Wireless infrared communication systems are attracting interest for high-data-rate, wireless, in-building local area networks. We investigate the use of mobility tracking and prediction for mobile users in such systems. One promising approach to achieving high data rates in such systems is to use narrowband optical systems to improve the signal-to-noise ratio. However, the angle dependency of such systems requires either tunable systems or adaptive arrays. The latency in such adaptation, if unmitigated, may cause the bit-error rate for mobile users to exceed acceptable levels, which in turn increases delay and reduces throughput. Mobility tracking and prediction can help by anticipating the required change in the adaptation parameter such as peak transmission wavelength or the angle of receiver axis. In this paper, we developed a set of terminal mobility model and movement observation model that closely represent indoor movement behavior and channel fading characteristics. Based on the established model, an extended Kalman filtering algorithm is developed which achieves efficient location tracking, shadow fading estimation and prediction of the peak-transmission wavelength of infrared radiation. Simulation results demonstrate the feasibility and efficiency of this algorithm in line of sight configurations and prove that with efficient trajectory tracking, location and fade transparent communication channels can be built to support high data rate transmission and improve overall QoS for wireless infrared LANs.
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