121,160 research outputs found
Improved Average Complexity for Comparison-Based Sorting
This paper studies the average complexity on the number of comparisons for
sorting algorithms. Its information-theoretic lower bound is . For many efficient algorithms, the first term is easy to
achieve and our focus is on the (negative) constant factor of the linear term.
The current best value is for the MergeInsertion sort. Our new value
is , narrowing the gap by some . An important building block of
our algorithm is "two-element insertion," which inserts two numbers and
, , into a sorted sequence . This insertion algorithm is still
sufficiently simple for rigorous mathematical analysis and works well for a
certain range of the length of for which the simple binary insertion does
not, thus allowing us to take a complementary approach with the binary
insertion.Comment: 21 pages, 2 figure
Improved Successive Cancellation Flip Decoding of Polar Codes Based on Error Distribution
Polar codes are a class of linear block codes that provably achieves channel
capacity, and have been selected as a coding scheme for generation
wireless communication standards. Successive-cancellation (SC) decoding of
polar codes has mediocre error-correction performance on short to moderate
codeword lengths: the SC-Flip decoding algorithm is one of the solutions that
have been proposed to overcome this issue. On the other hand, SC-Flip has a
higher implementation complexity compared to SC due to the required
log-likelihood ratio (LLR) selection and sorting process. Moreover, it requires
a high number of iterations to reach good error-correction performance. In this
work, we propose two techniques to improve the SC-Flip decoding algorithm for
low-rate codes, based on the observation of channel-induced error
distributions. The first one is a fixed index selection (FIS) scheme to avoid
the substantial implementation cost of LLR selection and sorting with no cost
on error-correction performance. The second is an enhanced index selection
(EIS) criterion to improve the error-correction performance of SC-Flip
decoding. A reduction of in the implementation cost of logic elements
is estimated with the FIS approach, while simulation results show that EIS
leads to an improvement on error-correction performance improvement up to
dB at a target FER of .Comment: This version of the manuscript corrects an error in the previous
ArXiv version, as well as the published version in IEEE Xplore under the same
title, which has the DOI:10.1109/WCNCW.2018.8368991. The corrections include
all the simulations of SC-Flip-based and SC-Oracle decoders, along with
associated comments in-tex
Hybridizing Non-dominated Sorting Algorithms: Divide-and-Conquer Meets Best Order Sort
Many production-grade algorithms benefit from combining an asymptotically
efficient algorithm for solving big problem instances, by splitting them into
smaller ones, and an asymptotically inefficient algorithm with a very small
implementation constant for solving small subproblems. A well-known example is
stable sorting, where mergesort is often combined with insertion sort to
achieve a constant but noticeable speed-up.
We apply this idea to non-dominated sorting. Namely, we combine the
divide-and-conquer algorithm, which has the currently best known asymptotic
runtime of , with the Best Order Sort algorithm, which
has the runtime of but demonstrates the best practical performance
out of quadratic algorithms.
Empirical evaluation shows that the hybrid's running time is typically not
worse than of both original algorithms, while for large numbers of points it
outperforms them by at least 20%. For smaller numbers of objectives, the
speedup can be as large as four times.Comment: A two-page abstract of this paper will appear in the proceedings
companion of the 2017 Genetic and Evolutionary Computation Conference (GECCO
2017
Dual-lattice ordering and partial lattice reduction for SIC-based MIMO detection
This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, we propose low-complexity lattice detection algorithms for successive interference cancelation (SIC) in multi-input multi-output (MIMO) communications. First, we present a dual-lattice view of the vertical Bell Labs Layered Space-Time (V-BLAST) detection. We show that V-BLAST ordering is equivalent to applying sorted QR decomposition to the dual basis, or equivalently, applying sorted Cholesky decomposition to the associated Gram matrix. This new view results in lower detection complexity and allows simultaneous ordering and detection. Second, we propose a partial reduction algorithm that only performs lattice reduction for the last several, weak substreams, whose implementation is also facilitated by the dual-lattice view. By tuning the block size of the partial reduction (hence the complexity), it can achieve a variable diversity order, hence offering a graceful tradeoff between performance and complexity for SIC-based MIMO detection. Numerical results are presented to compare the computational costs and to verify the achieved diversity order
ND-Tree-based update: a Fast Algorithm for the Dynamic Non-Dominance Problem
In this paper we propose a new method called ND-Tree-based update (or shortly
ND-Tree) for the dynamic non-dominance problem, i.e. the problem of online
update of a Pareto archive composed of mutually non-dominated points. It uses a
new ND-Tree data structure in which each node represents a subset of points
contained in a hyperrectangle defined by its local approximate ideal and nadir
points. By building subsets containing points located close in the objective
space and using basic properties of the local ideal and nadir points we can
efficiently avoid searching many branches in the tree. ND-Tree may be used in
multiobjective evolutionary algorithms and other multiobjective metaheuristics
to update an archive of potentially non-dominated points. We prove that the
proposed algorithm has sub-linear time complexity under mild assumptions. We
experimentally compare ND-Tree to the simple list, Quad-tree, and M-Front
methods using artificial and realistic benchmarks with up to 10 objectives and
show that with this new method substantial reduction of the number of point
comparisons and computational time can be obtained. Furthermore, we apply the
method to the non-dominated sorting problem showing that it is highly
competitive to some recently proposed algorithms dedicated to this problem.Comment: 15 pages, 21 figures, 3 table
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