969 research outputs found
A nonlinear M-estimation approach to robust asynchronous multiuser detection in Non-gaussian noise
A nonlinear M-estimation approach is proposed to solve the multiuser detection problem in asynchronous code-division multiple-access (CDMA) systems where the ambient noise is impulsive and the delays are not known. We treat the unknown delays as nuisance parameters and the transmitted symbols as parameters of interest. We also analyze the asymptotic performance of the proposed estimator and propose suboptimal but computationally efficient procedures for solving the nonlinear optimization function. Simulation results show considerable improvements over the conventional approaches
Estimation of the Number of Sources in Unbalanced Arrays via Information Theoretic Criteria
Estimating the number of sources impinging on an array of sensors is a well
known and well investigated problem. A common approach for solving this problem
is to use an information theoretic criterion, such as Minimum Description
Length (MDL) or the Akaike Information Criterion (AIC). The MDL estimator is
known to be a consistent estimator, robust against deviations from the Gaussian
assumption, and non-robust against deviations from the point source and/or
temporally or spatially white additive noise assumptions. Over the years
several alternative estimation algorithms have been proposed and tested.
Usually, these algorithms are shown, using computer simulations, to have
improved performance over the MDL estimator, and to be robust against
deviations from the assumed spatial model. Nevertheless, these robust
algorithms have high computational complexity, requiring several
multi-dimensional searches.
In this paper, motivated by real life problems, a systematic approach toward
the problem of robust estimation of the number of sources using information
theoretic criteria is taken. An MDL type estimator that is robust against
deviation from assumption of equal noise level across the array is studied. The
consistency of this estimator, even when deviations from the equal noise level
assumption occur, is proven. A novel low-complexity implementation method
avoiding the need for multi-dimensional searches is presented as well, making
this estimator a favorable choice for practical applications.Comment: To appear in the IEEE Transactions on Signal Processin
Sparse Signal Processing Concepts for Efficient 5G System Design
As it becomes increasingly apparent that 4G will not be able to meet the
emerging demands of future mobile communication systems, the question what
could make up a 5G system, what are the crucial challenges and what are the key
drivers is part of intensive, ongoing discussions. Partly due to the advent of
compressive sensing, methods that can optimally exploit sparsity in signals
have received tremendous attention in recent years. In this paper we will
describe a variety of scenarios in which signal sparsity arises naturally in 5G
wireless systems. Signal sparsity and the associated rich collection of tools
and algorithms will thus be a viable source for innovation in 5G wireless
system design. We will discribe applications of this sparse signal processing
paradigm in MIMO random access, cloud radio access networks, compressive
channel-source network coding, and embedded security. We will also emphasize
important open problem that may arise in 5G system design, for which sparsity
will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces
Replica Symmetry Breaking in Compressive Sensing
For noisy compressive sensing systems, the asymptotic distortion with respect
to an arbitrary distortion function is determined when a general class of
least-square based reconstruction schemes is employed. The sampling matrix is
considered to belong to a large ensemble of random matrices including i.i.d.
and projector matrices, and the source vector is assumed to be i.i.d. with a
desired distribution. We take a statistical mechanical approach by representing
the asymptotic distortion as a macroscopic parameter of a spin glass and
employing the replica method for the large-system analysis. In contrast to
earlier studies, we evaluate the general replica ansatz which includes the RS
ansatz as well as RSB. The generality of the solution enables us to study the
impact of symmetry breaking. Our numerical investigations depict that for the
reconstruction scheme with the "zero-norm" penalty function, the RS fails to
predict the asymptotic distortion for relatively large compression rates;
however, the one-step RSB ansatz gives a valid prediction of the performance
within a larger regime of compression rates.Comment: 7 pages, 3 figures, presented at ITA 201
Burst-by-Burst Adaptive Decision Feedback Equalised TCM, TTCM and BICM for H.263-Assisted Wireless Video Telephony
Decision Feedback Equaliser (DFE) aided wideband Burst-by-Burst (BbB) Adaptive Trellis Coded Modulation (TCM), Turbo Trellis Coded Modulation (TTCM) and Bit-Interleaved Coded Modulation (BICM) assisted H.263-based video transceivers are proposed and characterised in performance terms when communicating over the COST 207 Typical Urban wideband fading channel. Specifically, four different modulation modes, namely 4QAM, 8PSK, 16QAM and 64QAM are invoked and protected by the above-mentioned coded modulation schemes. The TTCM assisted scheme was found to provide the best video performance, although at the cost of the highest complexity. A range of lower-complexity arrangements will also be characterised. Finally, in order to confirm these findings in an important practical environment, we have also investigated the adaptive TTCM scheme in the CDMA-based Universal Mobile Telecommunications System's (UMTS) Terrestrial Radio Access (UTRA) scenario and the good performance of adaptive TTCM scheme recorded when communicating over the COST 207 channels was retained in the UTRA environment
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