Conditional maximum likelihood timing recovery: estimators and bounds

This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulation that is systematically applied in the literature for the derivation of non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramér–Rao Bound (CRB ), which is higher (less optimistic) than the modified CRB (MCRB) [which is only reached by decision-directed (DD) methods]. It is shown that the CRB is a lower bound on the asymptotic statistical accuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained bound is not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRB is obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Eg/No.Peer Reviewe

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

Enabling 5G Technologies

The increasing demand for connectivity and broadband wireless access is leading to the fifth generation (5G) of cellular networks. The overall scope of 5G is greater in client width and diversity than in previous generations, requiring substantial changes to network topologies and air interfaces. This divergence from existing network designs is prompting a massive growth in research, with the U.S. government alone investing $400 million in advanced wireless technologies. 5G is projected to enable the connectivity of 20 billion devices by 2020, and dominate such areas as vehicular networking and the Internet of Things. However, many challenges exist to enable large scale deployment and general adoption of the cellular industries. In this dissertation, we propose three new additions to the literature to further the progression 5G development. These additions approach 5G from top down and bottom up perspectives considering interference modeling and physical layer prototyping. Heterogeneous deployments are considered from a purely analytical perspective, modeling co-channel interference between and among both macrocell and femtocell tiers. We further enhance these models with parameterized directional antennas and integrate them into a novel mixed point process study of the network. At the air interface, we examine Software-Defined Radio (SDR) development of physical link level simulations. First, we introduce a new algorithm acceleration framework for MATLAB, enabling real-time and concurrent applications. Extensible beyond SDR alone, this dataflow framework can provide application speedup for stream-based or data dependent processing. Furthermore, using SDRs we develop a localization testbed for dense deployments of 5G smallcells. Providing real-time tracking of targets using foundational direction of arrival estimation techniques, including a new OFDM based correlation implementation

Direction of Arrival Estimation for Radio Positioning: a Hardware Implementation Perspective

Nowadays multiple antenna wireless systems have gained considerable attention due to their capability to increase performance. Advances in theory have introduced several new schemes that rely on multiple antennas and aim to increase data rate, diversity gain, or to provide multiuser capabilities, beamforming and direction finding (DF) features. In this respect, it has been shown that a multiple antenna receiver can be potentially used to perform radio localization by using the direction of arrival (DoA) estimation technique. In this field, the literature is extensive and gathers the results of almost four decades of research activities. Among the most cited techniques that have been developed, we find the so called high-resolution algorithms, such as multiple signal classification (MUSIC), or estimation of signal parameters via rotational invariance (ESPRIT). Theoretical analysis as well as simulation results have demonstrated their excellent performance to the point that they are usually considered as reference for the comparison with other algorithms. However, such a performance is not necessarily obtained in a real system due to the presence of non idealities. These can be divided into two categories: the impairments due to the antenna array, and the impairments due to the multiple radio frequency (RF) and acquisition front-ends (FEs). The former are strongly influenced by the manufacturing accuracy and, depending on the required DoA resolution, have to be taken into account. Several works address these issues in the literature. The multiple FE non idealities, instead, are usually not considered in the DoA estimation literature, even if they can have a detrimental effect on the performance. This has motivated the research work in this thesis that addresses the problem of DoA estimation from a practical implementation perspective, emphasizing the impact of the hardware impairments on the final performance. This work is substantiated by measurements done on a state-of-the-art hardware platform that have pointed out the presence of non idealities such as DC offsets, phase noise (PN), carrier frequency offsets (CFOs), and phase offsets (POs) among receivers. Particularly, the hardware platform will be herein described and examined to understand what non idealities can affect the DoA estimation performance. This analysis will bring to identify which features a DF system should have to reach certain performance. Another important issue is the number of antenna elements. In fact, it is usually limited by practical considerations, such as size, costs, and also complexity. However, the most cited DoA estimation algorithms need a high number of antenna elements, and this does not yield them suitable to be implemented in a real system. Motivated by this consideration, the final part of this work will describe a novel DoA estimation algorithm that can be used when multipath propagation occurs. This algorithm does not need a high number of antenna elements to be implemented, and it shows good performance despite its low implementation/computational complexity

Radio Channel Prediction Based on Parametric Modeling

Long range channel prediction is a crucial technology for future wireless communications. The prediction of Rayleigh fading channels is studied in the frame of parametric modeling in this thesis. Suggested by the Jakes model for Rayleigh fading channels, deterministic sinusoidal models were adopted for long range channel prediction in early works. In this thesis, a number of new channel predictors based on stochastic sinusoidal modeling are proposed. They are termed conditional and unconditional LMMSE predictors respectively. Given frequency estimates, the amplitudes of the sinusoids are modeled as Gaussian random variables in the conditional LMMSE predictors, and both the amplitudes and frequency estimates are modeled as Gaussian random variables in the unconditional LMMSE predictors. It was observed that a part of the channels cannot be described by the periodic sinusoidal bases, both in simulations and measured channels. To pick up this un-modeled residual signal, an adjusted conditional LMMSE predictor and a Joint LS predictor are proposed. Motivated by the analysis of measured channels and recently published physics based scattering SISO and MIMO channel models, a new approach for channel prediction based on non-stationary Multi-Component Polynomial Phase Signal (MC-PPS) is further proposed. The so-called LS MC-PPS predictor models the amplitudes of the PPS components as constants. In the case of MC-PPS with time-varying amplitudes, an adaptive channel predictor using the Kalman filter is suggested, where the time-varying amplitudes are modeled as auto-regressive processes. An iterative detection and estimation method of the number of PPS components and the orders of polynomial phases is also proposed. The parameter estimation is based on the Nonlinear LS (NLLS) and the Nonlinear Instantaneous LS (NILS) criteria, corresponding to the cases of constant and time-varying amplitudes, respectively. The performance of the proposed channel predictors is evaluated using both synthetic signals and measured channels. High order polynomial phase parameters are observed in both urban and suburban environments. It is observed that the channel predictors based on the non-stationary MC-PPS models outperform the other predictors in Monte Carlo simulations and examples of measured urban and suburban channels

Algorithms for channel impairment mitigation in broadband wireless communications

Ph.DDOCTOR OF PHILOSOPH