839 research outputs found
Adaptive Differential Feedback in Time-Varying Multiuser MIMO Channels
In the context of a time-varying multiuser multiple-input-multiple-output
(MIMO) system, we design recursive least squares based adaptive predictors and
differential quantizers to minimize the sum mean squared error of the overall
system. Using the fact that the scalar entries of the left singular matrix of a
Gaussian MIMO channel becomes almost Gaussian distributed even for a small
number of transmit antennas, we perform adaptive differential quantization of
the relevant singular matrix entries. Compared to the algorithms in the
existing differential feedback literature, our proposed quantizer provides
three advantages: first, the controller parameters are flexible enough to adapt
themselves to different vehicle speeds; second, the model is backward adaptive
i.e., the base station and receiver can agree upon the predictor and variance
estimator coefficients without explicit exchange of the parameters; third, it
can accurately model the system even when the correlation between two
successive channel samples becomes as low as 0.05. Our simulation results show
that our proposed method can reduce the required feedback by several kilobits
per second for vehicle speeds up to 20 km/h (channel tracker) and 10 km/h
(singular vector tracker). The proposed system also outperforms a fixed
quantizer, with same feedback overhead, in terms of bit error rate up to 30
km/h.Comment: IEEE 22nd International Conference on Personal, Indoor and Mobile
Radio Communications (2011
Subspace Tracking and Least Squares Approaches to Channel Estimation in Millimeter Wave Multiuser MIMO
The problem of MIMO channel estimation at millimeter wave frequencies, both
in a single-user and in a multi-user setting, is tackled in this paper. Using a
subspace approach, we develop a protocol enabling the estimation of the right
(resp. left) singular vectors at the transmitter (resp. receiver) side; then,
we adapt the projection approximation subspace tracking with deflation and the
orthogonal Oja algorithms to our framework and obtain two channel estimation
algorithms. We also present an alternative algorithm based on the least squares
approach. The hybrid analog/digital nature of the beamformer is also explicitly
taken into account at the algorithm design stage. In order to limit the system
complexity, a fixed analog beamformer is used at both sides of the
communication links. The obtained numerical results, showing the accuracy in
the estimation of the channel matrix dominant singular vectors, the system
achievable spectral efficiency, and the system bit-error-rate, prove that the
proposed algorithms are effective, and that they compare favorably, in terms of
the performance-complexity trade-off, with respect to several competing
alternatives.Comment: To appear on the IEEE Transactions on Communication
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