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Papers by Paul Tune

IEEE Transactions on Signal Processing, Oct 2012

We revisit the problem of computing submatrices of the Cramér-Rao bound (CRB), which lower bound... more We revisit the problem of computing submatrices of the Cramér-Rao bound (CRB), which lower bounds the variance of any unbiased estimator of a vector parameter mbi θ. We explore iterative methods that avoid direct inversion of the Fisher information matrix, which can be computationally expensive when the dimension of mbi θ is large. The computation of the bound is related to the quadratic matrix program, where there are highly efficient methods for solving it. We present several methods, and show that algorithms in prior work are special instances of existing optimization algorithms. Some of these methods converge to the bound monotonically, but in particular, algorithms converging nonmonotonically are much faster. We then extend the work to encompass the computation of the CRB when the Fisher information matrix is singular and when the parameter mbi θ is subject to constraints. As an application, we consider the design of a data streaming algorithm for network measurement.

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Abstract In this paper, we propose a method for user selection and channel estimation using compr... more Abstract In this paper, we propose a method for user selection and channel estimation using compressed sensing. In particular, we consider a multiple-input multiple-output (MIMO) downlink broadcast scenario. We establish that full channel state information (and not just channel quality) for each self-selecting user can be obtained at the basestation via compressed sensing with no increase in overhead for the uplink feedback channel. We demonstrate the new method as a medium access technique for MIMO downlink ...

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Digital Signal Processing, 2011

In this paper, we propose a method for user selection and channel estimation for the multiple-inp... more In this paper, we propose a method for user selection and channel estimation for the multiple-input multiple-output (MIMO) broadcast channel for the downlink of a cellular mobile or local-area wireless communication system.A distributed self-selection procedure is combined with a code-division multiple access (CDMA) uplink signaling strategy to reduce the uplink signaling bandwidth, and the computational complexity of user selection at the base station. We exploit recent advances in sparse signal recovery, which we apply to the uplink multi-user detection and channel estimation problems to reduce the signaling bandwidth. We establish that full channel state information (and not just channel quality) for each self-selecting user can be obtained at the base station via a compressed-sensing technique with no increase in overhead for the uplink feedback channel. We demonstrate the new method as a medium access technique for MIMO downlink broadcast with transmitter precoding and linear receiver processing.

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