18 research outputs found

    On continuous-time white phase noise channels

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    A continuous-time model for the additive white Gaussian noise (AWGN) channel in the presence of white (memoryless) phase noise is proposed and discussed. It is shown that for linear modulation the output of the baud-sampled filter matched to the shaping waveform represents a sufficient statistic. The analysis shows that the phase noise channel has the same information rate as an AWGN channel but with a penalty on the average signal-to-noise ratio, the amount of penalty depending on the phase noise statistic. © 2014 IEEE

    Reference transmission and receiver optimization for coherent optical communication systems

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    Includes bibliographical references (p. 13).Supported by NSF. NSF/8802991-NCR Supported by ARO. DAAL03-86-K-0171Murat AzizogĂŚlu, Pierre A. Humblet

    Multi-sample Receivers Increase Information Rates for Wiener Phase Noise Channels

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    A waveform channel is considered where the transmitted signal is corrupted by Wiener phase noise and additive white Gaussian noise (AWGN). A discrete-time channel model is introduced that is based on a multi-sample receiver. Tight lower bounds on the information rates achieved by the multi-sample receiver are computed by means of numerical simulations. The results show that oversampling at the receiver is beneficial for both strong and weak phase noise at high signal-to-noise ratios. The results are compared with results obtained when using other discrete-time models.Comment: Submitted to Globecom 201

    Performance of on-off modulated lightwave signals with phase

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    Caption title.Includes bibliographical references (leaves [8]-[9]).Research supported by the National Science Foundation. NSF/8802991-NCR Research supported by the U.S. Army Research Office. DAAL03-86-K-0171Murat AzizogĂŚlu, Pierre A. Humblet

    Reference transmission schemes for phase noise immunity

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    Caption title.Includes bibliographical references (p. 22-23).Supported by the NSF. NCR-8802991 NCR-9206379 Supported by DARPA. F19628-90-C-002 Supported by the ARO. DAAL03-92-G-0115Murat AzizoÄlu, Pierre A. Humblet

    A Belief Propagation Based Framework for Soft Multiple-Symbol Differential Detection

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    Soft noncoherent detection, which relies on calculating the \textit{a posteriori} probabilities (APPs) of the bits transmitted with no channel estimation, is imperative for achieving excellent detection performance in high-dimensional wireless communications. In this paper, a high-performance belief propagation (BP)-based soft multiple-symbol differential detection (MSDD) framework, dubbed BP-MSDD, is proposed with its illustrative application in differential space-time block-code (DSTBC)-aided ultra-wideband impulse radio (UWB-IR) systems. Firstly, we revisit the signal sampling with the aid of a trellis structure and decompose the trellis into multiple subtrellises. Furthermore, we derive an APP calculation algorithm, in which the forward-and-backward message passing mechanism of BP operates on the subtrellises. The proposed BP-MSDD is capable of significantly outperforming the conventional hard-decision MSDDs. However, the computational complexity of the BP-MSDD increases exponentially with the number of MSDD trellis states. To circumvent this excessive complexity for practical implementations, we reformulate the BP-MSDD, and additionally propose a Viterbi algorithm (VA)-based hard-decision MSDD (VA-HMSDD) and a VA-based soft-decision MSDD (VA-SMSDD). Moreover, both the proposed BP-MSDD and VA-SMSDD can be exploited in conjunction with soft channel decoding to obtain powerful iterative detection and decoding based receivers. Simulation results demonstrate the effectiveness of the proposed algorithms in DSTBC-aided UWB-IR systems.Comment: 14 pages, 12 figures, 3 tables, accepted to appear on IEEE Transactions on Wireless Communications, Aug. 201

    Calculation of Mutual Information for Partially Coherent Gaussian Channels with Applications to Fiber Optics

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    The mutual information between a complex-valued channel input and its complex-valued output is decomposed into four parts based on polar coordinates: an amplitude term, a phase term, and two mixed terms. Numerical results for the additive white Gaussian noise (AWGN) channel with various inputs show that, at high signal-to-noise ratio (SNR), the amplitude and phase terms dominate the mixed terms. For the AWGN channel with a Gaussian input, analytical expressions are derived for high SNR. The decomposition method is applied to partially coherent channels and a property of such channels called "spectral loss" is developed. Spectral loss occurs in nonlinear fiber-optic channels and it may be one effect that needs to be taken into account to explain the behavior of the capacity of nonlinear fiber-optic channels presented in recent studies.Comment: 30 pages, 9 figures, accepted for publication in IEEE Transactions on Information Theor
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