The increasing demand for IoT applications has driven the need for precise and scalable indoor positioning systems (IPS). Among existing techniques, Wi-Fi round trip time (RTT), introduced by the IEEE 802.11mc standard, offers high accuracy but suffers from scalability limitations due to the frames specifically sent for localization purposes. While fingerprinting can improve system scalability compared to multilateration, it relies on computationally intensive machine learning algorithms, which can be challenging to deploy on resource-constrained IoT devices. This article proposes a novel approach to improve the scalability and efficiency of Wi-Fi RTT fingerprinting solutions. The proposed system aims to simplify clustering and feature selection tasks by sorting RSSI measurements, thus eliminating the need for more complex algorithms. Experimental evaluations, in scenarios with varying densities of access points (APs), demonstrate significant performance gains compared to state of the art approaches. In high-density scenarios (e.g., one AP per 22 m2), the proposed system achieves an RMSE below 50 cm, a decrease of almost 98% in the memory used by the device, and supports location requests of up to 124 simultaneous Wi-Fi users, representing a 7.8% increase in scalability compared to previous proposals. These results highlight the potential of the proposed system to achieve a good compromise among accuracy, scalability, and complexity, making it a viable solution for IPS implementation in IoT environments.

Indoor localization has emerged as a critical enabler for next-generation location-based services and the evolving 6G ecosystem, particularly where satellite localization is unavailable. Among indoor technologies, Wi-Fi fingerprinting offers an attractive trade-off between deployment cost, infrastructure availability, and localization accuracy. Recent advances in IEEE 802.11mc have enabled the use of round-trip time (RTT) measurements, providing more stable and accurate observables than received signal strength (RSS). However, RTT fingerprinting still suffers from two major limitations: high overhead from exhaustive site surveys and the difficulty of maintaining dense radio maps in dynamic environments. This paper proposes a Wi-Fi RTT fingerprinting framework that minimizes offline calibration effort by restricting empirical measurements to a sparse set of reference locations associated with deployed access points (APs). A Gaussian Process Regression (GPR)-based reconstruction model synthetically generates dense virtual reference point fingerprints, while physical-signal fitting models improve RTT estimation during reconstruction. Unlike previous studies focused on RTT/RSS fusion, ranging compensation, or generic interpolation, this work systematically investigates GPR-based synthetic radio map reconstruction for Wi-Fi RTT fingerprinting, evaluating the impact of AP geometry, grid density, temporal averaging, and reconstruction models on localization performance. Experimental results from real-world RTT measurements show that the framework maintains sub-meter localization accuracy in deployments where the target area lies within the convex hull of the APs. Conversely, the observed RMSE is approximately 2 m in asymmetric extrapolation scenarios. Nonetheless, it significantly reduces the calibration complexity and signaling overhead associated with dense RTT fingerprint collection.

Non line of sight (NLOS) conditions significantly degrade the accuracy of Wi-Fi-Based indoor positioning systems (IPS). Although round-trip time (RTT) is generally more reliable than the received signal strength indicator (RSSI), it remains vulnerable to attenuation and multipath; moreover, dense RTT-compatible AP deployments may threaten scalability. This paper proposes a fingerprinting-based IPS that achieves high accuracy in NLOS scenarios, while remaining scalable and lightweight for Internet of Things (IoT) devices. By combining RTT, its standard deviation, and RSSI, accurate position estimates are obtained with only two RTT requests, reaching 93% accuracy and a 62 cm root mean squared error (RMSE) despite harsh conditions.

The wide availability of the Wi-Fi infrastructure together with the recent integration of the IEEE 802.11mc capability in common-off-the-shelf (COTS) devices, have contributed to increasing the interest of the research community in the fine time measurement (FTM) technique, which allows two Wi-Fi devices to estimate distances between each other. However, one of the main issues yet to be solved is how it scales with an increasing number of Wi-Fi devices injecting location-specific traffic in the shared medium. While the recently released IEEE 802.11az standard will still take time before being integrated in COTS devices, this paper aims at assessing the impact of the burst size on the ranging performance of COTS Wi-Fi Android devices running release 12. While increasing the burst size is expected to bring higher stability in the observed distance, on the other hand a longer transmission period for location-only purposes may jeopardize the transmission of data traffic among Wi-Fi users. Several models of smartphones and APs, and different frequency bands, have been considered in order to evaluate the behavior of the FTM procedure in real devices, showing that not always the newest or most expensive ones perform better. Also, it is shown that using the minimum burst size significantly decreases the performance and it is thus not recommended. While bursts longer than 8 may no be always supported by all the models and/or frequency bands, the small improvements in ranging estimations obtained when they are used do not always justify the increased location traffic injected in the network.

The field of Indoor Positioning Systems (IPS) is rapidly expanding due to the increasing need for accurate indoor localization. This research delves into the fingerprinting technique, a commonly used method in IPS, and advocates for coupling the Received Signal Strength Indicator (RSSI) to the Round-Trip Time (RTT) to boost its effectiveness. The primary incentive for this integration is to alleviate the network burden caused by the Wi-Fi RTT method while maintaining the system's precision. Our goal is two-fold: firstly, we aim to find the ideal combination of RTT and RSSI features that a specific machine learning algorithm requires to supply precise and prompt position estimations for real-time applications. Secondly, we aim to reduce the number of RTT features needed, as they demand the addition of location traffic, which may saturate the network when multiple stations try to locate themselves. To meet these goals, a variety of machine learning models and several combinations of the available metrics (RTT and RSSI) have been assessed. Initial findings indicate that this combined approach significantly diminishes network overhead and enhances the scalability and effectiveness of the fingerprinting method, paving the way for further exploration in indoor localization.

Since its integration in common-off-the-shelf (COTS) devices, the IEEE 802.11mc standard for the ranging estimation between a Wi-Fi card and an Access Point (AP) has grown interest in the research community. In 2021, Android released the new version 12 of its operating system, which adds some new configurable features in the Wi-Fi fine time measurement (FTM): the possibility for the user to set different burst sizes to the FTM procedure and a new one-sided FTM mode that can work with legacy APs. This paper assesses the impact of the burst size on the performance of the Wi-Fi FTM ranging. Intuitively, one may expect a higher stability in the ranging observation when the burst size is increased; however, it would imply an increase in the overhead of the ranging procedure. The impact has been studied with several models of smartphones and APs, and working in different frequency channels. The results show that, while using the minimum size allowed is not recommended because of a significant decrease in the performance, using burst sizes higher than 8 does not bring significant advantages that justify the additional traffic injected in the network.

AODVv2 is a well-known routing protocol used in MANETs (Mobile Ad hoc Networks). Formerly known as DYMO (DYnamic MANET On-demand), it is frequently used as a reference for routing protocols assessment. However, implementations of these protocols are scarce and the few ones available are currently outdated, no longer maintained and hardly upgradeable. This paper provides the details of a new AODVv2 implementation to be used in embedded devices working with the ARM microprocessor architecture. A user-space approach has been followed so both the upgradability and platform-independence are favored. A WiFi ad hoc network, modeling representative real scenarios, has been deployed to verify the correctness of the developed AODVv2 code and assess the performance of the protocol under realistic traffic conditions. A virtual machine has been used to perform a cross-compilation of a the code that implements the DYMO protocol in the Intel x86 computer architecture. Once compiled for being used in ARM-based devices, the code has been tested in Raspberry Pi devices to verify the proper behaviour. Simple scenarios and scenarios with high density of nodes have been deployed and data have been collected and analysed.

Since IEEE 802.11 defined a couple of enhancements that allow accurate time measurements in COTS Wi-Fi devices, the possibility of achieving precise low-cost distance estimations in Wi-Fi has become a reality. However, many sources of error, such as bandwidth limitations of the Wi-Fi signal, limited clock rate in the device, multipath propagation due to the obstacles in the indoor environment, etc., may add noise to the time measurements and therefore distort the estimated ranging. This study aims at covering the gap existing in the literature by assessing the performance of the ranging estimation in real IEEE 802.11mc stations in a typical NLOS environment. The impact on the accuracy is also explored when the station is held in different positions with respect to the floor.

Indoor positioning is still considered an open issue, especially when general-purpose communication networks are used to observe the metrics for positioning. IEEE 802.11mc aims at providing positioning capabilities to Wi-Fi networks. Google recently developed a feature aimed at making easy to run the standard in any Android device; however, only few access points (APs) officially support and advertise it. It is proven, though, that a bunch of APs are able to attend the location requests from 802.11mc devices despite not announcing their positioning capabilities. An application is proposed here that effectively gathers a list of all the APs that may collaborate in the indoor positioning process. This work is aimed at studying the performance of the location error in a real scenario where Android Wi-Fi devices run the IEEE 802.11mc positioning facility. The results demonstrate that, although errors are smaller than 2 meters as promised, the performance greatly depends on the AP and the frequency band used.

MANETs have been focusing the interest of researchers for several years. The new scenarios where MANETs are being deployed make that several challenging issues remain open: node scalability, energy efficiency, network lifetime, Quality of Service (QoS), network overhead, data privacy and security, and effective routing. This latter is often seen as key since it frequently constrains the performance of the overall network. Location-based routing protocols provide a good solution for scalable MANETs. Although several location-based routing protocols have been proposed, most of them rely on error-free positions. Only few studies have focused so far on how positioning error affects the routing performance; also, most of them consider outdated solutions. This paper is aimed at filling this gap, by studying the impact of the error in the position of the nodes of two location-based routing protocols: DYMOselfwd and AODV-Line. These protocols were selected as they both aim at reducing the routing overhead. Simulations considering different mobility patterns in a dense network were conducted, so that the performance of these protocols can be assessed under ideal (i.e. error-less) and realistic (i.e. with error) conditions. The results show that AODV-Line builds less reliable routes than DYMOselfwd in case of error in the position information, thus increasing the routing overhead.

Topics on network simulation are often offered as elective topics or short seminars of programs on computer sciences and telecommunications engineering. In other programs simulation is offered as part of a general core topic (e.g. probability and statistics, network performance, etc.). It is not frequent to find simulation as a core topic. At the Faculty of Telecommunications in Barcelona it was decided to include network simulation as a core topic in the former integrated master (5 academic years) on telecommunication engineering. This paper deals with the reasons after that decision. The goal of the paper is to present and discuss how the topic evolved through the years and how it has been migrated to the new careers with separated degree and master after the Bologna process.

Together with the trend towards engineering designs more accessible to handicapped people there is an increasing concern at the engineering faculties to include topics related to accessibility in their programs. Engineers must be aware that handicapped people use technology and designs must take into account this fact. This paper explains how a topic on accessibility was started at a technical faculty as a cross topic to five different engineering degrees: Electrical, Electronics and Automatic Control, Industrial Product Design, Electronic Systems and Computer Science. The introduction process is explained along with the teaching methodology. Results after the first two courses are good in general but present some issues. The main issue to be corrected is that students from different branches achieve different academic performances.

This paper proposes a positioning method that combines GPS pseudoranges and WLAN ranges when less than four GPS satellites are within sight. To enhance the positioning availability, a tight hybridization approach with both technologies is considered. Although the work has been performed considering WLAN and GPS, most of the presented ideas, procedures and results are also valid for generic tight non-synchronized fusion of GNSS with terrestrial signals. Special emphasis is placed on the phenomenon of positioning ambiguity that appears due to the combination of measurements with different characteristics. To solve this ambiguity, a method is proposed and studied. The availability and accuracy of the system are tested considering different satellite and terrestrial geometries. The results show that the proposed system is able to improve the availability while maintaining the accuracy of GPS as a standalone.

This article proposes a set of strategies to improve the performance stability and reliability of purely software ToA-based ranging with off-the-shelf WLAN equipment. Taking as starting point the core design lines proposed in, where timing measurements were taken at OS level using the CPU clock of the client device, we optimize the OS configuration and the capture of the time-stamps. Results obtained with a prototype demonstrate that the proposed enhancements improve the performance stability by a factor four. The interest in this kind of ranging methods is because they enable cost-effective and accurate positioning in GNSS-less environments.

Wireless networks have boosted the interest of users and network operators on location due to the possible synergies between the cellular layout and location techniques. As a result, location methods have been proposed to provide this information in most wireless technologies. Evaluation of the performance of these and further techniques is initially achieved by means of simulation. It is essential to use suitable models for featuring errors that are present in observations. This characterization is especially relevant in time-based techniques such as time-of-arrival (TOA) and time-difference-of-arrival (TDOA). These techniques are significantly impacted by non-line-of-sight conditions; hence their performance is usually evaluated under these conditions. This article compares several ranging-error models adapted to indoors and studies their impact on the performance of time-based techniques (e.g., TOA and TDOA). Results indicate that simple models that are not based on the actual distance between nodes tend to underestimate the positioning error with respect to more complex models.

This paper presents a positioning algorithm to improve the performance of location systems based on two-way TOA techniques. This algorithm, which we call passive-TDOA, consists of computing the time-difference-of-arrival (TDOA) measurements from the TOA messages that some terminals generate in the positioning process. Passive-TDOA offers accurate results under optimum geometry. This work goes a step further and evaluates the accuracy of the algorithm in scenarios with adverse geometry. Accordingly, scenarios with access points in line and non-line of sight are studied through simulation and compared with the accuracy achieved by means of regular TOA.

Hybridization is a hot topic in the location field. Since there is no universal location technique that is capable of positioning in indoor and outdoor environments, two or more techniques must be coupled to produce a complete location solution. Accordingly, information on the availability of each of the techniques being coupled is of great relevance in the design and implementation stages of the location system. In public cellular networks, this coupling usually involves a terrestrial triangulation technique (e.g. E-OTD, OTDOA) and a GNSS-based technique (e.g. A-GPS). The purpose of this paper is twofold. Firstly, it presents a software tool developed for studying the availability of location systems in certain environments, which is able to capture and present information on the availability of satellites in the NAVSTAR constellation (i.e. GPS) and the GSM/GPRS base stations being received in the user terminal. Secondly, it studies the coverage of these techniques using the tool described. Availability data for three routes in an urban environment are gathered and analyzed. In two of them, GPS did not cover 100% of the route, which demonstrated the need to couple the technique with another terrestrial technique to cope with the "dark" areas.

Location systems based on already-deployed cellular networks spend the resources of the underlying communications network. This paper proposes a middleware that reduces the consumption of resources and optimizes the location traffic load. This middleware, called MILCO (Middleware for Location Cost Optimization), is assumed to run on networks that can choose from among several location techniques (e.g. A-GPS, NMR, etc.). MILCO selects the optimum technique for each request, i.e. the location technique that provides the required quality of service (QoS) and minimizes resource operating expenses. In addition, MILCO takes advantage of ongoing location processes to reduce the overall expenditure of resources. The results show that MILCO reduces the rate of location-process failure and improves latency for location provisioning and resource usage in cellular networks.

This work presents a statistical field study of the availability of time sources for location in a true wireless network. Terrestrial (base stations) and satellite (GPS) sources were investigated in three different urban scenarios. The density function of a specific number of sources available for triangulation is presented along with other statistical data in order to assess coverage. Since the fusion of terrestrial and satellite sources to obtain the location in wireless networks has been proposed as a way of improving coverage, the joint density function and cross-correlation between the availability of both types of sources are also presented. This correlation depends on the scenario, leading to the conclusion that the improvement obtained through the fusion of sources depends on both the fusion type and the scenario.

This paper deals with the characterization of traffic-related variables in cellular mobile telephony in networks that use code-division multiple access (CDMA). In order to achieve this characterization, a simulation tool has been developed and used. The simulator implements the performance of a UMTS network, taking into account issues such as power and admission control. The aim of the paper is to study the impact of lognormal service time distribution and compare it to the exponential one normally used in literature. The simulator provides data about channel holding time, time between handoffs (handoff traffic characterization) and handoff duration, along with quality of service information about the simulated environment.

This work presents a new approach designed to reduce the costs (e.g., signalling, latency, power consumption, etc.) of providing location services in cellular networks that use a combination of location techniques in a hybrid fashion: MiLCO (middleware for location-services cost optimization). This proposal is based on managing location requests according to their quality of service (QoS) requirements of accuracy and latency, and selecting the most convenient technique or combination, i.e., the one that optimizes the use of the system's resources for positioning, whilst fulfilling QoS requirements. A possible implementation of this location middleware is evaluated and the results in comparison with other wide-deployed solutions are presented.

The paper presents an analysis of teletraffic variables in cellular networks. The variables studied are the time between two consecutive handoff arrivals and the handoff delay. These teletraffic variables are characterized by means of an advanced software simulator that models several scenarios assuming fixed channel allocation. Information about the quality of service is also provided. A large set of scenarios has been simulated and the characterization results derived from its study have been presented and analyzed.

The paper shows the need to transmit extra assistance data in hybrid location systems. The proposal presented here uses the current network protocols in order to deliver these non-standardized assistance data in 2G/2.5G location systems. To this end, a complete analysis of the available protocols and methods of identifying a non-standard assistance data source is performed.