For applications in concatenated coding for optical communications systems, we examine soft-demapping of short spherical codes constructed as constant-energy shells of the Cartesian power of pulse amplitude modulation constellations. These are unions of permutation codes having the same average power. We construct a list decoder for permutation codes by adapting Murty’s algorithm, which is then used to determine mutual information curves for these permutation codes. In the process, we discover a straightforward expression for determining the likelihood of large subcodes of permutation codes. We refer to these subcodes, obtained by all possible sign flips of a given permutation codeword, as orbits. We introduce a simple process, which we call orbit demapping with frozen symbols, that allows us to extract soft information from noisy permutation codewords. In a sample communication system with probabilistic amplitude shaping protected by a standard low-density parity-check code that employs short permutation codes, we demonstrate that orbit demapping with frozen symbols provides a gain of about 0.3 dB in signal-to-noise ratio compared to the traditional symbol-by-symbol demapping. By using spherical codes composed of unions of permutation codes, we can increase the input entropy compared to using permutation codes alone. In one scheme, we consider a union of a small number of permutation codes. In this case, orbit demapping with frozen symbols provides about 0.2 dB gain compared to the traditional method. In another scheme, we use all possible permutations to form a spherical code that exhibits a computationally feasible trellis representation. The soft information obtained using the BCJR algorithm outperforms the traditional symbol-by-symbol method by 0.1 dB. Overall, using the spherical codes containing all possible permutation codes of the same average power and the BCJR algorithm, a gain of 0.5 dB is observed compared with the case of using one permutation code with the symbol-by-symbol demapping. Comparison of the achievable information rates of bit-metric decoding verifies the observed gains.

The nondispersive per-sample channel model for the optical fiber channel is considered. Under certain smoothness assumptions, the problem of finding the minimum amount of noise energy that can render two different input points indistinguishable is formulated. This minimum noise energy is then taken as a measure of distance between the points in the input alphabet. Using the machinery of optimal control theory, necessary conditions that describe the minimum-energy noise trajectories are stated as a system of nonlinear differential equations. It is shown how to find the distance between two input points by solving this system of differential equations. The problem of designing signal constellations with the largest minimum distance subject to a peak power constraint is formulated as a clique-finding problem. As an example, a 16-point constellation is designed and compared with conventional quadrature amplitude modulation. A computationally efficient approximation for the proposed distance measure is provided. It is shown how to use this approximation to design large constellations with large minimum distances. Based on the control-theoretic viewpoint of this paper, a new decoding scheme for such nonlinear channels is proposed.

The nondispersive per-sample channel model for the optical fiber channel is considered. Under some smoothness assumptions, the problem of finding the minimum amount of noise energy that can render two different input points indistinguishable is formulated. The necessary conditions for the noise trajectory that has the minimum energy are described as a system of nonlinear differential equations. It is suggested that this model can be generalized to consider dispersion and to design new communication schemes for fiber-optic communication systems.

In a multiway relay channel (MWRC), pairwise transmission strategy can be used to reduce the computational complexity at the relay and the users without sacrificing the data rate significantly. The performance of such pairwise strategies, however, is affected by the way that the users are paired to transmit. In this paper, we study the effect of pairing on the common rate and sum rate of an MWRC with functional-decode-forward (FDF) relaying strategy where users experience asymmetric channel conditions. To this end, we first develop a graphical model for an MWRC with pairwise transmission strategy. Using this model, we then find the maximum achievable common rate and sum rate as well as the user pairings that achieve these rates. This marks the ultimate performance of FDF relaying in an MWRC setup. Further, we show that the rate enhancement achieved through the optimal user pairing becomes less pronounced at higher signal to noise ratios. Using computer simulations, the performance of the optimal pairing is compared with those of other proposed pairings in the literature.

Erasure codes, such as LT and Raptor codes, are designed for the purpose of erasure-resilient distribution of data over computer networks. To achieve a small reception overhead, however, LT and Raptor codes must be used with a large design length$k$, making these codes unsuitable for real-time applications. In this paper, we propose a new class of erasure codes based on Reed–Solomon codes that unlike other Reed–Solomon-based erasure codes are rateless and also, unlike other rateless codes, guarantee zero overhead even for small$k$. Moreover, they have a reasonable computational complexity of coding when$k$is not too large. In fact, a practical implementation of subfield subcodes of Reed-Solomon codes with arbitrarily large block lengths is presented.

In this paper, we study the effect of users' transmission ordering on the common rate and sum rate of pairwise multiway relay channels (MWRCs) with functional-decode-forward strategy. To this end, we first develop a graphical model for the data transmission in a pairwise MWRC. Using this model, we then find the optimal orderings that achieve the maximum common rate and sum rate of the system, respectively. The achieved maximum common/sum rate is also found. Moreover, we show that the performance gap between optimal orderings and a random ordering vanishes when SNR increases. Computer simulations are presented for better illustration of the results.