Impact of 4D channel distribution on the achievable rates in coherent optical communication experiments

We experimentally investigate mutual information and generalized mutual information for coherent optical transmission systems. The impact of the assumed channel distribution on the achievable rate is investigated for distributions in up to four dimensions. Single channel and wavelength division multiplexing (WDM) transmission over transmission links with and without inline dispersion compensation are studied. We show that for conventional WDM systems without inline dispersion compensation, a circularly symmetric complex Gaussian distribution is a good approximation of the channel. For other channels, such as with inline dispersion compensation, this is no longer true and gains in the achievable information rate are obtained by considering more sophisticated four-dimensional (4D) distributions. We also show that for nonlinear channels, gains in the achievable information rate can also be achieved by estimating the mean values of the received constellation in four dimensions. The highest gain for such channels is seen for a 4D correlated Gaussian distribution

A Simple Approximation for the Bit-Interleaved Coded Modulation Capacity

The generalized mutual information (GMI) is an achievable rate for bit-interleaved coded modulation (BICM) and is highly dependent on the binary labeling of the constellation. The BICM-GMI, sometimes called the BICM capacity, can be evaluated numerically. This approach, however, becomes impractical when the number of constellation points and/or the constellation dimensionality grows, or when many different labelings are considered. A simple approximation for the BICM-GMI based on the area theorem of the demapper's extrinsic information transfer (EXIT) function is proposed. Numerical results show the proposed approximation gives good estimates of the BICM-GMI for labelings with close to linear EXIT functions, which includes labelings of common interest, such as the natural binary code, binary reflected Gray code, etc. This approximation is used to optimize the binary labeling of the 32-APSK constellation defined in the DVB-S2 standard. Gains of approximately 0.15 dB are obtained

The maximum number of minimal codewords in an [n,k]−[n,k]-code

Upper and lower bounds are derived for the quantity in the title, which is tabulated for modest values of $n$ and $k.$ An application to graphs with many cycles is given.Comment: 6 pp. Submitte

An Interactive Multi-Criteria Decision Model for Reservoir Management: The Shellmouth Reservoir Case

Reservoir management is inherently multi-criterial, since any release decision involves implicit trade-offs between various conflicting objectives. The release decision reflects concerns such as flood protection, hydroelectric power generation, dilution of downstream wastewater and heat effluents, downstream municipal, agricultural and industrial water supply, environmental standards and recreational needs. This paper presents a framework for analysing trade-offs between several decision criteria, and includes the management of heated effluents from downstream thermoelectric power generation in an optimisation model for reservoir management. The model is formulated and analysed in an interactive multi-criteria decision making (MCDM) modelling framework. Rather than providing specific target levels or ad hoc constants in a Goal Programming framework, as proposed elsewhere, our multi-criteria framework suggests a systematic way of evaluating trade-offs by progressive preference assessment. The MCDM model, based on a Tchebycheff metric and a contracted cone approach, is learning-oriented and permits a natural exploration of the decision space while maintaining non-dominated decisions. A detailed case study of the Shellmouth Reservoir in Manitoba, Canada, serves as an illustration of the model

Optimal lattices for sampling

The generalization of the sampling theorem to multidimensional signals is considered, with or without bandwidth constraints. The signal is modeled as a stationary random process and sampled on a lattice. Exact expressions for the mean-square error of the best linear interpolator are given in the frequency domain. Moreover, asymptotic expansions are derived for the average mean-square error when the sampling rate tends to zero and infinity, respectively. This makes it possible to determine the optimal lattices for sampling. In the low-rate sampling case, or equivalently for rough processes, the optimal lattice is the one which solves the packing problem, whereas in the high-rate sampling case, or equivalently for smooth processes, the optimal lattice is the one which solves the dual packing problem. In addition, the best linear interpolation is compared with ideal low-pass filtering (cardinal interpolation)

Corrections to "Replacing the soft-decision FEC limit paradigm in the design of optical communication systems"

Presents corrections to "Replacing the soft-decision FEC limit paradigm in the design of optical communication systems," (Alvarado, A., et al; (J. Lightw. Technol., vol. 33, no. 20, pp. 4338-4352, Oct. 2015)

Four-Dimensional Coded Modulation with Bit-wise Decoders for Future Optical Communications

Coded modulation (CM) is the combination of forward error correction (FEC) and multilevel constellations. Coherent optical communication systems result in a four-dimensional (4D) signal space, which naturally leads to 4D-CM transceivers. A practically attractive design paradigm is to use a bit-wise decoder, where the detection process is (suboptimally) separated into two steps: soft-decision demapping followed by binary decoding. In this paper, bit-wise decoders are studied from an information-theoretic viewpoint. 4D constellations with up to 4096 constellation points are considered. Metrics to predict the post-FEC bit-error rate (BER) of bit-wise decoders are analyzed. The mutual information is shown to fail at predicting the post- FEC BER of bit-wise decoders and the so-called generalized mutual information is shown to be a much more robust metric. For the suboptimal scheme under consideration, it is also shown that constellations that transmit and receive information in each polarization and quadrature independently (e.g., PM-QPSK, PM- 16QAM, and PM-64QAM) outperform the best 4D constellations designed for uncoded transmission. Theoretical gains are as high as 4 dB, which are then validated via numerical simulations of low-density parity check codes

Backward particle message passing

Particle methods are an established way to represent messages and perform message passing in factor graphs. Despite their common use, there are several cases for which messages are hard to compute, even in linear models. Building on results from Gaussian message passing, we demonstrate how backward particle-based messages can be computed and describe a practical application in the context of fiber-optical communications

The role of multiplier bounds in fuzzy data envelopment analysis

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The non-Archimedean epsilon ε is commonly considered as a lower bound for the dual input weights and output weights in multiplier data envelopment analysis (DEA) models. The amount of ε can be effectively used to differentiate between strongly and weakly efficient decision making units (DMUs). The problem of weak dominance particularly occurs when the reference set is fully or partially defined in terms of fuzzy numbers. In this paper, we propose a new four-step fuzzy DEA method to re-shape weakly efficient frontiers along with revisiting the efficiency score of DMUs in terms of perturbing the weakly efficient frontier. This approach eliminates the non-zero slacks in fuzzy DEA while keeping the strongly efficient frontiers unaltered. In comparing our proposed algorithm to an existing method in the recent literature we show three important flaws in their approach that our method addresses. Finally, we present a numerical example in banking with a combination of crisp and fuzzy data to illustrate the efficacy and advantages of the proposed approach