Dynamic Propagation Channel Research Articles

Virtual Drive Testing of Adaptive Antenna Systems in Dynamic Propagation Scenarios for Vehicle Communications

Virtual drive testing (VDT) has gained great interest from both industry and academia, owing to its promise to replay field trials in a controllable laboratory condition. VDT is especially appealing for vehicle communication scenarios, where actual field trials can be difficult to carry out in practice. Research work on VDT of adaptive antenna systems in dynamic propagation scenarios has been limited, mainly due to high VDT setup cost and lack of efficient dynamic propagation channel models. In this paper, we propose to jointly emulate adaptive antennas (i.e. beamformers) and radio channels in the radio channel emulator to reduce the VDT setup cost. A simple dynamic propagation channel framework, which is based on linear interpolation of propagation parameters of the stationary channel models, is also presented. We further experimentally evaluate the beamformer capability (i.e. beam tracking and null steering) in dynamic line-of-sight (LOS) and non-LOS scenarios in the proposed cost-effective conducted VDT setups. The simulation and measurement results have demonstrated the effectiveness of the beam tracking and nulling steering algorithms in dynamic propagation conditions in the presence of interfering signal. The proposed setup and dynamic channel modeling framework are valuable for the VDT of adaptive antenna systems.

Dynamic propagation characteristics estimation and tracking based on an EM-EKF algorithm in time-variant MIMO channel

In cognitive radio (CR), it is important to understand the multi-dimension and multi-scale characteristics of the dynamic multiple-input multiple-output (MIMO) channels obtained from observations. In this paper, to estimate and track propagation path parameters in time-variant MIMO channels, we propose an expectation maximization-extended Kalman filter (EM-EKF) in the frequency domain. The proposed algorithm can capture the dynamic channel with a high accuracy and a low time consumption. We use the EKF in the frequency domain to detect existed paths and to continue to track how the paths evolve over time. Then, we formulate a frequency-domain EM method to estimate the new paths in the dynamic propagation channel. Simulation results demonstrate that the proposed approach has an improved performance in terms of parametric estimation and a lower time consumption compared with the comparative space-alternating generalized expectation-maximization algorithm (SAGE).

Dynamic Propagation Channel Characterization and Modeling for Human Body Communication

This paper presents the first characterization and modeling of dynamic propagation channels for human body communication (HBC). In-situ experiments were performed using customized transceivers in an anechoic chamber. Three HBC propagation channels, i.e., from right leg to left leg, from right hand to left hand and from right hand to left leg, were investigated under thirty-three motion scenarios. Snapshots of data (2,800,000) were acquired from five volunteers. Various path gains caused by different locations and movements were quantified and the statistical distributions were estimated. In general, for a given reference threshold è = −10 dB, the maximum average level crossing rate of the HBC was approximately 1.99 Hz, the maximum average fade time was 59.4 ms, and the percentage of bad channel duration time was less than 4.16%. The HBC exhibited a fade depth of −4 dB at 90% complementary cumulative probability. The statistical parameters were observed to be centered for each propagation channel. Subsequently a Fritchman model was implemented to estimate the burst characteristics of the on-body fading. It was concluded that the HBC is motion-insensitive, which is sufficient for reliable communication link during motions, and therefore it has great potential for body sensor/area networks.