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

A Study on the Impact of Locality in the Decoding of Binary Cyclic Codes

In this paper, we study the impact of locality on the decoding of binary cyclic codes under two approaches, namely ordered statistics decoding (OSD) and trellis decoding. Given a binary cyclic code having locality or availability, we suitably modify the OSD to obtain gains in terms of the Signal-To-Noise ratio, for a given reliability and essentially the same level of decoder complexity. With regard to trellis decoding, we show that careful introduction of locality results in the creation of cyclic subcodes having lower maximum state complexity. We also present a simple upper-bounding technique on the state complexity profile, based on the zeros of the code. Finally, it is shown how the decoding speed can be significantly increased in the presence of locality, in the moderate-to-high SNR regime, by making use of a quick-look decoder that often returns the ML codeword.Comment: Extended version of a paper submitted to ISIT 201

On a question of Babadi and Tarokh

In a recent remarkable paper, Babadi and Tarokh proved the "randomness" of sequences arising from binary linear block codes in the sense of spectral distribution, provided that their dual distances are sufficiently large. However, numerical experiments conducted by the authors revealed that Gold sequences which have dual distance 5 also satisfy such randomness property. Hence the interesting question was raised as to whether or not the stringent requirement of large dual distances can be relaxed in the theorem in order to explain the randomness of Gold sequences. This paper improves their result on several fronts and provides an affirmative answer to this question

Matching Business Process Workflows across Abstraction Levels

In Business Process Modeling, several models are defined for the same system, supporting the transition from business requirements to IT implementations. Each of these models targets a different abstraction level and stakeholder perspective. In order to maintain consistency among these models, which has become a major challenge not only in this field, the correspondence between them has to be identified. A correspondence between process models establishes which activities in one model correspond to which activities in another model. This paper presents an algorithm for determining such correspondences. The algorithm is based on an empirical study of process models at a large company in the banking sector, which revealed frequent correspondence patterns between models spanning multiple abstraction levels. The algorithm has two phases, first establishing correspondences based on similarity of model element attributes such as types and names and then refining the result based on the structure of the models. Compared to previous work, our algorithm can recover complex correspondences relating whole process fragments rather than just individual activities. We evaluate the algorithm on 26 pairs of business-technical and technical-IT level models from four real-world projects, achieving overall precision of 93% and recall of 70%. Given the substantial recall and the high precision, the algorithm helps automating significant part of the correspondence recovery for such models.Ministerio de Ciencia e Innovación TIN2008-03107Ministerio de Economía y Competitividad TIN2011-2379

On Maximum-Likelihood Decoding of Time-Varying Trellis Codes

Decoding complexity of convolutional and trellis codes by Viterbi decoder can be reduced by applying suggested merging algorithm to the Forney code trellis. The algorithm can be applied for every trellis section separately, which is convenient for time-varying codes, and it outputs the minimal trellis of the section. In case of convolutional codes, the same minimal trellis of every section can be obtained from the syndrome trellis of proposed split code

Compressed Online Dictionary Learning for Fast fMRI Decomposition

We present a method for fast resting-state fMRI spatial decomposi-tions of very large datasets, based on the reduction of the temporal dimension before applying dictionary learning on concatenated individual records from groups of subjects. Introducing a measure of correspondence between spatial decompositions of rest fMRI, we demonstrates that time-reduced dictionary learning produces result as reliable as non-reduced decompositions. We also show that this reduction significantly improves computational scalability

A hardware spinal decoder

Spinal codes are a recently proposed capacity-achieving rateless code. While hardware encoding of spinal codes is straightforward, the design of an efficient, high-speed hardware decoder poses significant challenges. We present the first such decoder. By relaxing data dependencies inherent in the classic M-algorithm decoder, we obtain area and throughput competitive with 3GPP turbo codes as well as greatly reduced latency and complexity. The enabling architectural feature is a novel alpha-beta incremental approximate selection algorithm. We also present a method for obtaining hints which anticipate successful or failed decoding, permitting early termination and/or feedback-driven adaptation of the decoding parameters. We have validated our implementation in FPGA with on-air testing. Provisional hardware synthesis suggests that a near-capacity implementation of spinal codes can achieve a throughput of 12.5 Mbps in a 65 nm technology while using substantially less area than competitive 3GPP turbo code implementations.Irwin Mark Jacobs and Joan Klein Jacobs Presidential FellowshipIntel Corporation (Fellowship)Claude E. Shannon Research Assistantshi

4D Ariadne the Static Debugger of Java Programs

Development environments support the programmer in numerous ways from syntax highlighting to different refactoring and code generating methods. However, there are cases where these tools are limited or not usable, such as getting familiar with large and complex source codes written by a third person; finding the complexities of huge projects or finding semantic errors.In this paper we present our static analyzer tool, called 4D Ariadne, which concentrates on these problems. 4D Ariadne is a static debugger of Object Oriented applications written in Java programming language. It calculates data dependencies of objects being able to compute them both forward and backward. As 4D Ariadne provides only the direct influences to the user, it can be considered as an alternative of traditional debuggers, without executing the code. 4D Ariadne also provides dynamic call graphs representing polymorphic properties of objects