Time-varying phase noise and channel estimation in MIMO systems

Performance of high speed communication systems is negatively affected by oscillator phase noise (PN). In this paper joint estimation of channel gains and Wiener PN in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail. In order to reduce overhead, a low complexity data-aided least-squares (LS) estimator for jointly obtaining the channel gains and PN parameters is derived. In order to track PN processes over a frame, a new decision-directed extended Kalman filter (EKF) is proposed. Numerical results show that the proposed LS and EKF based PN estimator performances are close to the CRLB and simulation results indicate that by employing the proposed estimators the bit-error rate (BER) performance of a MIMO system can be significantly improved in the presence of PN

Synchronization in Cooperative Communication Systems

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 error (MMSE) compensation and maximum likelihood (ML) decoding algorithm are proposed for the destination receiver. It has been evidenced by numerical simulations that application of the proposed estimation and compensation methods in conjunction with space-time block codes achieve full diversity gain in the presence of channel and synchronization impairments. Considering training-based transmission scheme, this thesis also addresses the design of optimal training sequences for efficient and joint estimation of MTOs and multiple channel parameters. In the second part of the thesis, the problem of joint estimation and compensation of multiple impairments in non-data-aided (NDA) DF cooperative systems is addressed. The use of blind source separation is proposed at the destination to convert the difficult problem of jointly estimating the multiple synchronization parameters in the relaying phase into more tractable sub-problems of estimating many individual timing offsets and carrier frequency offsets for the independent relays. Next, a criteria for best relay selection is proposed at the destination. Applying the relay selection algorithm, simulation results demonstrate promising bit-error rate (BER) performance and realise the achievable maximum diversity order at the destination

Analysis and Design of Line of Sight MIMO transmission systems

A cost-effective solution to the problem of guaranteeing backhaul connectivity in mobile cellular networks is the use of point-to-point microwave links in the Q-Band and E-Band. The always increasing rate in mobile data traffic makes these microwave radio links a potential bottleneck in the deployment of high-throughput cellular networks. A fundamental way to characterize the impact of phase noise on the throughput of these systems is to study their Shannon capacity. Unfortunately, the capacity of the phase-noise channel is not known in closed-form, even for simple channel models. The effect of phase noise in telecommunication systems is more evident in presence of multiple antennas at transmitter and receiver because of the overlapping of phase noise contribution in receivers. We propose a simulated-based tool to compute a lower bound to channel capacity for SISO and MIMO systems in presence of phase noise with one oscillator shared among the antennas per side and we give a non asymptotic expression of an upper bound to capacity always for SISO and MIMO channels. Finally we present a low complex phase detector based on combination of Phase Locked Loop (PLL) exploiting the decisions made by a turbo decoder. The aim of this work is showing a way to bound the channel capacity for single antenna and multiple antennas channels impaired by phase noise generated by instabilities in oscillators driving all the transceivers, and compare the performance of the proposed phase detector to those theoretical limits

Time-varying phase noise and channel estimation in MIMO systems

Performance of high speed communication systems is negatively affected by oscillator phase noise (PN). In this paper joint estimation of channel gains and Wiener PN in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail. In order to reduce overhead, a low complexity data-aided least-squares (LS) estimator for jointly obtaining the channel gains and PN parameters is derived. In order to track PN processes over a frame, a new decision-directed extended Kalman filter (EKF) is proposed. Numerical results show that the proposed LS and EKF based PN estimator performances are close to the CRLB and simulation results indicate that by employing the proposed estimators the bit-error rate (BER) performance of a MIMO system can be significantly improved in the presence of PN