Optimal Fronthaul Quantization for Cloud Radio Positioning

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Wireless positioning systems that are implemented by means of a cloud radio access network (C-RAN) may provide cost-effective solutions, particularly for indoor localization. In a C-RAN, baseband processing, including localization, is carried out at a centralized control unit (CU) based on quantized baseband signals received from the radio units (RUs) over finite-capacity fronthaul links. In this paper, the problem of maximizing the localization accuracy over fronthaul quantization/compression is formulated by adopting the Cramer-Rao bound (CRB) on the localization accuracy as the performance metric of interest and information-theoretic bounds on the compression rate. The analysis explicitly accounts for the uncertainty of parameters at the CU via a robust, or worst-case, optimization formulation. The proposed algorithm leverages the Charnes-Cooper transformation and difference-of-convex (DC) programming and is validated via numerical results.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2016-04
Language
English
Article Type
Article
Keywords

ALLOCATION; NETWORKS

Citation

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.65, no.4, pp.2763 - 2768

ISSN
0018-9545
DOI
10.1109/TVT.2015.2431491
URI
http://hdl.handle.net/10203/209228
Appears in Collection
EE-Journal Papers(저널논문)
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