1,276 research outputs found

    Improved Decoding of Interleaved AG-Codes

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    We analyze a generalization of a recent algorithm of Bleichenbacher et al.~for decoding interleaved codes on the QQ-ary symmetric channel for large QQ. We will show that for any mm and any ϵ\epsilon the new algorithms can decode up to a fraction of at least βmβm+1(1R2Q1/2m)ϵ\frac{\beta m}{\beta m+1}(1-R-2Q^{- 1/2m})-\epsilon errors (where β=ln(qm1)ln(qm)\beta = \frac{\ln(q^m - 1)}{\ln(q^m)}), and that the error probability of the decoder is upper bounded by O(1/qϵn)O(1/q^{\epsilon n}), where nn is the block-length. The codes we construct do not have a- priori any bound on their length

    Multiple Beamforming with Perfect Coding

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    Perfect Space-Time Block Codes (PSTBCs) achieve full diversity, full rate, nonvanishing constant minimum determinant, uniform average transmitted energy per antenna, and good shaping. However, the high decoding complexity is a critical issue for practice. When the Channel State Information (CSI) is available at both the transmitter and the receiver, Singular Value Decomposition (SVD) is commonly applied for a Multiple-Input Multiple-Output (MIMO) system to enhance the throughput or the performance. In this paper, two novel techniques, Perfect Coded Multiple Beamforming (PCMB) and Bit-Interleaved Coded Multiple Beamforming with Perfect Coding (BICMB-PC), are proposed, employing both PSTBCs and SVD with and without channel coding, respectively. With CSI at the transmitter (CSIT), the decoding complexity of PCMB is substantially reduced compared to a MIMO system employing PSTBC, providing a new prospect of CSIT. Especially, because of the special property of the generation matrices, PCMB provides much lower decoding complexity than the state-of-the-art SVD-based uncoded technique in dimensions 2 and 4. Similarly, the decoding complexity of BICMB-PC is much lower than the state-of-the-art SVD-based coded technique in these two dimensions, and the complexity gain is greater than the uncoded case. Moreover, these aforementioned complexity reductions are achieved with only negligible or modest loss in performance.Comment: accepted to journa

    Self-concatenated code design and its application in power-efficient cooperative communications

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    In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions

    On BICM receivers for TCM transmission

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    Recent results have shown that the performance of bit-interleaved coded modulation (BICM) using convolutional codes in nonfading channels can be significantly improved when the interleaver takes a trivial form (BICM-T), i.e., when it does not interleave the bits at all. In this paper, we give a formal explanation for these results and show that BICM-T is in fact the combination of a TCM transmitter and a BICM receiver. To predict the performance of BICM-T, a new type of distance spectrum for convolutional codes is introduced, analytical bounds based on this spectrum are developed, and asymptotic approximations are also presented. It is shown that the minimum distance of the code is not the relevant optimization criterion for BICM-T. Optimal convolutional codes for different constrain lengths are tabulated and asymptotic gains of about 2 dB are obtained. These gains are found to be the same as those obtained by Ungerboeck's one-dimensional trellis coded modulation (1D-TCM), and therefore, in nonfading channels, BICM-T is shown to be asymptotically as good as 1D-TCM.Comment: Submitted to the IEEE Transactions on Communication

    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
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