196 research outputs found
Low-Complexity Detection/Equalization in Large-Dimension MIMO-ISI Channels Using Graphical Models
In this paper, we deal with low-complexity near-optimal
detection/equalization in large-dimension multiple-input multiple-output
inter-symbol interference (MIMO-ISI) channels using message passing on
graphical models. A key contribution in the paper is the demonstration that
near-optimal performance in MIMO-ISI channels with large dimensions can be
achieved at low complexities through simple yet effective
simplifications/approximations, although the graphical models that represent
MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1)
use of Markov Random Field (MRF) based graphical model with pairwise
interaction, in conjunction with {\em message/belief damping}, and 2) use of
Factor Graph (FG) based graphical model with {\em Gaussian approximation of
interference} (GAI). The per-symbol complexities are and
for the MRF and the FG with GAI approaches, respectively, where
and denote the number of channel uses per frame, and number of transmit
antennas, respectively. These low-complexities are quite attractive for large
dimensions, i.e., for large . From a performance perspective, these
algorithms are even more interesting in large-dimensions since they achieve
increasingly closer to optimum detection performance for increasing .
Also, we show that these message passing algorithms can be used in an iterative
manner with local neighborhood search algorithms to improve the
reliability/performance of -QAM symbol detection
A BP-MF-EP Based Iterative Receiver for Joint Phase Noise Estimation, Equalization and Decoding
In this work, with combined belief propagation (BP), mean field (MF) and
expectation propagation (EP), an iterative receiver is designed for joint phase
noise (PN) estimation, equalization and decoding in a coded communication
system. The presence of the PN results in a nonlinear observation model.
Conventionally, the nonlinear model is directly linearized by using the
first-order Taylor approximation, e.g., in the state-of-the-art soft-input
extended Kalman smoothing approach (soft-in EKS). In this work, MF is used to
handle the factor due to the nonlinear model, and a second-order Taylor
approximation is used to achieve Gaussian approximation to the MF messages,
which is crucial to the low-complexity implementation of the receiver with BP
and EP. It turns out that our approximation is more effective than the direct
linearization in the soft-in EKS with similar complexity, leading to
significant performance improvement as demonstrated by simulation results.Comment: 5 pages, 3 figures, Resubmitted to IEEE Signal Processing Letter
Receiver Architectures for MIMO-OFDM Based on a Combined VMP-SP Algorithm
Iterative information processing, either based on heuristics or analytical
frameworks, has been shown to be a very powerful tool for the design of
efficient, yet feasible, wireless receiver architectures. Within this context,
algorithms performing message-passing on a probabilistic graph, such as the
sum-product (SP) and variational message passing (VMP) algorithms, have become
increasingly popular.
In this contribution, we apply a combined VMP-SP message-passing technique to
the design of receivers for MIMO-ODFM systems. The message-passing equations of
the combined scheme can be obtained from the equations of the stationary points
of a constrained region-based free energy approximation. When applied to a
MIMO-OFDM probabilistic model, we obtain a generic receiver architecture
performing iterative channel weight and noise precision estimation,
equalization and data decoding. We show that this generic scheme can be
particularized to a variety of different receiver structures, ranging from
high-performance iterative structures to low complexity receivers. This allows
for a flexible design of the signal processing specially tailored for the
requirements of each specific application. The numerical assessment of our
solutions, based on Monte Carlo simulations, corroborates the high performance
of the proposed algorithms and their superiority to heuristic approaches
Expectation propagation as a solution for digital communication systems.
In the context of digital communications, a digital receiver is required to provide an estimation of the transmitted symbols. Nowadays channel decoders highly benefit from soft (probabilistic) estimates for each transmitted symbol rather than from hard decisions. For this reason, digital receivers must be designed to provide the probability that each possible symbol was transmitted based on the received corrupted signal. Since exact inference might be unfeasible in terms of complexity for high-order scenarios, it is necessary to resort to approximate inference, such as the linear minimum mean square error (LMMSE) criterion. The LMMSE approximates the discrete prior information of the transmitted symbols with a Gaussian distribution, which causes a degradation in its performance. In this thesis, an alternative approximate statistical technique is applied to the design of a digital
probabilistic receiver in digital communications. Specifically, the expectation
propagation (EP) algorithm is investigated to find the Gaussian posterior probability density function (pdf) that minimizes the Kullback-Leibler (KL) divergence with respect to the true posterior pdf. Two different communication system scenarios are studied: a single-input singleoutput (SISO) digital communication system with memory channel and a multipleinput multiple-output (MIMO) system with memoryless channel. In the SISO scenario, three different designs of a soft standalone and turbo equalizer based on the EP algorithm are developed: the block or batch approach, the filter-type
version that emulates theWiener filter behavior and the smoothing equalizer which proceeds similarly to a Kalman smoother. Finally, the block EP implementation is also adapted to MIMO scenarios with feedback from the decoder. In both scenarios, the EP is applied iteratively, including a damping mechanism and a control to avoid negative values of variances, which would lead to instabilities (specially for high-order constellations). Experimental results included through the thesis show that the EP algorithm applied to communication systems greatly improves the performance of previous approaches found in the literature with a complexity slightly increased but still proportional to that of the LMMSE. These results also show the robustness of the algorithm even for high-order modulations, large memory channels and high number of antennas. Major contributions of this dissertation have been published in four journal (one of them is still under review) and two conference papers. One more paper will be submitted to a journal soon. All these papers are listed below:
• Irene Santos, Juan José Murillo-Fuentes, Rafael Boloix-Tortosa, Eva Arias
de Reyna and Pablo M. Olmos, "Expectation Propagation as Turbo Equalizer
in ISI Channels," IEEE Transactions on Communications, vol. 65, no.1, pp.
360-370, Jan 2017.
• Irene Santos, Juan José Murillo-Fuentes, Eva Arias de Reyna and Pablo M.
Olmos, "Turbo EP-based Equalization: a Filter-Type Implementation," IEEE
Transactions on Communications, Sep 2017, Accepted. [Online] Available:
https://ieeexplore.ieee.org/document/8353388/
• Irene Santos, Juan José Murillo-Fuentes, Eva Arias-de-Reyna and Pablo M.
Olmos, "Probabilistic Equalization With a Smoothing Expectation Propagation
Approach," IEEE Transactions on Wireless Communications, vol. 16,
no. 5, pp. 2950-2962, May 2017.
• Irene Santos, Juan José Murillo-Fuentes and Eva Arias-de-Reyna, "Equalization
with Expectation Propagation at Smoothing Level," To be submitted.
[Online] Available: https://arxiv.org/abs/1809.00806
• Irene Santos and Juan José Murillo-Fuentes, "EP-based turbo detection for
MIMO receivers and large-scale systems," IEEE Transactions on Vehicular
Technology, May 2018, Under review. [Online] Available:
https://arxiv.org/abs/1805.05065
• Irene Santos, Juan José Murillo-Fuentes, and Pablo M. Olmos, "Block
expectation propagation equalization for ISI channels," 23rd European Signal
Processing Conference (EUSIPCO 2015), Nice, 2015, pp. 379-383.
• Irene Santos, and Juan José Murillo-Fuentes, "Improved probabilistic EPbased receiver for MIMO systems and high-order modulations," XXXIII
Simposium Nacional de la Unión CientÃfica Internacional de Radio (URSI
2018), Granada, 2018.En el ámbito de las comunicaciones digitales, es necesario un receptor digital que proporcione una estimación de los sÃmbolos transmitidos. Los decodificadores de canal actuales se benefician enormemente de estimaciones suaves (probabilÃsticas) de cada sÃmbolo transmitido, en vez de estimaciones duras. Por este motivo, los receptores digitales deben diseñarse para proporcionar la probabilidad de cada posible sÃmbolo que fue transmitido en base a la señal recibida y corrupta. Dado que la inferencia exacta puede no ser posible en términos de complejidad para escenarios de alto orden, es necesario recurrir a inferencia aproximada, como por
ejemplo el criterio de linear minimum-mean-square-error (LMMSE). El LMMSE aproxima la información a priori discreta de los sÃmbolos transmitidos con una distribución Gaussiana, lo cual provoca una degradación en su resultado. En esta tesis, se aplica una técnica alternativa de inferencia estadÃstica para diseñar un receptor digital probabilÃstico de comunicaciones digitales. En concreto, se investiga el algoritmo expectation propagation (EP) con el objetivo de encontrar la función densidad de probabilidad (pdf) a posteriori Gaussiana que minimiza la divergencia de Kullback-Leibler (KL) con respecto a la pdf a posteriori verdadera. Se estudian dos escenarios de comunicaciones digitales diferentes: un sistema de comunicaciones single-input single-output (SISO) con canales con memoria y un sistema multiple-input multiple-output (MIMO) con canales sin memoria. Para el
escenario SISO se proponen tres diseños diferentes para un igualador probabilÃstico, tanto simple como turbo, que está basado en el algoritmo EP: una versión bloque, una versión filtrada que emula el comportamiento de un filtroWiener y una versión smoothing que funciona de forma similar a un Kalman smoother. Finalmente, la implementación del EP en bloque se adapta también para escenarios MIMO con realimentación desde el decodificador. En ambos escenarios, el EP se aplica de forma iterativa, incluyendo un mecanismo de damping y un control para evitar valores de varianzas negativas, que darÃan lugar a inestabilidades (especialmente, en
constelaciones de alto orden). Los resultados experimentales que se incluyen en la tesis muestran que, cuando el algoritmo EP se aplica a sistemas de comunicaciones, se mejora notablemente el resultado de otras propuestas anteriores que existen en la literatura, con un pequeño incremento de la complejidad que es proporcional a la carga del LMMSE. Estos resultados también demuestran la robustez del algoritmo incluso para modulaciones de alto orden, canales con bastante memoria y un gran número de antenas.
Las principales contribuciones de esta tesis se han publicado en cuatro artÃculos de revista (uno de ellos todavÃa bajo revisión) y dos artÃculos de conferencia. Otro artÃculo adicional se encuentra en preparación y se enviarÃa próximamente a una revista. Estos se citan a continuación:
• Irene Santos, Juan José Murillo-Fuentes, Rafael Boloix-Tortosa, Eva Arias
de Reyna and Pablo M. Olmos, "Expectation Propagation as Turbo Equalizer
in ISI Channels," IEEE Transactions on Communications, vol. 65, no.1, pp.
360-370, Jan 2017.
• Irene Santos, Juan José Murillo-Fuentes, Eva Arias de Reyna and Pablo
M. Olmos, "Turbo EP-based Equalization: a Filter-Type Implementation,"
IEEE Transactions on Communications, Sep 2017, Aceptado. [Online]
Disponible: https://ieeexplore.ieee.org/document/8353388/
• Irene Santos, Juan José Murillo-Fuentes, Eva Arias-de-Reyna and Pablo M.
Olmos, "Probabilistic Equalization With a Smoothing Expectation Propagation
Approach," IEEE Transactions on Wireless Communications, vol. 16,
no. 5, pp. 2950-2962, May 2017.
• Irene Santos, Juan José Murillo-Fuentes and Eva Arias-de-Reyna, "Equalization with Expectation Propagation at Smoothing Level," En preparación. [Online] Disponible: https://arxiv.org/abs/1809.00806
• Irene Santos and Juan José Murillo-Fuentes, "EP-based turbo detection for
MIMO receivers and large-scale systems," IEEE Transactions on Vehicular
Technology, May 2018, En revisión. [Online] Disponible: https://arxiv.org/abs/1805.05065
• Irene Santos, Juan José Murillo-Fuentes, and Pablo M. Olmos, "Block
expectation propagation equalization for ISI channels," 23rd European Signal
Processing Conference (EUSIPCO 2015), Nice, 2015, pp. 379-383.
• Irene Santos, and Juan José Murillo-Fuentes, "Improved probabilistic EPbased receiver for MIMO systems and high-order modulations," XXXIII Simposium Nacional de la Unión CientÃfica Internacional de Radio (URSI
2018), Granada, 2018
Gaussian Message Passing for Overloaded Massive MIMO-NOMA
This paper considers a low-complexity Gaussian Message Passing (GMP) scheme
for a coded massive Multiple-Input Multiple-Output (MIMO) systems with
Non-Orthogonal Multiple Access (massive MIMO-NOMA), in which a base station
with antennas serves sources simultaneously in the same frequency.
Both and are large numbers, and we consider the overloaded cases
with . The GMP for MIMO-NOMA is a message passing algorithm operating
on a fully-connected loopy factor graph, which is well understood to fail to
converge due to the correlation problem. In this paper, we utilize the
large-scale property of the system to simplify the convergence analysis of the
GMP under the overloaded condition. First, we prove that the \emph{variances}
of the GMP definitely converge to the mean square error (MSE) of Linear Minimum
Mean Square Error (LMMSE) multi-user detection. Secondly, the \emph{means} of
the traditional GMP will fail to converge when . Therefore, we propose and derive a new
convergent GMP called scale-and-add GMP (SA-GMP), which always converges to the
LMMSE multi-user detection performance for any , and show that it
has a faster convergence speed than the traditional GMP with the same
complexity. Finally, numerical results are provided to verify the validity and
accuracy of the theoretical results presented.Comment: Accepted by IEEE TWC, 16 pages, 11 figure
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