DocumentCode
81490
Title
Channel State Tracking for Large-Scale Distributed MIMO Communication Systems
Author
Brown, D. Richard ; Rui Wang ; Dasgupta, Soura
Author_Institution
Dept. of Electr. & Comput. Eng., Worcester Polytech. Inst., Worcester, MA, USA
Volume
63
Issue
10
fYear
2015
fDate
15-May-15
Firstpage
2559
Lastpage
2571
Abstract
This paper considers the problem of estimating and tracking channels in a distributed transmission system with Nt transmit nodes and Nr receive nodes. Since each node in the distributed transmission system has an independent local oscillator, the effective channel between each transmit node and each receive node has time-varying phase and frequency offsets which must be tracked and predicted to facilitate coherent transmission. A linear time-invariant state-space model is developed and is shown to be observable but nonstabilizable. To quantify the steady-state performance of a Kalman filter channel tracker, two methods are developed to efficiently compute the steady-state prediction covariance. The first method requires the solution of a 2(Nt + Nr-1)-dimensional discrete-time algebraic Riccati equation, but allows for nonhomogenous oscillator parameters. The second method requires the solution of four two-dimensional discrete-time algebraic Riccati equations but requires homogenous oscillator parameters for all nodes in the system. An asymptotic analysis is also presented for the homogenous oscillator case for systems with a large number of transmit and receive nodes with closed-form results for all of the elements in the asymptotic prediction covariance as a function of the carrier frequency, oscillator parameters, and channel measurement period. Numeric results confirm the analysis and demonstrate the effect of the oscillator parameters on the ability of the distributed transmission system to achieve coherent transmission.
Keywords
Kalman filters; MIMO communication; Riccati equations; covariance analysis; state-space methods; Kalman filter; asymptotic prediction covariance; carrier frequency; channel measurement period; channel state tracking; coherent transmission; distributed transmission system; frequency offsets; homogenous oscillator parameters; independent local oscillator; large-scale distributed MIMO communication systems; linear time-invariant state-space model; nonhomogenous oscillator parameters; receive nodes; steady-state prediction covariance; time-varying phase offsets; transmit nodes; two-dimensional discrete-time algebraic Riccati equations; Kalman filters; MIMO; Oscillators; Riccati equations; Steady-state; Synchronization; Asymptotic analysis; channel prediction; coherent transmission; discrete-time algebraic Riccati equation; distributed communication systems; oscillator dynamics;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2015.2407316
Filename
7050323
Link To Document