng, Bile, 1985, et al.
(author)
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Precoding and Detection for Broadband Single Carrier Terahertz Massive MIMO Systems Using LSQR Algorithm
- 2019
-
In: IEEE Transactions on Wireless Communications. - 1558-2248 .- 1536-1276. ; 18:8599164, s. 1026-1040
-
Journal article (peer-reviewed)abstract
- The terahertz (THz) communication utilizes the frequency spectrum above 300 GHz and is widely considered as a promising solution to the future high-speed short-range wireless communication beyond millimeter wave (mmWave) communication. While providing tens of gigahertz bandwidth, it is subjected to high propagation path loss, inter-symbol and inter-user interferences. The massive multiple-input- multiple-output (MIMO) can be applied to address these problems by cooperation between many access point (AP) antennas. However, the THz channel characteristics, including high propagation path loss, frequency selectivity and big number of samples per channel impulse response (CIR), require carefully tailored algorithm for massive MIMO signal processing. In this paper, we propose a single carrier minimum mean square error (MMSE) precoding and detection algorithm for frequency selective THz channels. The MIMO signal transmission is described with the block matrices. A gain control heuristic is introduced to reduce the complexity. The sparsity property of the channel is utilized to construct sparse channel matrices and the least square QR (LSQR) algorithm is applied to efficiently solve the problems. Besides the uniform antenna array, the hybrid array consisting of several subarrays is considered as well. Simulation results show that the massive MIMO array can provide a satisfactory performance in terms of bit error rate (BER).
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| 18. |
- Peng, Bile, 1985, et al.
(author)
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Statistical Characteristics Study of Human Blockage Effect in Future Indoor Millimeter and Sub-millimeter Wave Wireless Communications
- 2018
-
In: IEEE Vehicular Technology Conference. - 1550-2252.
-
Conference paper (peer-reviewed)abstract
- The millimeter and sub-millimeter wave communication is a promising solution to future indoor multi-gigabit wireless communications because of its huge available bandwidth. One of the key difficulties is the human blockage effect since the human body can no longer be considered as being "transparent" as at lower frequencies. In this paper a study of statistical characteristics of this problem is presented. At first, broadband measurements of human blockage are provided. Afterwards, a realis- tic mobility model for indoor movements of humans is adopted and elliptic cylinders are applied to approximate human bodies in ray-launching simulations. Consequently, the distributions of Line-Of-Sight (LOS) path and blockage durations as well as blockage numbers are obtained by simulations. Finally, the system performance in presence of the distributed antennas is evaluated.
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| 19. |
- Song, Jinxiang, 1995, et al.
(author)
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Learning Physical-Layer Communication with Quantized Feedback
- 2020
-
In: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; 68:1, s. 645-653
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Journal article (peer-reviewed)abstract
- Data-driven optimization of transmitters and receivers can reveal new modulation and detection schemes and enable physical-layer communication over unknown channels. Previous work has shown that practical implementations of this approach require a feedback signal from the receiver to the transmitter. In this paper, we study the impact of quantized feedback on data-driven learning of physical-layer communication. A novel quantization method is proposed, which exploits the specific properties of the feedback signal and is suitable for nonstationary signal distributions. The method is evaluated for linear and nonlinear channels. Simulation results show that feedback quantization does not appreciably affect the learning process and can lead to similar performance as compared to the case where unquantized feedback is used for training, even with 1-bit quantization. In addition, it is shown that learning is surprisingly robust to noisy feedback where random bit flips are applied to the quantization bits.
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| 20. |
- Wu, Yibo, 1996, et al.
(author)
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Cooperative localization with angular measurements and posterior linearization
- 2020
-
In: 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings.
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Conference paper (peer-reviewed)abstract
- The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage of the positioning. Conventional distance measurements between vehicles are limited by the need for synchronization and provide no heading information of the vehicle. To address this, we present a cooperative localization algorithm using posterior linearization belief propagation (PLBP) utilizing angle-of-arrival (AoA)-only measurements. Simulation results show that both directional and positional root mean squared error (RMSE) of vehicles can be decreased significantly and converge to a low value in a few iterations. Furthermore, the influence of parameters for the vehicular network, such as vehicle density, communication radius, prior uncertainty, and AoA measurements noise, is analyzed.
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| 21. |
- Xie, Wenjing, et al.
(author)
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An Improved Algorithm Based on Particle Filter for 3D UAV Target Tracking
- 2019
-
In: IEEE International Conference on Communications. - 1550-3607. ; 2019-May
-
Conference paper (peer-reviewed)abstract
- The widespread application of unmanned aerial vehicles (UAVs) urgently requires an effective tracking algorithm as technical support. Particle filter has been widely applied in maneuvering target tracking, however, there has been no suitable solution to the trade-off between weight degeneracy and particle diversity during the process of resampling. In this paper, we propose an improved particle filter algorithm based on systematic resampling with additional random perturbation. This method ensures that particle filter maintains particle diversity and reduces weight degeneracy under environments with different noise types, simultaneously. The simulation results demonstrate that the proposed algorithm generates more accurate filtered trajectory than generic particle filter, especially under the environment with low noise.
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