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.
| Original language | English (US) |
|---|---|
| Article number | 7104164 |
| Pages (from-to) | 2763-2768 |
| Number of pages | 6 |
| Journal | IEEE Transactions on Vehicular Technology |
| Volume | 65 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2016 |
All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Aerospace Engineering
- Computer Networks and Communications
- Electrical and Electronic Engineering
Keywords
- Cloud Radio Access Networks (C-RANs)
- Cramer-Rao bound (CRB)
- localization
- quantization