Abstract

Distributed MIMO communications involve multiple transmitters and receivers organizing themselves into virtual antenna arrays. As these carry individual clocks and oscillators that drift, maintaining sychronization requires that the frequency and the unwrapped phase of each oscillator be tracked using Kalman filters. Kalman filters in turn are sensitive to how well the process and measurement noise variances are known. Existing methods for estimating unknown system variances do not work well for oscillators as the process noise variances are very small (orders of 10−21). In this paper we modify the most advanced technique for estimating the noise variances to develop a scheme that leads to faster and more accurate estimation of the noise variances, using fewer observations.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.