18,504 research outputs found
Robust Transceiver Design Based on Interference Alignment for Multi-User Multi-Cell MIMO Networks with Channel Uncertainty
In this paper, we firstly exploit the inter-user interference (IUI) and
inter-cell interference (ICI) as useful references to develop a robust
transceiver design based on interference alignment for a downlink multi-user
multi-cell multiple-input multiple-output (MIMO) interference network under
channel estimation error. At transmitters, we propose a two-tier transmit
beamforming strategy, we first achieve the inner beamforming direction and
allocated power by minimizing the interference leakage as well as maximizing
the system energy efficiency, respectively. Then, for the outer beamformer
design, we develop an efficient conjugate gradient Grassmann manifold subspace
tracking algorithm to minimize the distances between the subspace spanned by
interference and the interference subspace in the time varying channel. At
receivers, we propose a practical interference alignment based on fast and
robust fast data projection method (FDPM) subspace tracking algorithm, to
achieve the receive beamformer under channel uncertainty. Numerical results
show that our proposed robust transceiver design achieves better performance
compared with some existing methods in terms of the sum rate and the energy
efficiency.Comment: 12 pages, 8 figure
Underdetermined-order recursive least-squares adaptive filtering: The concept and algorithms
Published versio
Robust Reduced-Rank Adaptive Processing Based on Parallel Subgradient Projection and Krylov Subspace Techniques
In this paper, we propose a novel reduced-rank adaptive filtering algorithm
by blending the idea of the Krylov subspace methods with the set-theoretic
adaptive filtering framework. Unlike the existing Krylov-subspace-based
reduced-rank methods, the proposed algorithm tracks the optimal point in the
sense of minimizing the \sinq{true} mean square error (MSE) in the Krylov
subspace, even when the estimated statistics become erroneous (e.g., due to
sudden changes of environments). Therefore, compared with those existing
methods, the proposed algorithm is more suited to adaptive filtering
applications. The algorithm is analyzed based on a modified version of the
adaptive projected subgradient method (APSM). Numerical examples demonstrate
that the proposed algorithm enjoys better tracking performance than the
existing methods for the interference suppression problem in code-division
multiple-access (CDMA) systems as well as for simple system identification
problems.Comment: 10 figures. In IEEE Transactions on Signal Processing, 201
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