1,703 research outputs found
MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity
In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts
MIMO Detection for High-Order QAM Based on a Gaussian Tree Approximation
This paper proposes a new detection algorithm for MIMO communication systems
employing high order QAM constellations. The factor graph that corresponds to
this problem is very loopy; in fact, it is a complete graph. Hence, a
straightforward application of the Belief Propagation (BP) algorithm yields
very poor results. Our algorithm is based on an optimal tree approximation of
the Gaussian density of the unconstrained linear system. The finite-set
constraint is then applied to obtain a loop-free discrete distribution. It is
shown that even though the approximation is not directly applied to the exact
discrete distribution, applying the BP algorithm to the loop-free factor graph
outperforms current methods in terms of both performance and complexity. The
improved performance of the proposed algorithm is demonstrated on the problem
of MIMO detection
MIMO Underwater Visible Light Communications: Comprehensive Channel Study, Performance Analysis, and Multiple-Symbol Detection
In this paper, we analytically study the bit error rate (BER) performance of
underwater visible light communication (UVLC) systems with binary pulse
position modulation (BPPM). We simulate the channel fading-free impulse
response (FFIR) based on Monte Carlo numerical method to take into account the
absorption and scattering effects. Additionally, to characterize turbulence
effects, we multiply the aforementioned FFIR by a fading coefficient which for
weak oceanic turbulence can be modeled as a lognormal random variable (RV).
Moreover, to mitigate turbulence effects, we employ multiple transmitters
and/or receivers, i.e., spatial diversity technique over UVLC links.
Closed-form expressions for the system BER are provided, when equal gain
combiner (EGC) is employed at the receiver side, thanks to Gauss-Hermite
quadrature formula and approximation to the sum of lognormal RVs. We further
apply saddle-point approximation, an accurate photon-counting-based method, to
evaluate the system BER in the presence of shot noise. Both laser-based
collimated and light emitting diode (LED)-based diffusive links are
investigated. Since multiple-scattering effect of UVLC channels on the
propagating photons causes considerable inter-symbol interference (ISI),
especially for diffusive channels, we also obtain the optimum multiple-symbol
detection (MSD) algorithm to significantly alleviate ISI effects and improve
the system performance. Our numerical analysis indicates good matches between
the analytical and photon-counting results implying the negligibility of
signal-dependent shot noise, and also between analytical results and numerical
simulations confirming the accuracy of our derived closed-form expressions for
the system BER. Besides, our results show that spatial diversity significantly
mitigates fading impairments while MSD considerably alleviates ISI
deteriorations
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