Tracking of Time-Variant Radio Propagation Paths Using Particle Filtering

Abstract

Abstract-In this contribution a low-complexity particle filtering algorithm is proposed to track the parameters of time-variant propagation paths in multiple-input multiple-output (MIMO) radio channels. A state-space model is used to describe the path evolution in delay, azimuth of arrival, azimuth of departure, Doppler frequency and complex amplitude dimensions. The proposed particle filter (PF) has an additional resampling step specifically designed for wideband MIMO channel sounding, where the posterior probability density functions of the path states is usually highly concentrated in the multi-dimensional state space. Preliminary investigations using measurement data show that the proposed PF can track paths stably with a small number of particles, e.g. 5 per path, even in the case where the paths are undetected by the conventional SAGE algorithm.Index Terms-Radio propagation channel, sequential Bayesian estimation, particle filter, state-space model, and maximumlikelihood estimation.

Hybrid Data Fusion and Cooperative Schemes for Wireless Positioning

“…Two novel hybrid data fusion algorithms [8], [9] have been proposed recently within the framework of WHERE.…”

“…In the first novel approach [8], a particle filter (PF) is used to track the path parameters directly from the received signals. The data fusion that is performed usually as a separate stage in the conventional tracking algorithms, is now implicitly done during the parameter estimation.…”

Detection and Tracking of MIMO Propagation Path Parameters Using State-Space Approach

“…A statespace model is derived and an extended Kalman filter (EKF) is applied for the parameter estimation of the nonlinear data model. Another approach for the tracking of the dynamic space, time, and frequency dependent MIMO radio channel was recently proposed in [5] based on Particle Filter concept. However, in [5] the number of tracked paths is very limited and the number of particles (5) per path is unrealistically low, leading to an increased need for particle resampling.…”

“…Another approach for the tracking of the dynamic space, time, and frequency dependent MIMO radio channel was recently proposed in [5] based on Particle Filter concept. However, in [5] the number of tracked paths is very limited and the number of particles (5) per path is unrealistically low, leading to an increased need for particle resampling. As the dimensionality of the problem grows, these issues can be expected to increase the computational complexity accordingly.…”

“…As the dimensionality of the problem grows, these issues can be expected to increase the computational complexity accordingly. In addition, the diffuse scattering (DMC) was not considered in [5].…”