212,224 research outputs found
Achieving Low-Complexity Maximum-Likelihood Detection for the 3D MIMO Code
The 3D MIMO code is a robust and efficient space-time block code (STBC) for
the distributed MIMO broadcasting but suffers from high maximum-likelihood (ML)
decoding complexity. In this paper, we first analyze some properties of the 3D
MIMO code to show that the 3D MIMO code is fast-decodable. It is proved that
the ML decoding performance can be achieved with a complexity of O(M^{4.5})
instead of O(M^8) in quasi static channel with M-ary square QAM modulations.
Consequently, we propose a simplified ML decoder exploiting the unique
properties of 3D MIMO code. Simulation results show that the proposed
simplified ML decoder can achieve much lower processing time latency compared
to the classical sphere decoder with Schnorr-Euchner enumeration
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
Cross-coupled doa trackers
A new robust, low complexity algorithm for multiuser tracking is proposed, modifying the two-stage parallel architecture of the estimate-maximize (EM) algorithm. The algorithm copes with spatially colored noise, large differences in source powers, multipath, and crossing trajectories. Following a discussion on stability, the simulations demonstrate an asymptotic and tracking behavior that neither the EM nor a nonparallelized tracker can emulate.Peer ReviewedPostprint (published version
- …