JOURNAL ARTICLE

Robust distributed compression for cloud radio access networks

Abstract

This work studies distributed compression for the uplink of a cloud radio access network, where multiple multi-antenna base stations (BSs) communicate with a central unit, also referred to as cloud decoder, via capacity-constrained back-haul links. Distributed source coding strategies are potentially beneficial since the signals received at different BSs are correlated. However, they require each BS to have information about the joint statistics of the received signals across the BSs, and are generally sensitive to uncertainties regarding such information. Motivated by this observation, a robust compression method is proposed to cope with uncertainties on the correlation of the received signals. The problem is formulated using a deterministic worst-case approach, and an algorithm is proposed that achieves a stationary point for the problem. From numerical results, it is observed that the proposed robust compression scheme compensates for a large fraction of the performance loss induced by the imperfect statistical information.

Keywords:
Computer science Distributed source coding Telecommunications link Cloud computing Base station Data compression Computer network Radio access network Coding (social sciences) Real-time computing Robustness (evolution) Decoding methods Algorithm Distributed computing Mathematics Statistics Channel code

Metrics

61
Cited By
6.34
FWCI (Field Weighted Citation Impact)
17
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Wireless Communication Security Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Cooperative Communication and Network Coding
Physical Sciences →  Computer Science →  Computer Networks and Communications
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