128 research outputs found
Filter-And-Forward Distributed Beamforming in Relay Networks with Frequency Selective Fading
A new approach to distributed cooperative beamforming in relay networks with
frequency selective fading is proposed. It is assumed that all the relay nodes
are equipped with finite impulse response (FIR) filters and use a
filter-and-forward (FF) strategy to compensate for the transmitter-to-relay and
relay-to-destination channels.
Three relevant half-duplex distributed beamforming problems are considered.
The first problem amounts to minimizing the total relay transmitted power
subject to the destination quality-of-service (QoS) constraint. In the second
and third problems, the destination QoS is maximized subject to the total and
individual relay transmitted power constraints, respectively. For the first and
second problems, closed-form solutions are obtained, whereas the third problem
is solved using convex optimization. The latter convex optimization technique
can be also directly extended to the case when the individual and total power
constraints should be jointly taken into account. Simulation results
demonstrate that in the frequency selective fading case, the proposed FF
approach provides substantial performance improvements as compared to the
commonly used amplify-and-forward (AF) relay beamforming strategy.Comment: Submitted to IEEE Trans. on Signal Processing on 8 July 200
Downlink Channel Estimation in Cellular Systems with Antenna Arrays at Base Stations Using Channel Probing with Feedback
Moving Target Parameters Estimation in Non-Coherent MIMO Radar Systems
The problem of estimating the parameters of a moving target in multiple-input
multiple-output (MIMO) radar is considered and a new approach for estimating
the moving target parameters by making use of the phase information associated
with each transmit-receive path is introduced. It is required for this
technique that different receive antennas have the same time reference, but no
synchronization of initial phases of the receive antennas is needed and,
therefore, the estimation process is non-coherent. We model the target motion
within a certain processing interval as a polynomial of general order. The
first three coefficients of such a polynomial correspond to the initial
location, velocity, and acceleration of the target, respectively. A new maximum
likelihood (ML) technique for estimating the target motion coefficients is
developed. It is shown that the considered ML problem can be interpreted as the
classic "overdetermined" nonlinear least-squares problem. The proposed ML
estimator requires multi-dimensional search over the unknown polynomial
coefficients. The Cram\'er-Rao Bound (CRB) for the proposed parameter
estimation problem is derived. The performance of the proposed estimator is
validated by simulation results and is shown to achieve the CRB.Comment: 17 pages, 4 figures, Submitted to the IEEE Trans. Signal Processing
in Aug. 201
Cooperative Transmission for Wireless Relay Networks Using Limited Feedback
To achieve the available performance gains in half-duplex wireless relay
networks, several cooperative schemes have been earlier proposed using either
distributed space-time coding or distributed beamforming for the transmitter
without and with channel state information (CSI), respectively. However, these
schemes typically have rather high implementation and/or decoding complexities,
especially when the number of relays is high. In this paper, we propose a
simple low-rate feedback-based approach to achieve maximum diversity with a low
decoding and implementation complexity. To further improve the performance of
the proposed scheme, the knowledge of the second-order channel statistics is
exploited to design long-term power loading through maximizing the receiver
signal-to-noise ratio (SNR) with appropriate constraints. This maximization
problem is approximated by a convex feasibility problem whose solution is shown
to be close to the optimal one in terms of the error probability. Subsequently,
to provide robustness against feedback errors and further decrease the feedback
rate, an extended version of the distributed Alamouti code is proposed. It is
also shown that our scheme can be generalized to the differential transmission
case, where it can be applied to wireless relay networks with no CSI available
at the receiver.Comment: V1: 27 pages, 1 column, 6 figures. Submitted to IEEE Transactions on
Signal Processing, February 2, 2009. V2: 30 pages, 1 column, 8 figures.
Revised version submitted to IEEE Transactions on Signal Processing, July 23,
200
Statistical Eigenmode Transmission over Jointly-Correlated MIMO Channels
We investigate MIMO eigenmode transmission using statistical channel state
information at the transmitter. We consider a general jointly-correlated MIMO
channel model, which does not require separable spatial correlations at the
transmitter and receiver. For this model, we first derive a closed-form tight
upper bound for the ergodic capacity, which reveals a simple and interesting
relationship in terms of the matrix permanent of the eigenmode channel coupling
matrix and embraces many existing results in the literature as special cases.
Based on this closed-form and tractable upper bound expression, we then employ
convex optimization techniques to develop low-complexity power allocation
solutions involving only the channel statistics. Necessary and sufficient
optimality conditions are derived, from which we develop an iterative
water-filling algorithm with guaranteed convergence. Simulations demonstrate
the tightness of the capacity upper bound and the near-optimal performance of
the proposed low-complexity transmitter optimization approach.Comment: 32 pages, 6 figures, to appear in IEEE Transactions on Information
Theor
Optimization-boosted beamforming: From receive and transmit methods to cooperative relay techniques
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