This paper considers channel estimation and system performance for the uplink of a single-cell massive multiple-input multiple-output (MIMO) system. Each receive antenna of the base station (BS) is assumed to be equipped with a pair of onebit analog-to-digital converters (ADCs) to quantize the real and imaginary part of the received signal. We first propose an approach for channel estimation that is applicable for both flat and frequency-selective fading, based on the Bussgang decomposition that reformulates the nonlinear quantizer as a linear function with identical first-and second-order statistics. The resulting channel estimator outperforms previously proposed approaches across all SNRs. We then derive closed-form expressions for the achievable rate in flat fading channels assuming low SNR and a large number of users for the maximal ratio and zero forcing receivers that takes channel estimation error due to both noise and one-bit quantization into account. The closed-form expressions in turn allow us to obtain insight into important system design issues such as optimal resource allocation, maximal sum spectral efficiency, overall energy efficiency, and number of antennas. Numerical results are presented to verify our analytical results and demonstrate the benefit of optimizing system performance accordingly.

Millimeter wave signals and large antenna arrays are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are well-known, their potential advantages for accurate positioning are largely undiscovered. We derive the Cramér-Rao bound (CRB) on position and rotation angle estimation uncertainty from millimeter wave signals from a single transmitter, in the presence of scatterers. We also present a novel two-stage algorithm for position and rotation angle estimation that attains the CRB for average to high signal-to-noise ratio. The algorithm is based on multiple measurement vectors matching pursuit for coarse estimation, followed by a refinement stage based on the space-alternating generalized expectation maximization algorithm. We find that accurate position and rotation angle estimation is possible using signals from a single transmitter, in either lineof-sight, non-line-of-sight, or obstructed-line-of-sight conditions.

Location-aware communication systems are expected to play a pivotal part in the next generation of mobile communication networks. Therefore, there is a need to understand the localization limits in these networks, particularly, using millimeter-wave technology (mmWave). Towards that, we address the uplink and downlink localization limits in terms of 3D position and orientation error bounds for mmWave multipath channels. We also carry out a detailed analysis of the dependence of the bounds on different system parameters. Our key findings indicate that the uplink and downlink behave differently in two distinct ways. First of all, the error bounds have different scaling factors with respect to the number of antennas in the uplink and downlink. Secondly, uplink localization is sensitive to the orientation angle of the user equipment (UE), whereas downlink is not. Moreover, in the considered outdoor scenarios, the non-line-of-sight paths generally improve localization when a line-of-sight path exists. Finally, our numerical results show that mmWave systems are capable of localizing a UE with sub-meter position error, and sub-degree orientation error. communications [7], assisted living applications [8], or to support the communication robustness and effectiveness in different aspects such as resource allocation [9], beamforming [10], [11], and pilot assignment [12]. Therefore, the study of positioning in 5G mmWave systems becomes specially imperative. Due to the use of directional beamforming in mmWave, in addition to the UE position also the UE orientation plays an important role in location-aided systems.Conventionally position information is obtained by GPS, though this has several limitations.Most importantly, GPS suffers from degraded performance in outdoor rich-scattering scenarios and urban canyons, and may fail to provide a position fix for indoor scenarios. Even in good conditions, GPS positioning accuracy ranges between 1-5 meters. To address these limitations, there has been intense research on competing radio-based localization technologies. To understand the fundamental behavior of any technology, the Cramér-Rao lower bound (CRLB)[13] or related bounds can be used. The CRLB provides a lower bound on the variance of an unbiased estimator of a certain parameter. The square-root of the CRLB of the position and the orientation are termed the position error bound (PEB), and the orientation error bound (OEB), respectively. PEB and OEB can be computed indirectly by transforming the bounds of the channel parameters, namely: directions of arrival (DOA), directions of departure (DOD), and time of arrival (TOA). For conventional MIMO systems, the bounds of the 2D channel parameters are derived in [14], based on received digital signals and uniform linear arrays (ULA), while bounds are derived in [15] based on 3D channel matrix with no transmit beamforming. It was found that having more transmit and receive antennas is beneficial for estimating the DOA and DOD. In both [14], [15] beamforming was not considered. The b...

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Abstract-Millimeter wave and massive MIMO are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are wellknown, their potential advantages for accurate positioning are largely undiscovered. We derive sufficient conditions under which transmission from a single mm-wave base station leads to a nonsingular Fisher information matrix associated with the position and orientation of a user terminal equipped with multiple antennas, which is in turn a prerequisite for joint estimation of the position and orientation.

Abstract-This paper addresses the estimation of the code-phase (pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. The signal is received by an antenna array in a scenario with interference and multipath propagation. These two effects are generally the limiting error sources in most high-precision positioning applications. A new estimator of the code-and carrier-phases is derived by using a simplified signal model and the maximum likelihood (ML) principle. The simplified model consists essentially of gathering all signals, except for the direct one, in a component with unknown spatial correlation. The estimator exploits the knowledge of the direction-of-arrival of the direct signal and is much simpler than other estimators derived under more detailed signal models. Moreover, we present an iterative algorithm, that is adequate for a practical implementation and explores an interesting link between the ML estimator and a hybrid beamformer. The mean squared error and bias of the new estimator are computed for a number of scenarios and compared with those of other methods. The presented estimator and the hybrid beamforming outperform the existing techniques of comparable complexity and attains, in many situations, the Cramér-Rao lower bound of the problem at hand.

ccurately determining one's position has been a recurrent problem in history [1]. It even precedes the first deep-sea navigation attempts of ancient civilizations and reaches the present time with the issue of legal mandates for the location identification of emergency calls in cellular networks and the emergence of location-based services. The science and technology for positioning and navigation has experienced a dramatic evolution [2]. The observation of celestial bodies for navigation purposes has been replaced today by the use of electromagnetic waveforms emitted from reference sources [3].There is a large variety of radio-navigation systems, ranging from legacy ones dating from the middle of the last century, such as Decca or Loran, to the ones relying on the transmissions from wireless local area network (WLAN) base stations or from the devices found in wireless sensor networks. However, the systems based on satellite transmissions are the ones that play a prominent role today. They are gathered under global navigation satellite systems (GNSS). This term refers to all systems (some of them operational, and others under development) that provide users with positioning information

GNSS vulnerabilities have become evident in the last decade. Authentication of the GNSS signals and data can be an important building block contributing to mitigating these vulnerabilities. This paper presents a Navigation Message Authentication (NMA) scheme based on the Timed Efficient Stream Loss‐tolerant Authentication (TESLA) protocol and a novel concept based on a single one‐way chain for all senders and cross‐authentication. The paper presents an NMA implementation in the Galileo Open Service (OS) navigation message that should provide similar navigation performance to data‐authenticated users and standard non‐authenticated users in terms of time to first fix, accuracy, and availability even in difficult reception conditions. The proposal also maintains a high level of signal unpredictability to help receivers protect against replay attacks. The scheme and implementation proposed yield significant improvements compared to the state of the art, offering the opportunity for Galileo to become the reference GNSS in civil navigation authentication. Copyright © 2016 Institute of Navigation