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In most wired and wireless systems, carrier tracking is an essential task that allows the receiver to precisely synchronize with the carrier of the incoming signal. Stringent carrier tracking requirements are imposed in systems that are sensitive to carrier mismatches, such as orthogonal frequency division multiplexing (OFDM), digital communication receivers employing high-order constellations, and terrestrial-or satellitebased positioning systems, just to mention a few. In the recent years, even more critical requirements are being imposed due to the emergence of new applications and services that are pushing traditional systems to operate in much more challenging conditions than the ones for which they were originally designed. The presence of severe fading, signal outages, abrupt phase changes and high user dynamics, are currently compromising the validity of well-known and long-established traditional carrier tracking techniques, thus calling for the development of new robust carrier tracking algorithms. In this paper, we provide a detailed survey on the five main strategies that can be adopted to cope with the technical challenges of robust carrier tracking. These strategies range from some basic optimizations of current tracking loops, to the use of Kalman filter-based architectures, or the application of innovative carrier tracking techniques based on particle filters or compressive sensing. We will also review some open-loop techniques, which are widely adopted in burstmode communications receivers, as an alternative and potential candidate solution for robust carrier tracking in harsh conditions.

Robustness of nominal Global Navigation Satellite Systems (GNSS) performance can be enhanced by means of complimentary systems, such as the Long Term Evolution (LTE). Particularly, the LTE standard specifies a dedicated downlink signal for positioning purposes, i.e. the positioning reference signal (PRS). This paper presents the achievable localization accuracy of the PRS signal for different interference LTE scenarios by means of the Crámer-Rao bound (CRB) for time delay estimation, in order to assess the LTE positioning capabilities.

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The Long Term Evolution (LTE) is a mobile communication standard that is receiving significant attention, and especially offers positioning capabilities by specifying a dedicated downlink signal, i.e. the positioning reference signal (PRS). Thus, this technology can improve the location of mobile terminals operating in harsh environments, such as urban or indoor scenarios. This paper presents a study of the impact of the channel on the positioning capabilities of LTE with respect to the signal bandwidth. For that purpose, typical channel models, such as those recommended by the International Telecommunication Union (ITU), are used to obtain timing error distributions by means of the histogram of maximum likelihood estimates. The results obtained represent the worst-case scenario since the applied estimation process does not consider the presence of the multipath channel. The dependency of the timing error distributions with respect to the type of channel model is also analysed.

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This paper focuses on the exploitation of fifth generation (5G) centimetre-wave (cmWave) and millimetre-wave (mmWave) transmissions for high-accuracy positioning, in order to complement the availability of Global Navigation Satellite Systems (GNSS) in harsh environments, such as urban canyons. Our goal is to present a representative methodology to simulate and assess their hybrid positioning capabilities over outdoor urban, suburban and rural scenarios. A novel scenario definition is proposed to integrate the network density of 5G deployments with the visibility masks of GNSS satellites, which helps to generate correlated scenarios of both technologies. Then, a generic and representative modeling of the 5G and GNSS observables is presented for snapshot positioning, which is suitable for standard protocols. The simulations results indicate that GNSS drives the achievable accuracy of its hybridisation with 5G cmWave, because non-line-of-sight (NLoS) conditions can limit the cmWave localization accuracy to around 20 m. The 5G performance is significantly improved with the use of mmWave positioning with dominant line-of-sight (LoS) conditions, which can even achieve sub-meter localization with one or more base stations. Therefore, these results show that NLoS conditions need to be weighted in 5G localization, in order to complement and outperform GNSS positioning over urban environments.