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This paper uses a case study of a tail-biting convolutional code (with successful decoding indicated by the reliability output Viterbi algorithm) to present an information density approach for analyzing and optimizing the throughput of systems using incremental redundancy controlled by feedback. Polyan-skiy's normal approximation combined with a linear model for the information gap of a rate-compatible...
Particle Swarm Optimization (PSO), though being originally introduced for continuous search spaces, has been increasingly applied to combinatorial optimization problems. In particular, we focus on the PSO applications to permutation problems. As far as we know, the most popular PSO variants that produce permutation solutions are those based on random key techniques. In this paper, after highlighting...
In this paper a robust encoding scheme is proposed to improve the visual quality of HEVC decoded video when intra frames are lost along the streaming path. For this purpose, the encoding process includes frame loss simulation and subsequent error concealment, to find the most efficient method that should be used by a decoder to recover lost intra frames. In this novel scheme, each image is divided...
Network coding-based caching at base stations (BSs) is a promising caching approach to support massive content delivery over wireless networks. However, existing network coding-based caching designs do not fully explore and exploit the potential advantages. In this paper, we consider the analysis and optimization of a random linear network coding-based caching design in large-scale successive interference...
In this paper, we present a low-density parity-check coded modulation approach addressing orthogonal modulations with moderate order (between 8 and 32) over the additive white Gaussian noise channel. The proposed design is based on a constrained optimization of a non-binary low-density parity-check ensemble degree distribution, where the iterative decoding threshold is optimized via extrinsic information...
In this paper, we propose a design of spatially coupled repeat-accumulate (SC-RA) codes over a three-phase bidirectional relay. The channels between the nodes are assumed binary input additive white Gaussian noise (BIAWGN) channels, while decode-and-forward (DF) relaying is considered at the relay. We present low complexity density evolution analysis for the proposed bidirectional relay code, which...
We characterize time and power allocations to optimize the sum-throughput of a Wireless Powered Communication Network (WPCN) with Non-Orthogonal Multiple Access (NOMA). In our setup, an Energy Rich (ER) source broadcasts wireless energy to several devices, which use it to simultaneously transmit data to an Access Point (AP) on the uplink. Differently from most prior works, in this paper we consider...
Opportunistic routing (OR) is a promising technology to enhance the throughput of wireless networks, which can be implemented in a distributed manner using random linear network coding (RLNC). To reduce the computational cost incurred by RLNC, most previous approaches partition the input packets into disjoint small chunks, apply RLNC within each chunk, and guarantee the decoding reliability by a feedback...
Providing new parallel programming models/abstractions as a set of library functions has the huge advantage that it allows for an relatively easy incremental porting path for legacy HPC applications, in contrast to the huge effort needed when novel concepts are only provided in new programming languages or language extensions. However, performance issues are to be expected with fine granular usage...
In this paper, we propose a new full-duplex relay-assisted cognitive radio system model with an adaptive decoding algorithm at the secondary user, in order to maximize both primary and secondary achievable rates. We consider the uplink transmission and we compare the system's achievable rates obtained with both amplify-and-forward and decode-and-forward relaying in the single-carrier case. Then, we...
This paper deals with the recently introduced class of Non-Surjective Finite Alphabet Iterative Decoders (NS-FAIDs). First, optimization results for an extended class of regular NS-FAIDs are presented. They reveal different possible trade-offs between decoding performance and hardware implementation efficiency. To validate the promises of optimized NS-FAIDs in terms of hardware implementation benefits,...
Handling constraints is not a trivial task in evolutionary computing. Even if different techniques have been proposed in the literature, very few have considered co-evolution which tends to decompose problems into easier sub-problems. Existing co-evolutionary approaches have been mainly used to separate the decision vector. In this article we propose a different co-evolutionary approach, referred...
This paper introduces a class of specific puncturing patterns, called symmetric puncturing patterns, which can be characterized and generated from the rows of the generator matrix GN. They are first shown to be non-equivalent, then a low-complexity method to generate symmetric puncturing patterns is proposed, which performs a search tree algorithm with limited depth, over the rows of GN. Symmetric...
In this paper, an optimization-based approach to construct spiking networks for the purposes of decoding and control is presented. Specifically, we postulate a simple objective function wherein a network of interacting, primitive spiking units is decoded in order to drive a linear system along a prescribed trajectory. The units are assumed to spike only if doing so will decrease a specified objective...
In this paper, we solve the optimizing problem of designing Low-Density Parity Check codes for two parallel erasure links based on the known SDP approach. We show that our reformulation is suitable for this optimizing problem. Our results show that the optimal rate code design problem is a good way and worth-mentioning tool. One can extend our work to the other area.
Directed graphs encode meaningful dependencies among objects ubiquitously. This paper introduces new and simple representations for labeled directed graphs with the properties of being succinct (space is information-theoretically optimal); in which we avoid exploiting a-priori knowledge on digraph regularity such as triangularity, separability, planarity, symmetry and sparsity. Our results have direct...
Error Correcting Output Coding (ECOC) is a multi-class classification technique in which multiple binary classifiers are trained according to a preset code matrix such that each one learns a separate dichotomy of the classes. While ECOC is one of the best solutions for multi-class problems, one issue which makes it suboptimal is that the training of the base classifiers is done independently of the...
A novel sparse coding framework with unity range codes and the possibility to produce a discriminative dictionary is presented. The framework is, in contrast to many other works, able to handle unsupervised, supervised and semi-supervised settings. Furthermore, codes are constrained to be in unity range, which is beneficial in many scenarios. The paper presents the framework and solvers used to produce...
In this paper, we explore the usage of automated hyper-parameter optimization techniques with scalarization of multiple objectives to find decoder hyper-parameters suitable for a given acoustic and language model for an LVCSR task. We compare manual optimization, random sampling, tree of Parzen estimators, Bayesian Optimization, and genetic algorithm to find a technique that yields better performance...
UnionPay's inter-bank transaction settlement platform (ITSP) generates a huge amount of bankcard transaction data everyday, recording different bankcard activities. In order to unleash the business value of these data, UnionPay has built a customized data warehouse based on Hadoop to manage and query the massive data imported from ITSP. However, the original system suffers from low storage utilization...
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