Synchronization in Cooperative Communication Systems

Abstract

Cooperative communication is an attractive solution to combat fading in wireless communication systems. Achieving synchronization is a fundamental requirement in such systems. In cooperative networks, multiple single antenna relay terminals receive and cooperatively transmit the source information to the destination. The multiple distributed nodes, each with its own local oscillator, give rise to multiple timing offsets (MTOs) and multiple carrier frequency offsets (MCFOs). Particularly, the received signal at the destination is the superposition of the relays’ transmitted signals that are attenuated differently, are no longer aligned with each other in time, and experience phase rotations at different rates due to different channels, MTOs, and MCFOs, respectively. The loss of synchronization due to the presence of MTOs and MCFOs sets up the recovery of the source signal at the destination to be a very challenging task. This thesis seeks to develop estimation and compensation algorithms that can achieve synchronization and enable cooperative communication for both decode-and-forward (DF) and amplify-and-forward (AF) relaying networks in the presence of multiple impairments, i.e., unknown channel gains, MTOs, and MCFOs. In the first part of the thesis, a training-based transmission scheme is considered, in which training symbols are transmitted first in order to assist the joint estimation of multiple impairments at the destination node in DF and AF cooperative relaying networks. New transceiver structure at the relays and novel receiver design at the destination are proposed which allow for the decoding of the received signal in the presence of unknown channel gains, MTOs, and MCFOs. Different estimation algorithms, e.g., least squares (LS), expectation conditional maximization (ECM), space-alternating generalized expectation-maximization (SAGE), and differential evolution (DE), are proposed and analyzed for joint estimation of multiple impairments. In order to compare the estimation accuracy of the proposed estimators, Cramer-Rao lower bounds (CRLBs) for the multi-parameter estimation are derived. Next, in order to detect the signal from multiple relays in the presence of multiple impairments, novel optimal and sub-optimal minimum mean-square er-