Shortening array codes and the perfect 1-factorization conjecture

The existence of a perfect 1-factorization of the complete graph with n nodes, namely, K_n , for arbitrary even number n, is a 40-year-old open problem in graph theory. So far, two infinite families of perfect 1-factorizations have been shown to exist, namely, the factorizations of K_(p+1) and K_2p , where p is an arbitrary prime number (p > 2) . It was shown in previous work that finding a perfect 1-factorization of K_n is related to a problem in coding, specifically, it can be reduced to constructing an MDS (Minimum Distance Separable), lowest density array code. In this paper, a new method for shortening arbitrary array codes is introduced. It is then used to derive the K_(p+1) family of perfect 1-factorization from the K_2p family. Namely, techniques from coding theory are used to prove a new result in graph theory-that the two factorization families are related

Low-density MDS codes and factors of complete graphs

We present a class of array code of size n×l, where l=2n or 2n+1, called B-Code. The distances of the B-Code and its dual are 3 and l-1, respectively. The B-Code and its dual are optimal in the sense that i) they are maximum-distance separable (MDS), ii) they have an optimal encoding property, i.e., the number of the parity bits that are affected by change of a single information bit is minimal, and iii) they have optimal length. Using a new graph description of the codes, we prove an equivalence relation between the construction of the B-Code (or its dual) and a combinatorial problem known as perfect one-factorization of complete graphs, thus obtaining constructions of two families of the B-Code and its dual, one of which is new. Efficient decoding algorithms are also given, both for erasure correcting and for error correcting. The existence of perfect one-factorizations for every complete graph with an even number of nodes is a 35 years long conjecture in graph theory. The construction of B-Codes of arbitrary odd length will provide an affirmative answer to the conjecture

A New Class of MDS Erasure Codes Based on Graphs

Maximum distance separable (MDS) array codes are XOR-based optimal erasure codes that are particularly suitable for use in disk arrays. This paper develops an innovative method to build MDS array codes from an elegant class of nested graphs, termed \textit{complete-graph-of-rings (CGR)}. We discuss a systematic and concrete way to transfer these graphs to array codes, unveil an interesting relation between the proposed map and the renowned perfect 1-factorization, and show that the proposed CGR codes subsume B-codes as their "contracted" codes. These new codes, termed \textit{CGR codes}, and their dual codes are simple to describe, and require minimal encoding and decoding complexity.Comment: in Proceeding of IEEE Global Communications Conference (GLOBECOM

Reduced Receivers for Faster-than-Nyquist Signaling and General Linear Channels

Fast and reliable data transmission together with high bandwidth efficiency are important design aspects in a modern digital communication system. Many different approaches exist but in this thesis bandwidth efficiency is obtained by increasing the data transmission rate with the faster-than-Nyquist (FTN) framework while keeping a fixed power spectral density (PSD). In FTN consecutive information carrying symbols can overlap in time and in that way introduce a controlled amount of intentional intersymbol interference (ISI). This technique was introduced already in 1975 by Mazo and has since then been extended in many directions. Since the ISI stemming from practical FTN signaling can be of significant duration, optimum detection with traditional methods is often prohibitively complex, and alternative equalization methods with acceptable complexity-performance tradeoffs are needed. The key objective of this thesis is therefore to design reduced-complexity receivers for FTN and general linear channels that achieve optimal or near-optimal performance. Although the performance of a detector can be measured by several means, this thesis is restricted to bit error rate (BER) and mutual information results. FTN signaling is applied in two ways: As a separate uncoded narrowband communication system or in a coded scenario consisting of a convolutional encoder, interleaver and the inner ISI mechanism in serial concatenation. Turbo equalization where soft information in the form of log likelihood ratios (LLRs) is exchanged between the equalizer and the decoder is a commonly used decoding technique for coded FTN signals. The first part of the thesis considers receivers and arising stability problems when working within the white noise constraint. New M-BCJR algorithms for turbo equalization are proposed and compared to reduced-trellis VA and BCJR benchmarks based on an offset label idea. By adding a third low-complexity M-BCJR recursion, LLR quality is improved for practical values of M. M here measures the reduced number of BCJR computations for each data symbol. An improvement of the minimum phase conversion that sharpens the focus of the ISI model energy is proposed. When combined with a delayed and slightly mismatched receiver, the decoding allows a smaller M without significant loss in BER. The second part analyzes the effect of the internal metric calculations on the performance of Forney- and Ungerboeck-based reduced-complexity equalizers of the M-algorithm type for both ISI and multiple-input multiple-output (MIMO) channels. Even though the final output of a full-complexity equalizer is identical for both models, the internal metric calculations are in general different. Hence, suboptimum methods need not produce the same final output. Additionally, new models working in between the two extremes are proposed and evaluated. Note that the choice of observation model does not impact the detection complexity as the underlying algorithm is unaltered. The last part of the thesis is devoted to a different complexity reducing approach. Optimal channel shortening detectors for linear channels are optimized from an information theoretical perspective. The achievable information rates of the shortened models as well as closed form expressions for all components of the optimal detector of the class are derived. The framework used in this thesis is more general than what has been previously used within the area

Distributed Quasi-Orthogonal Space-Time coding in wireless cooperative relay networks

Cooperative diversity provides a new paradigm in robust wireless re- lay networks that leverages Space-Time (ST) processing techniques to combat the effects of fading. Distributing the encoding over multiple relays that potentially observe uncorrelated channels to a destination terminal has demonstrated promising results in extending range, data- rates and transmit power utilization. Specifically, Space Time Block Codes (STBCs) based on orthogonal designs have proven extremely popular at exploiting spatial diversity through simple distributed pro- cessing without channel knowledge at the relaying terminals. This thesis aims at extending further the extensive design and analysis in relay networks based on orthogonal designs in the context of Quasi- Orthogonal Space Time Block Codes (QOSTBCs). The characterization of Quasi-Orthogonal MIMO channels for cooper- ative networks is performed under Ergodic and Non-Ergodic channel conditions. Specific to cooperative diversity, the sub-channels are as- sumed to observe different shadowing conditions as opposed to the traditional co-located communication system. Under Ergodic chan- nel assumptions novel closed-form solutions for cooperative channel capacity under the constraint of distributed-QOSTBC processing are presented. This analysis is extended to yield closed-form approx- imate expressions and their utility is verified through simulations. The effective use of partial feedback to orthogonalize the QOSTBC is examined and significant gains under specific channel conditions are demonstrated. Distributed systems cooperating over the network introduce chal- lenges in synchronization. Without extensive network management it is difficult to synchronize all the nodes participating in the relaying between source and destination terminals. Based on QOSTBC tech- niques simple encoding strategies are introduced that provide compa- rable throughput to schemes under synchronous conditions with neg- ligible overhead in processing throughout the protocol. Both mutli- carrier and single-carrier schemes are developed to enable the flexi- bility to limit Peak-to-Average-Power-Ratio (PAPR) and reduce the Radio Frequency (RF) requirements of the relaying terminals. The insights gained in asynchronous design in flat-fading cooperative channels are then extended to broadband networks over frequency- selective channels where the novel application of QOSTBCs are used in distributed-Space-Time-Frequency (STF) coding. Specifically, cod- ing schemes are presented that extract both spatial and mutli-path diversity offered by the cooperative Multiple-Input Multiple-Output (MIMO) channel. To provide maximum flexibility the proposed schemes are adapted to facilitate both Decode-and-Forward (DF) and Amplify- and-Forward (AF) relaying. In-depth Pairwise-Error-Probability (PEP) analysis provides distinct design specifications which tailor the distributed- STF code to maximize the diversity and coding gain offered under the DF and AF protocols. Numerical simulation are used extensively to confirm the validity of the proposed cooperative schemes. The analytical and numerical re- sults demonstrate the effective use of QOSTBC over orthogonal tech- niques in a wide range of channel conditions

Rethinking Erasure Codes for Cloud File Systems: Minimizing I/O for Recovery and Degraded Reads,”

Abstract To reduce storage overhead, cloud file systems are transitioning from replication to erasure codes. This process has revealed new dimensions on which to evaluate the performance of different coding schemes: the amount of data used in recovery and when performing degraded reads. We present an algorithm that finds the optimal number of codeword symbols needed for recovery for any XOR-based erasure code and produces recovery schedules that use a minimum amount of data. We differentiate popular erasure codes based on this criterion and demonstrate that the differences improve I/O performance in practice for the large block sizes used in cloud file systems. Several cloud systems [Ford10,Calder11] have adopted Reed-Solomon (RS) codes, because of their generality and their ability to tolerate larger numbers of failures. We define a new class of rotated ReedSolomon codes that perform degraded reads more efficiently than all known codes, but otherwise inherit the reliability and performance properties of Reed-Solomon codes. The online home for this paper may be found at: http://web.eecs.utk.edu/~plank/plank/papers/ FAST-2012 Abstract To reduce storage overhead, cloud file systems are transitioning from replication to erasure codes. This process has revealed new dimensions on which to evaluate the performance of different coding schemes: the amount of data used in recovery and when performing degraded reads. We present an algorithm that finds the optimal number of codeword symbols needed for recovery for any XOR-based erasure code and produces recovery schedules that use a minimum amount of data. We differentiate popular erasure codes based on this criterion and demonstrate that the differences improve I/O performance in practice for the large block sizes used in cloud file systems. Several cloud system