Bile Peng

On Millimeter Wave and THz Mobile Radio Channel for Smart Rail Mobility

As a widely acknowledged efficient and green transportation model, rail traffic is expected to evolve into a new era of “smart rail mobility” whereby infrastructure, trains, and travelers will be interconnected to achieve optimized mobility, higher safety, and lower costs. Thus, a seamless high-data rate wireless connectivity with up to dozens of gigahertz bandwidth is required. Such a huge bandwidth requirement motivates the exploration of the underutilized millimeter (mm) wave and terahertz (THz) bands. In this paper, the motivations for developing millimeter wave and THz communications for railway are clarified by first defining the applications and scenarios required for smart rail mobility. Ray-tracing simulations at 100 GHz imply that to form high-gain directional antenna beams, dynamic beamforming strategies and advanced handover design are critical for the feasibility of THz communications to enable smart rail mobility.

Three-Dimensional Angle of Arrival Estimation in Dynamic Indoor Terahertz Channels Using a Forward–Backward Algorithm

A novel angle-of-arrival (AoA) estimation method for both azimuth and elevation based on Bayesian inference and statistical state transition probabilities is presented for the dynamic indoor terahertz (THz) channel. A precise AoA estimation is crucial for the deployment of a directive antenna, which can compensate for the high path loss and reduce the intersymbol interference. In many application scenarios, the user equipment is moved by the user during the data transmission, and the AoA is not constant. The novel algorithm exploits the fact that the AoA movement can be represented as a Markov process and that the Bayesian inference can be used to combine the likelihood and a priori information to provide a more precise estimate than using the likelihood alone. An indoor human movement model is developed to generate the realistic application scenario and obtain the statistical transition probabilities. The forward–backward algorithm is implemented to carry out the Bayesian inference. The algorithm performance is illustrated using the channel models generated by a ray launching simulator. The background log-likelihood is suggested to adapt the algorithm to the instant channel state change in a multipath environment.

Effects of phase shift errors on the antenna directivity of phased arrays in indoor terahertz communications

Phased arrays provide a high antenna gain and improve the signal quality in the presence of high propagation path loss. However, an imprecise phase shift could reduce the antenna performance. This problem is especially serious when the carrier frequency is very high because the short wave length results in a high sensitivity against phase impairments. Any phase shift error effectively affects the radiation pattern and thereby reduces the antenna directivity. This paper derives the expectation of the antenna directivity in the presence of random phase shift errors. The theoretical estimate is validated with the simulation result and offers a simple way to determine the precision requirement of the phase shifter for a given necessary directivity.

Angle of arrival estimation in dynamic indoor THz channels with Bayesian filter and reinforcement learning

This paper presents a novel algorithm to estimate the Angle of Arrival (AoA) in a dynamic indoor Terahertz channel. In a realistic application, the user equipment is often moved by the user during the data transmission and the AoA must be estimated periodically, such that the adaptive directional antenna can be adjusted to realize a high antenna gain. The Bayesian filter is applied to exploit continuity and smoothness of the channel dynamics for the AoA estimation. Reinforcement learning is introduced to adapt the prior transition probabilities between system states, in order to fit the variation of application scenarios and personal habits. The algorithm is validated using the ray launching channel simulator and realistic human movement models.

A stochastic channel model for future wireless THz data centers

A wireless link in the data center has many advantages over the traditional wired connection. Because of the high available bandwidth, the THz communication holds a good prospect for the future wireless data center. In this paper, a stochastic THz channel model in the data center is developed based on the ray tracing simulation, which generates the temporal and spatial channel characteristics, providing the basis for the standardization and system design. The channel model is validated by comparing RMS delay/angular spreads of ray tracing simulations and stochastic channel model.

Feasibility studies of LTE for the broadband service delivery in Professional Mobile Radio

Professional Mobile Radio (PMR) requires higher reliability with less dense infrastructure than usual public mobile networks. Potential implementation of the next generation public mobile radio system Long Term Evolution (LTE) in PMR can bring new features, e.g., real time video. However, its feasibility must be carefully investigated with realistic PMR applications. This paper presents such an investigation based on a ray tracing wave propagation model applied in the inner city of Hannover. Two typical PMR application scenarios - a patrol scenario in daily use and an emergent rescue - were defined and simulated. Different network setups and simulation parameters were compared to derive the optimal setting for the performance of the PMR system.