5,661 research outputs found
An Adaptive Conditional Zero-Forcing Decoder with Full-diversity, Least Complexity and Essentially-ML Performance for STBCs
A low complexity, essentially-ML decoding technique for the Golden code and
the 3 antenna Perfect code was introduced by Sirianunpiboon, Howard and
Calderbank. Though no theoretical analysis of the decoder was given, the
simulations showed that this decoding technique has almost maximum-likelihood
(ML) performance. Inspired by this technique, in this paper we introduce two
new low complexity decoders for Space-Time Block Codes (STBCs) - the Adaptive
Conditional Zero-Forcing (ACZF) decoder and the ACZF decoder with successive
interference cancellation (ACZF-SIC), which include as a special case the
decoding technique of Sirianunpiboon et al. We show that both ACZF and ACZF-SIC
decoders are capable of achieving full-diversity, and we give sufficient
conditions for an STBC to give full-diversity with these decoders. We then show
that the Golden code, the 3 and 4 antenna Perfect codes, the 3 antenna Threaded
Algebraic Space-Time code and the 4 antenna rate 2 code of Srinath and Rajan
are all full-diversity ACZF/ACZF-SIC decodable with complexity strictly less
than that of their ML decoders. Simulations show that the proposed decoding
method performs identical to ML decoding for all these five codes. These STBCs
along with the proposed decoding algorithm outperform all known codes in terms
of decoding complexity and error performance for 2,3 and 4 transmit antennas.
We further provide a lower bound on the complexity of full-diversity
ACZF/ACZF-SIC decoding. All the five codes listed above achieve this lower
bound and hence are optimal in terms of minimizing the ACZF/ACZF-SIC decoding
complexity. Both ACZF and ACZF-SIC decoders are amenable to sphere decoding
implementation.Comment: 11 pages, 4 figures. Corrected a minor typographical erro
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
on Information Theor
A New Low-Complexity Decodable Rate-1 Full-Diversity 4 x 4 STBC with Nonvanishing Determinants
Space-time coding techniques have become common-place in wireless
communication standards as they provide an effective way to mitigate the fading
phenomena inherent in wireless channels. However, the use of Space-Time Block
Codes (STBCs) increases significantly the optimal detection complexity at the
receiver unless the low complexity decodability property is taken into
consideration in the STBC design. In this letter we propose a new
low-complexity decodable rate-1 full-diversity 4 x 4 STBC. We provide an
analytical proof that the proposed code has the Non-Vanishing-Determinant (NVD)
property, a property that can be exploited through the use of adaptive
modulation which changes the transmission rate according to the wireless
channel quality. We compare the proposed code to existing low-complexity
decodable rate-1 full-diversity 4 x 4 STBCs in terms of performance over
quasi-static Rayleigh fading channels, detection complexity and Peak-to-Average
Power Ratio (PAPR). Our code is found to provide the best performance and the
smallest PAPR which is that of the used QAM constellation at the expense of a
slight increase in detection complexity w.r.t. certain previous codes but this
will only penalize the proposed code for high-order QAM constellations.Comment: 5 pages, 3 figures, and 1 table; IEEE Transactions on Wireless
Communications, Vol. 10, No. 8, AUGUST 201
Achieving a vanishing SNR-gap to exact lattice decoding at a subexponential complexity
The work identifies the first lattice decoding solution that achieves, in the
general outage-limited MIMO setting and in the high-rate and high-SNR limit,
both a vanishing gap to the error-performance of the (DMT optimal) exact
solution of preprocessed lattice decoding, as well as a computational
complexity that is subexponential in the number of codeword bits. The proposed
solution employs lattice reduction (LR)-aided regularized (lattice) sphere
decoding and proper timeout policies. These performance and complexity
guarantees hold for most MIMO scenarios, all reasonable fading statistics, all
channel dimensions and all full-rate lattice codes.
In sharp contrast to the above manageable complexity, the complexity of other
standard preprocessed lattice decoding solutions is shown here to be extremely
high. Specifically the work is first to quantify the complexity of these
lattice (sphere) decoding solutions and to prove the surprising result that the
complexity required to achieve a certain rate-reliability performance, is
exponential in the lattice dimensionality and in the number of codeword bits,
and it in fact matches, in common scenarios, the complexity of ML-based
solutions. Through this sharp contrast, the work was able to, for the first
time, rigorously quantify the pivotal role of lattice reduction as a special
complexity reducing ingredient.
Finally the work analytically refines transceiver DMT analysis which
generally fails to address potentially massive gaps between theory and
practice. Instead the adopted vanishing gap condition guarantees that the
decoder's error curve is arbitrarily close, given a sufficiently high SNR, to
the optimal error curve of exact solutions, which is a much stronger condition
than DMT optimality which only guarantees an error gap that is subpolynomial in
SNR, and can thus be unbounded and generally unacceptable in practical
settings.Comment: 16 pages - submission for IEEE Trans. Inform. Theor
Achieving Low-Complexity Maximum-Likelihood Detection for the 3D MIMO Code
The 3D MIMO code is a robust and efficient space-time block code (STBC) for
the distributed MIMO broadcasting but suffers from high maximum-likelihood (ML)
decoding complexity. In this paper, we first analyze some properties of the 3D
MIMO code to show that the 3D MIMO code is fast-decodable. It is proved that
the ML decoding performance can be achieved with a complexity of O(M^{4.5})
instead of O(M^8) in quasi static channel with M-ary square QAM modulations.
Consequently, we propose a simplified ML decoder exploiting the unique
properties of 3D MIMO code. Simulation results show that the proposed
simplified ML decoder can achieve much lower processing time latency compared
to the classical sphere decoder with Schnorr-Euchner enumeration
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