69,130 research outputs found

    New approaches to reduced-complexity decoding

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    We examine new approaches to the problem of decoding general linear codes under the strategies of full or bounded hard decoding and bounded soft decoding. The objective is to derive enhanced new algorithms that take advantage of the major features of existing algorithms to reduce decoding complexity. We derive a wide range of results on the complexity of many existing algorithms. We suggest a new algorithm for cyclic codes, and show how it exploits all the main features of the existing algorithms. Finally, we propose a new approach to the problem of bounded soft decoding, and show that its asymptotic complexity is significantly lower than that of any other currently known general algorithm. In addition, we give a characterization of the weight distribution of the average linear code and thus show that the Gilbert-Varshamov bound is tight for virtually all linear codes over any symbol field.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29034/1/0000066.pd

    Reduced Complexity Sphere Decoding

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    In Multiple-Input Multiple-Output (MIMO) systems, Sphere Decoding (SD) can achieve performance equivalent to full search Maximum Likelihood (ML) decoding, with reduced complexity. Several researchers reported techniques that reduce the complexity of SD further. In this paper, a new technique is introduced which decreases the computational complexity of SD substantially, without sacrificing performance. The reduction is accomplished by deconstructing the decoding metric to decrease the number of computations and exploiting the structure of a lattice representation. Furthermore, an application of SD, employing a proposed smart implementation with very low computational complexity is introduced. This application calculates the soft bit metrics of a bit-interleaved convolutional-coded MIMO system in an efficient manner. Based on the reduced complexity SD, the proposed smart implementation employs the initial radius acquired by Zero-Forcing Decision Feedback Equalization (ZF-DFE) which ensures no empty spheres. Other than that, a technique of a particular data structure is also incorporated to efficiently reduce the number of executions carried out by SD. Simulation results show that these approaches achieve substantial gains in terms of the computational complexity for both uncoded and coded MIMO systems.Comment: accepted to Journal. arXiv admin note: substantial text overlap with arXiv:1009.351

    Approximate MIMO Iterative Processing with Adjustable Complexity Requirements

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    Targeting always the best achievable bit error rate (BER) performance in iterative receivers operating over multiple-input multiple-output (MIMO) channels may result in significant waste of resources, especially when the achievable BER is orders of magnitude better than the target performance (e.g., under good channel conditions and at high signal-to-noise ratio (SNR)). In contrast to the typical iterative schemes, a practical iterative decoding framework that approximates the soft-information exchange is proposed which allows reduced complexity sphere and channel decoding, adjustable to the transmission conditions and the required bit error rate. With the proposed approximate soft information exchange the performance of the exact soft information can still be reached with significant complexity gains.Comment: The final version of this paper appears in IEEE Transactions on Vehicular Technolog

    Decoder-in-the-Loop: Genetic Optimization-based LDPC Code Design

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    LDPC code design tools typically rely on asymptotic code behavior and are affected by an unavoidable performance degradation due to model imperfections in the short length regime. We propose an LDPC code design scheme based on an evolutionary algorithm, the Genetic Algorithm (GenAlg), implementing a "decoder-in-the-loop" concept. It inherently takes into consideration the channel, code length and the number of iterations while optimizing the error-rate of the actual decoder hardware architecture. We construct short length LDPC codes (i.e., the parity-check matrix) with error-rate performance comparable to, or even outperforming that of well-designed standardized short length LDPC codes over both AWGN and Rayleigh fading channels. Our proposed algorithm can be used to design LDPC codes with special graph structures (e.g., accumulator-based codes) to facilitate the encoding step, or to satisfy any other practical requirement. Moreover, GenAlg can be used to design LDPC codes with the aim of reducing decoding latency and complexity, leading to coding gains of up to 0.3250.325 dB and 0.80.8 dB at BLER of 10−510^{-5} for both AWGN and Rayleigh fading channels, respectively, when compared to state-of-the-art short LDPC codes. Also, we analyze what can be learned from the resulting codes and, as such, the GenAlg particularly highlights design paradigms of short length LDPC codes (e.g., codes with degree-1 variable nodes obtain very good results).Comment: in IEEE Access, 201
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