395 research outputs found
DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models
The work identifies the first general, explicit, and non-random MIMO
encoder-decoder structures that guarantee optimality with respect to the
diversity-multiplexing tradeoff (DMT), without employing a computationally
expensive maximum-likelihood (ML) receiver. Specifically, the work establishes
the DMT optimality of a class of regularized lattice decoders, and more
importantly the DMT optimality of their lattice-reduction (LR)-aided linear
counterparts. The results hold for all channel statistics, for all channel
dimensions, and most interestingly, irrespective of the particular lattice-code
applied. As a special case, it is established that the LLL-based LR-aided
linear implementation of the MMSE-GDFE lattice decoder facilitates DMT optimal
decoding of any lattice code at a worst-case complexity that grows at most
linearly in the data rate. This represents a fundamental reduction in the
decoding complexity when compared to ML decoding whose complexity is generally
exponential in rate.
The results' generality lends them applicable to a plethora of pertinent
communication scenarios such as quasi-static MIMO, MIMO-OFDM, ISI,
cooperative-relaying, and MIMO-ARQ channels, in all of which the DMT optimality
of the LR-aided linear decoder is guaranteed. The adopted approach yields
insight, and motivates further study, into joint transceiver designs with an
improved SNR gap to ML decoding.Comment: 16 pages, 1 figure (3 subfigures), submitted to the IEEE Transactions
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Joint data detection and channel estimation for OFDM systems
We develop new blind and semi-blind data detectors and channel estimators for orthogonal frequency-division multiplexing (OFDM) systems. Our data detectors require minimizing a complex, integer quadratic form in the data vector. The semi-blind detector uses both channel correlation and noise variance. The quadratic for the blind detector suffers from rank deficiency; for this, we give a low-complexity solution. Avoiding a computationally prohibitive exhaustive search, we solve our data detectors using sphere decoding (SD) and V-BLAST and provide simple adaptations of the SD algorithm. We consider how the blind detector performs under mismatch, generalize the basic data detectors to nonunitary constellations, and extend them to systems with pilots and virtual carriers. Simulations show that our data detectors perform well
PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink
We investigate an orthogonal frequency-division multiplexing (OFDM)-based
downlink transmission scheme for large-scale multi-user (MU) multiple-input
multiple-output (MIMO) wireless systems. The use of OFDM causes a high
peak-to-average (power) ratio (PAR), which necessitates expensive and
power-inefficient radio-frequency (RF) components at the base station. In this
paper, we present a novel downlink transmission scheme, which exploits the
massive degrees-of-freedom available in large-scale MU-MIMO-OFDM systems to
achieve low PAR. Specifically, we propose to jointly perform MU precoding, OFDM
modulation, and PAR reduction by solving a convex optimization problem. We
develop a corresponding fast iterative truncation algorithm (FITRA) and show
numerical results to demonstrate tremendous PAR-reduction capabilities. The
significantly reduced linearity requirements eventually enable the use of
low-cost RF components for the large-scale MU-MIMO-OFDM downlink.Comment: To appear in IEEE Journal on Selected Areas in Communication
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
Space Frequency Codes from Spherical Codes
A new design method for high rate, fully diverse ('spherical') space
frequency codes for MIMO-OFDM systems is proposed, which works for arbitrary
numbers of antennas and subcarriers. The construction exploits a differential
geometric connection between spherical codes and space time codes. The former
are well studied e.g. in the context of optimal sequence design in CDMA
systems, while the latter serve as basic building blocks for space frequency
codes. In addition a decoding algorithm with moderate complexity is presented.
This is achieved by a lattice based construction of spherical codes, which
permits lattice decoding algorithms and thus offers a substantial reduction of
complexity.Comment: 5 pages. Final version for the 2005 IEEE International Symposium on
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