Optimal fronthaul quantization for cloud radio positioning

Document Type

Article

Publication Date

4-1-2016

Abstract

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 Cramér-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.

Identifier

84964614193 (Scopus)

Publication Title

IEEE Transactions on Vehicular Technology

External Full Text Location

https://doi.org/10.1109/TVT.2015.2431491

ISSN

00189545

First Page

2763

Last Page

2768

Issue

4

Volume

65

Grant

B0101-15-1372

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