Capacity Approximations for Gaussian Relay Networks
From MaRDI portal
Publication:2977271
DOI10.1109/TIT.2015.2457904zbMATH Open1359.94960arXiv1407.3841OpenAlexW2963410385MaRDI QIDQ2977271
Author name not available (Why is that?)
Publication date: 28 April 2017
Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)
Abstract: Consider a Gaussian relay network where a source node communicates to a destination node with the help of several layers of relays. Recent work has shown that compress-and-forward based strategies can achieve the capacity of this network within an additive gap. Here, the relays quantize their received signals at the noise level and map them to random Gaussian codebooks. The resultant gap to capacity is independent of the SNRs of the channels in the network and the topology but is linear in the total number of nodes. In this paper, we provide an improved lower bound on the rate achieved by compress-and-forward based strategies (noisy network coding in particular) in arbitrary Gaussian relay networks, whose gap to capacity depends on the network not only through the total number of nodes but also through the degrees of freedom of the min cut of the network. We illustrate that for many networks, this refined lower bound can lead to a better approximation of the capacity. In particular, we demonstrate that it leads to a logarithmic rather than linear capacity gap in the total number of nodes for certain classes of layered networks. The improvement comes from quantizing the received signals of the relays at a resolution decreasing with the total number of nodes in the network. This suggests that the rule-of-thumb in literature of quantizing the received signals at the noise level can be highly suboptimal.
Full work available at URL: https://arxiv.org/abs/1407.3841
Related Items (7)
Approximate Capacity of a Class of Gaussian Interference-Relay Networks ⋮ Distortion Exponents of Two-Way Relay Networks ⋮ Ergodic Channel Capacity of an Amplify-and-Forward Relay System at Low SNR in a Generic Noise Environment ⋮ Approximately Achieving Gaussian Relay Network Capacity With Lattice-Based QMF Codes ⋮ Efficient Capacity Computation and Power Optimization for Relay Networks ⋮ The Approximate Capacity of the Gaussian $N$-Relay Diamond Network ⋮ Cooperative Strategies and Capacity Theorems for Relay Networks
This page was built for publication: Capacity Approximations for Gaussian Relay Networks
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q2977271)
