A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> In this paper, a novel simultaneous tracking and direction of arrival estimation algorithm for TDD/TDMA broadband wireless access networks employing beam-switched base station antennas is presented. Direction of arrival estimation could be useful, for example, to generate occasional user dedicated beams to overcome temporary channel impairments or to develop advanced network management strategies such as system handover based on direction of arrival knowledge. The algorithm has been studied theoretically and by means of simulations achieving high efficiency and very good performance results. <s> BIB001 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> Millimeter-wave (mm-wave) communication systems operating between 30GHz and 300GHz are emerging as a promising technology for meeting the exploding bandwidth requirements of future wireless systems. In addition to large bandwidths, mm-wave systems afford high-dimensional multiple input multiple output (MIMO) operation with relatively compact arrays, and the corresponding narrow spatial beams make beamspace MIMO communication particular attractive. An important implication is that while the ambient spatial dimension is high, mm-wave MIMO channels exhibit a low-rank structure that is manifested in the sparsity of the beamspace MIMO channel matrix. In this paper, we develop a model for sparse mm-wave MIMO channels and propose an approach to mobile station (MS) localization that exploits changes in statistics of the sparse beamspace channel matrix as a function of the MS position. Unlike most existing methods, line-of-sight (LoS) propagation is not mandatory and the proposed approach benefits from the information provided by non-line-of-sight (NLoS) paths. Beamspace sparsity is exploited for developing a low-dimensional maximum-likelihood (ML) classifier that delivers near-optimal performance with dramatically reduced complexity compared to conventional designs. Numerical results illustrate the impact of the physical environment, grid-resolution, and MIMO dimensions on localization performance. <s> BIB002 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> Indoor positioning gained great interest in recent years. Several performance evaluations are available for consolidated systems, especially for ultra-wideband radios. Given the current success of mmWaves networks, in this paper, we investigate the performance of RSSI localization systems operating at mmWaves. Our reference is the IEEE 802.11ad standard for multi-Gbps WLANs. We tested the performance of RSSI localization in several scenarios differing in the number of access points serving as anchors and the RSSI acquisition. Our results show that RSSI localization is still effective at mmWaves using devices compliant with the IEEE 802.11ad standard in terms of sensitivity and frequency bands. We will show that these radios can achieve an accuracy of around 1 m if a sufficient number of measurement samples is acquired. <s> BIB003 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> In this paper, an approach of estimating signal parameters via rotational invariance technique (ESPRIT) is proposed for two-dimensional (2-D) localization of incoherently distributed (ID) sources in large-scale/massive multiple-input multiple-output (MIMO) systems. The traditional ESPRIT-based methods are valid only for one-dimensional (1-D) localization of the ID sources. By contrast, in the proposed approach the signal subspace is constructed for estimating the nominal azimuth and elevation direction-of-arrivals and the angular spreads. The proposed estimator has closed-form expressions and hence it does not have to search over the entire feasible field. Therefore, it imposes significantly lower computational complexity than the conventional 2-D estimation approaches. Our analysis shows that the estimation performance of the proposed approach improves when the large-scale/massive MIMO systems are employed. The approximate Cramer-Rao bound of the proposed estimator for the 2-D localization is also derived. Numerical results demonstrate that albeit the proposed estimation method is comparable with the traditional 2-D estimators in terms of performance, it benefits from a remarkably lower computational complexity <s> BIB004 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> Next generation cellular networks will experience the combination of femtocells, millimeter-wave (mmW) communications and massive antenna arrays. In addition to benefits in terms of an increased communication capacity, this mix of technologies can be fruitfully exploited to enable high-accuracy indoor positioning. In fact, thanks to the high beamforming capability of massive arrays, mobile terminal localization can be performed in principle by using only one single access point (AP), thus avoiding costly infrastructures with additional APs dedicated to positioning. In this context, our paper aims at investigating the localization and orientation performance limits of networks employing wideband massive arrays both at receiving and transmitting devices. In particular, the effects of the array structure, bandwidth and synchronization error are studied both at mmW and at 10GHz, when phased, timed and random arrays are employed. <s> BIB005 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> Location awareness in wireless networks may enable many applications such as emergency services, autonomous driving and geographic routing. Although there are many available positioning techniques, none of them is adapted to work with massive multiple-in-multiple-out (MIMO) systems, which represent a leading 5G technology candidate. In this paper, we discuss possible solutions for positioning of mobile stations using a vector of signals at the base station, equipped with many antennas distributed over deployment area. Our main proposal is to use fingerprinting techniques based on a vector of received signal strengths. This kind of methods are able to work in highly-cluttered multipath environments, and require just one base station, in contrast to standard range-based and angle-based techniques. We also provide a solution for fingerprinting-based positioning based on Gaussian process regression, and discuss main applications and challenges. <s> BIB006 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> The vision of next generation 5G wireless communications lies in providing very high data rates (typically of Gbps order), extremely low latency, manifold increase in base station capacity, and significant improvement in users’ perceived quality of service (QoS), compared to current 4G LTE networks. Ever increasing proliferation of smart devices, introduction of new emerging multimedia applications, together with an exponential rise in wireless data (multimedia) demand and usage is already creating a significant burden on existing cellular networks. 5G wireless systems, with improved data rates, capacity, latency, and QoS are expected to be the panacea of most of the current cellular networks’ problems. In this survey, we make an exhaustive review of wireless evolution toward 5G networks. We first discuss the new architectural changes associated with the radio access network (RAN) design, including air interfaces, smart antennas, cloud and heterogeneous RAN. Subsequently, we make an in-depth survey of underlying novel mm-wave physical layer technologies, encompassing new channel model estimation, directional antenna design, beamforming algorithms, and massive MIMO technologies. Next, the details of MAC layer protocols and multiplexing schemes needed to efficiently support this new physical layer are discussed. We also look into the killer applications, considered as the major driving force behind 5G. In order to understand the improved user experience, we provide highlights of new QoS, QoE, and SON features associated with the 5G evolution. For alleviating the increased network energy consumption and operating expenditure, we make a detail review on energy awareness and cost efficiency. As understanding the current status of 5G implementation is important for its eventual commercialization, we also discuss relevant field trials, drive tests, and simulation experiments. Finally, we point out major existing research issues and identify possible future research directions. <s> BIB007 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> Using collaborative sensors or other observing devices equipped with sectorized antennas provides a practical and low-cost solution to direction-of-arrival (DoA) and received signal strength (RSS) estimation, as well as noncooperative transmitter (TX) localization. In this paper, we study the performance and theoretical bounds of DoA/RSS estimation and localization using sectorized antennas. We first show that the sector-power measurements at an individual sensor form a sufficient statistic for DoA/RSS estimation and TX localization. Motivated by that, we then derive the Cramer–Rao bound (CRB) on DoA/RSS estimation based on sector-powers and study its asymptotic behavior. Moreover, we derive an analytical expression for the mean square error (MSE) of a practical sectorized-antenna-based DoA estimator, compare its performance to the derived CRB, and study its asymptotic properties. Next, we derive the CRB for localization based on sector-powers. The resulting CRB is a lower bound for a localization system where the DoA/RSS estimates, obtained from sector-powers at individual sensors, are fused together into a location estimate. Moreover, the CRB also covers the more general case of a localization system where the sector-powers from individual nodes are directly fused together, without an intermediate DoA/RSS estimation step. We compare the obtained CRB to a localization approach employing an intermediate DoA/RSS estimation step and observe that skipping this intermediate processing step may result in a substantially improved localization performance. Finally, we study the influence of various important system parameters, such as the number of sensors, sectors, and measurement samples, on the achievable estimation and localization performance. Overall, this paper demonstrates and quantifies the achievable DoA/RSS estimation and localization performance of sectorized antennas and provides comprehensive design guidelines for sector-power based low-complexity localization systems. <s> BIB008 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> One of the notable aspects of public safety applications in 5G networks is location awareness, which is a feature of contemporary technology that imparts details about a user’s geographical location to another user or application. Mobile users take their cell phones and other gadgets with them almost everywhere. Thus, integrating location awareness in mobile applications gives users a much more real experience. Therefore, this paper presents an algorithm to predict user location in 5G networks by using received signal strength measurements. Initially, the relative coordinates of users are computed using Isomap. Then the relative coordinates of users are transformed by Procrustes analysis. In order to evaluate the performance of the proposed algorithm, the Cramer–Rao lower bound is derived, which is the lower bound on error variance. It can be concluded from our results that the proposed approach outperforms those found in the existing literature. <s> BIB009 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> C. MDS Based Localization for Future 5G <s> In this article, we address the prospects and key enabling technologies for highly efficient and accurate device positioning and tracking in 5G radio access networks. Building on the premises of ultra-dense networks as well as on the adoption of multicarrier waveforms and antenna arrays in the access nodes (ANs), we first formulate extended Kalman filter (EKF)-based solutions for computationally efficient joint estimation and tracking of the time of arrival (ToA) and direction of arrival (DoA) of the user nodes (UNs) using uplink reference signals. Then, a second EKF stage is proposed in order to fuse the individual DoA/ToA estimates from one or several ANs into a UN position estimate. Since all the processing takes place at the network side, the computing complexity and energy consumption at the UN side are kept to a minimum. The cascaded EKFs proposed in this article also take into account the unavoidable relative clock offsets between UNs and ANs, such that reliable clock synchronization of the access-link is obtained as a valuable by-product. The proposed cascaded EKF scheme is then revised and extended to more general and challenging scenarios where not only the UNs have clock offsets against the network time, but also the ANs themselves are not mutually synchronized in time. Finally, comprehensive performance evaluations of the proposed solutions on a realistic 5G network setup, building on the METIS project based outdoor Madrid map model together with complete ray tracing based propagation modeling, are provided. The obtained results clearly demonstrate that by using the developed methods, sub-meter scale positioning and tracking accuracy of moving devices is indeed technically feasible in future 5G radio access networks operating at sub-6GHz frequencies, despite the realistic assumptions related to clock offsets and potentially even under unsynchronized network elements. <s> BIB010
The fifth generation (5G) wireless networks are promising to achieve higher data rates, higher bandwidth low transmission latency. 5G is also considered to be a revolutionary milestone in wireless communication, which will enable lots of new applications including connected cars, IoT with billions of sensors and humanoid robots. Currently, the number of devices connected to the Internet are 6.4 billion, in  Gartner predicted that in 2020 the approximate number of devices connected to the Internet would reach up to 20.8 billion. In order to support these billions of devices, 5G systems require wide bandwidth which is available in higher frequencies of the radio spectrum BIB007 . A large number of devices will lead to the deployment of the dense networks in which it is possible to get better-ranging measurements in terms of localization. In the past, some localization techniques are developed for 3G and 4G networks, but developing localization techniques for 5G is still an open issue  . LBS are always popular among the users and it is expected to become an essential part of the development of 5G technology. In BIB002 , BIB003 the authors proposed localization techniques for millimeter waves in 5G. In BIB005 BIB004 BIB006 the authors presented localization schemes for massive multiple input multiple output (MIMO) systems. DoA technique is investigated for 5G in BIB001 . Similarly, in BIB003 , BIB009 the authors used localization based on RSS. An extended Kalman filter fused with the hybrid DoA and ToA is used in BIB010 for 5G localization. A similar technique is presented in BIB008 in case of a non-cooperative transmitter. 5G Network localization with the dense deployment of users is investigated in BIB009 using a variant of MDS, i.e., Isomap. Localization of static IoT networks in 5G is recently presented in  by using centralized MDS.