The adoption of aggressive frequency reuse schemes along with interference management techniques has become the leading paradigm in satellite communications to increase the spectral efficiency. In general terms, one cannot rely on precoding techniques in the absence of channel phase information. Nevertheless, the availability of channel magnitude information, makes it possible to explore power-based separation of superimposed signals. In this paper, rate splitting (RS) ideas are exploited, whereby the separation of messages into private and public parts serves to improve the performance of successive cancellation decoding (SCD). Numerical results reveal that in some pertinent system scenarios, the proposed schemes achieve a larger rate region than that of orthogonal schemes that do not exploit the interference and other strategies that either do not allow beam cooperation or do not apply RS.
This paper presents a joint typicality framework for encoding and decoding nested linear codes in multiuser networks. This framework provides a new perspective on compute-forward within the context of discrete memoryless networks. In particular, it establishes an achievable rate region for computing a linear combination over a discrete memoryless multiple-access channel (MAC). When specialized to the Gaussian MAC, this rate region recovers and improves upon the lattice-based compute-forward rate region of Nazer and Gastpar, thus providing a unified approach for discrete memoryless and Gaussian networks. Furthermore, our framework provides some valuable insights on establishing the optimal decoding rate region for compute-forward by considering joint decoders, progressing beyond most previous works that consider successive cancellation decoding. Specifically, this work establishes an achievable rate region for simultaneously decoding two linear combinations of nested linear codewords from K senders. Index Terms Linear codes, joint decoding, compute-forward, multiple-access channel, relay networks I. INTRODUCTION In network information theory, random i.i.d. ensembles serve as the foundation for the vast majority of coding theorems and analytical tools. As elegantly demonstrated by the textbook of El Gamal and Kim [1], the core results of this theory can be unified via a few powerful packing and covering lemmas. However, starting from the many-help-one source coding example of Körner and Marton [2], it has been well-known that there are coding theorems that seem to require random linear ensembles, as opposed to random i.i.d. ensembles. Recent efforts have demonstrated that linear and lattice codes can yield new achievable rates for relay networks [3]-[9],
Abstract-Inspired by the compute-and-forward scheme from Nazer and Gastpar, a novel multiple-access scheme introduced by Zhu and Gastpar makes use of nested lattice codes and sequential decoding of linear combinations of codewords to recover the individual messages. This strategy, coined computeforward multiple access (CFMA), provably achieves points on the dominant face of the multiple-access capacity region while circumventing the need of time sharing or rate splitting. For a two-user multiple-access channel (MAC), we propose a practical procedure to design suitable codes from off-the-shelf LDPC codes and present a sequential belief propagation decoder with complexity comparable with that of point-to-point decoders. We demonstrate the potential of our strategy by comparing several numerical evaluations with theoretical limits.
Abstract-Recent work has employed joint typicality encoding and decoding of nested linear code ensembles to generalize the compute-forward strategy to discrete memoryless multiple-access channels (MACs). An appealing feature of these nested linear code ensembles is that the coding strategies and error probability bounds are conceptually similar to classical techniques for random i.i.d. code ensembles. In this paper, we consider the problem of recovering K linearly independent combinations over a K-user MAC, i.e., recovering the messages in their entirety via nested linear codes. While the MAC rate region is wellunderstood for random i.i.d. code ensembles, new techniques are needed to handle the statistical dependencies between competing codeword K-tuples that occur in nested linear code ensembles.
This paper investigates a novel technique to deal with the interference in the forward link of multibeam satellite systems when aggressive frequency reuse schemes are employed. Taking into account only magnitude information about the forward channel, the gateway judiciously splits the messages to be transmitted into private and public parts. At the receive terminals, partial cancellation of the public messages is applied prior to private message detection. The practical significance of the absence of channel phase information is stressed and complemented by some additional insights on the implementation. Our numerical results show that, in terms of average total throughput, this technique combined with a 2-colour frequency reuse scheme can outperform a classic orthogonal system with a conservative 4-colour frequency reuse scheme, despite the additional co-channel interference.
Most performance measures of pilot-assisted multiple-input multiple-output (MIMO) systems are functions that depend on both the linear precoding filter and the pilot sequence. A framework for the optimization of these two parameters is proposed, based on a matrix-valued generalization of the concept of effective signal-to-noise ratio (SNR) introduced in a famous work by Hassibi and Hochwald. The framework applies to a wide class of utility functions of said effective SNR matrix, most notably a well-known mutual information expression for Gaussian inputs, an upper bound on the minimum mean-square error (MMSE), as well as approximations thereof. The approach consists in decomposing the joint optimization problem into three subproblems: first, we describe how to reformulate the optimization of the linear precoder subject to a fixed pilot sequence as a convex problem. Second, we do likewise for the optimization of the pilot sequence subject to a fixed precoder. Third, we describe how to generate pairs of precoders and pilot sequences that are Pareto optimal in the sense that they attain the Pareto boundary of the set of feasible effective SNR matrices. By combining these three optimization problems into an iteration, we obtain an algorithm which allows to compute jointly optimal pairs of precoders and pilot sequences with respect to some generic utility function of the effective SNR.Comment: 32 pages, 9 figures, submitted to IEEE Transactions on Information Theor
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