Blind Estimation of Multiple Carrier Frequency Offsets

TL;DR

This paper introduces a novel blind estimation method for multiple carrier frequency offsets in distributed antenna systems, transforming the problem into multiple single CFO estimations using a MIMO framework.

Contribution

It proposes a new approach that leverages polyphase components and blind MIMO techniques to estimate multiple CFOs without prior knowledge.

Findings

Estimator performance approaches the Cramer-Rao Lower bound with large samples.

The method effectively transforms multiple CFO estimation into independent single CFO problems.

The approach enhances symbol recovery accuracy in distributed antenna systems.

Abstract

Multiple carrier-frequency offsets (CFO) arise in a distributed antenna system, where data are transmitted simultaneously from multiple antennas. In such systems the received signal contains multiple CFOs due to mismatch between the local oscillators of transmitters and receiver. This results in a time-varying rotation of the data constellation, which needs to be compensated for at the receiver before symbol recovery. This paper proposes a new approach for blind CFO estimation and symbol recovery. The received base-band signal is over-sampled, and its polyphase components are used to formulate a virtual Multiple-Input Multiple-Output (MIMO) problem. By applying blind MIMO system estimation techniques, the system response is estimated and used to subsequently transform the multiple CFOs estimation problem into many independent single CFO estimation problems. Furthermore, an initial estimate of the CFO is obtained from the phase of the MIMO system response. The Cramer-Rao Lower bound is also derived, and the large sample performance of the proposed estimator is compared to the bound.