Generalized Compression Strategy for the Downlink Cloud Radio Access Network
Pratik Patil, Wei Yu

TL;DR
This paper analyzes a generalized compression strategy for the downlink of a cloud radio access network, showing it achieves near-capacity performance under certain fronthaul constraints by using successive encoding techniques.
Contribution
It characterizes an achievable rate region for a generalized compression strategy with Marton's multicoding and multivariate compression, and proves its near-optimality under sum fronthaul constraints.
Findings
Compression strategy achieves within a constant gap of capacity under sum fronthaul constraints.
Successive encoding compression performs nearly as well as joint schemes for the Gaussian C-RAN.
The difference between compression and DDF schemes is negligible under certain constraints.
Abstract
This paper studies the downlink of a cloud radio access network (C-RAN) in which a centralized processor (CP) communicates with mobile users through base stations (BSs) that are connected to the CP via finite-capacity fronthaul links. Information theoretically, the downlink of a C-RAN is modeled as a two-hop broadcast-relay network. Among the various transmission and relaying strategies for such model, this paper focuses on the compression strategy, in which the CP centrally encodes the signals to be broadcasted jointly by the BSs, then compresses and sends these signals to the BSs through the fronthaul links. This paper characterizes an achievable rate region for a generalized compression strategy with Marton's multicoding for broadcasting and multivariate compression for fronthaul transmission. We then compare this rate region with the distributed decode-forward (DDF) scheme, which…
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Taxonomy
TopicsCooperative Communication and Network Coding · Wireless Communication Security Techniques · Advanced MIMO Systems Optimization
