390 research outputs found
Gaussian Belief Propagation Based Multiuser Detection
In this work, we present a novel construction for solving the linear
multiuser detection problem using the Gaussian Belief Propagation algorithm.
Our algorithm yields an efficient, iterative and distributed implementation of
the MMSE detector. We compare our algorithm's performance to a recent result
and show an improved memory consumption, reduced computation steps and a
reduction in the number of sent messages. We prove that recent work by
Montanari et al. is an instance of our general algorithm, providing new
convergence results for both algorithms.Comment: 6 pages, 1 figures, appeared in the 2008 IEEE International Symposium
on Information Theory, Toronto, July 200
Unified bit-based probabilistic data association aided MIMO detection for high-order QAM
A unified Bit-based Probabilistic Data Association (B-PDA) detection approach is proposed for Multiple-Input Multiple-Output (MIMO) systems employing high-order Quadrature Amplitude Modulation (QAM). The new approach transforms the symbol detection process of QAM to a bit-based process by introducing a Unified Matrix Representation (UMR) of QAM. Both linear natural and nonlinear Gray bit-to-symbol mapping schemes are considered. Our analytical and simulation results demonstrate that the linear natural mapping based B-PDA approach attains an improved detection performance, despite dramatically reducing the computational complexity in contrast to the conventional symbol-based PDA aided MIMO detector. Furthermore, it is shown that the linear natural mapping based B-PDA method is capable of approaching the lower bound performance provided by the nonlinear Gray mapping based B-PDA MIMO detector. Since the linear natural mapping based scheme is simpler and more applicable in practice than its nonlinear Gray mapping based counterpart, we conclude that in the context of the uncoded B-PDA MIMO detector it is preferable to use the linear natural bit-to-symbol mapping, rather than the nonlinear Gray mapping
A Family of Likelihood Ascent Search Multiuser Detectors: an Upper Bound of Bit Error Rate and a Lower Bound of Asymptotic Multiuser Efficiency
In this paper, the bit error performance of a family of likelihood ascent
search (LAS) multiuser detectors is analyzed. An upper bound on the BER of any
LAS detector is obtained by bounding the fixed point region with the worst
initial detector. The concept of indecomposable errors developed by Verdu is
applied to tighten the upper bound. In a special instance, the upper bound is
reduced to that for all the local maximum likelihood detectors. The upper bound
is comparable with that of the optimum detector obtained by Verdu. A lower
bound on the asymptotic multiuser efficiency (AME) is then obtained. It is
shown that there are nontrivial CDMA channels such that a LAS detector can
achieve unit AME regardless of user number. The AME lower bound provides a
means for further seeking a good set of spreading sequences and power
distribution for spectral and power efficient CDMA.Comment: To appear in IEEE Trans. on Communication
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
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