4,764 research outputs found
Low-complexity dominance-based Sphere Decoder for MIMO Systems
The sphere decoder (SD) is an attractive low-complexity alternative to
maximum likelihood (ML) detection in a variety of communication systems. It is
also employed in multiple-input multiple-output (MIMO) systems where the
computational complexity of the optimum detector grows exponentially with the
number of transmit antennas. We propose an enhanced version of the SD based on
an additional cost function derived from conditions on worst case interference,
that we call dominance conditions. The proposed detector, the king sphere
decoder (KSD), has a computational complexity that results to be not larger
than the complexity of the sphere decoder and numerical simulations show that
the complexity reduction is usually quite significant
On the sphere-decoding algorithm I. Expected complexity
The problem of finding the least-squares solution to a system of linear equations where the unknown vector is comprised of integers, but the matrix coefficient and given vector are comprised of real numbers, arises in many applications: communications, cryptography, GPS, to name a few. The problem is equivalent to finding the closest lattice point to a given point and is known to be NP-hard. In communications applications, however, the given vector is not arbitrary but rather is an unknown lattice point that has been perturbed by an additive noise vector whose statistical properties are known. Therefore, in this paper, rather than dwell on the worst-case complexity of the integer least-squares problem, we study its expected complexity, averaged over the noise and over the lattice. For the "sphere decoding" algorithm of Fincke and Pohst, we find a closed-form expression for the expected complexity, both for the infinite and finite lattice. It is demonstrated in the second part of this paper that, for a wide range of signal-to-noise ratios (SNRs) and numbers of antennas, the expected complexity is polynomial, in fact, often roughly cubic. Since many communications systems operate at noise levels for which the expected complexity turns out to be polynomial, this suggests that maximum-likelihood decoding, which was hitherto thought to be computationally intractable, can, in fact, be implemented in real time - a result with many practical implications
Advanced constellation and demapper schemes for next generation digital terrestrial television broadcasting systems
206 p.Esta tesis presenta un nuevo tipo de constelaciones llamadas no uniformes. Estos esquemas presentan una eficacia de hasta 1,8 dB superior a las utilizadas en los últimos sistemas de comunicaciones de televisión digital terrestre y son extrapolables a cualquier otro sistema de comunicaciones (satélite, móvil, cable¿). Además, este trabajo contribuye al diseño de constelaciones con una nueva metodología que reduce el tiempo de optimización de días/horas (metodologías actuales) a horas/minutos con la misma eficiencia. Todas las constelaciones diseñadas se testean bajo una plataforma creada en esta tesis que simula el estándar de radiodifusión terrestre más avanzado hasta la fecha (ATSC 3.0) bajo condiciones reales de funcionamiento.Por otro lado, para disminuir la latencia de decodificación de estas constelaciones esta tesis propone dos técnicas de detección/demapeo. Una es para constelaciones no uniformes de dos dimensiones la cual disminuye hasta en un 99,7% la complejidad del demapeo sin empeorar el funcionamiento del sistema. La segunda técnica de detección se centra en las constelaciones no uniformes de una dimensión y presenta hasta un 87,5% de reducción de la complejidad del receptor sin pérdidas en el rendimiento.Por último, este trabajo expone un completo estado del arte sobre tipos de constelaciones, modelos de sistema, y diseño/demapeo de constelaciones. Este estudio es el primero realizado en este campo
Cooperative Lattice Coding and Decoding
A novel lattice coding framework is proposed for outage-limited cooperative
channels. This framework provides practical implementations for the optimal
cooperation protocols proposed by Azarian et al. In particular, for the relay
channel we implement a variant of the dynamic decode and forward protocol,
which uses orthogonal constellations to reduce the channel seen by the
destination to a single-input single-output time-selective one, while
inheriting the same diversity-multiplexing tradeoff. This simplification allows
for building the receiver using traditional belief propagation or tree search
architectures. Our framework also generalizes the coding scheme of Yang and
Belfiore in the context of amplify and forward cooperation. For the cooperative
multiple access channel, a tree coding approach, matched to the optimal linear
cooperation protocol of Azarain et al, is developed. For this scenario, the
MMSE-DFE Fano decoder is shown to enjoy an excellent tradeoff between
performance and complexity. Finally, the utility of the proposed schemes is
established via a comprehensive simulation study.Comment: 25 pages, 8 figure
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