Fluid accumulation in the human body is, in many cases, a symptom of some underlying pathological condition. Most common examples include edema, ascites, pleural effusion, and internal bleeding. Currently available non-invasive methods to assess fluid accumulation in the body are mainly imaging-based (i.e. ultrasound, computed tomography). This means that monitoring is limited to spot-checks and is only performed when the presence of a particular condition is already suspected from prior clinical evaluation of the patient. There is high clinical interest in the development of a system allowing such monitoring to be performed automatically, continuously over a prolonged period of time, and independently of prior clinical evaluation. For instance, in the case of internal bleeding, hemorrhage indicators such as variation in heart rate and blood pressure are only observable after significant blood loss (up to more than 1 liter) has already taken place, therefore an early warning system can save lives, decrease hospital stay length and significantly reduce complication-related costs. In this thesis, a pioneer solution is proposed for development of such a monitoring system. The hypothesized solution is based on the observation of specific energy-describing features of the Ballistocardiogram (BCG) signal, a measure of the periodic displacements generated on the body as a result of ballistic forces produced by the heart during each cardiac cycle. Because of additional damping generated by the presence of internally accumulated fluid, the energy of this signal is expected to decrease compared to its baseline value. The BCG can be recorded unobtrusively with different sensing modalities on the surface of the body. In order to validate the research hypothesis and assess the feasibility of this novel technique, a custom experimental set-up exploiting several different BCG sensing options has been used to carry out a study on 15 human volunteers. Localized fluid accumulation along the GI tract was induced in a controlled, safe and simple fashion, by means of water intake by the participants, and the BCG signal was recorded before and after intake. Signal feature exploration and performance analysis has been used to develop an optimized feature able to accurately capture the decrease in signal energy due to fluid accumulation, as well as to identify the most suitable sensor type and monitoring body location for the present application. The developed energy-describing feature shows a significant decrease in energy value from baseline to after-intake condition with a p-value<0.001. Moreover, the selected feature was able to correctly identify presence of fluid accumulation with high sensitivity (90% in bed-based, and 100% in standing-position monitoring). Given the promising results of the present study, further research towards improvement and development of the proposed technique is highly encouraged.

Decreasing injuries in football is a topic of interest for the KNVB and KNHB. To reach this goal, the use of smart sensor pants is researched. The data will be used to develop models for finding injury risk factors that are related to movements. Currently, the system is capable of reading out the IMUs and storing the data on an SD-card, for post-analysis of the data. As next step, the communication link should be implemented, for real time feedback to the football players. The design of an efficient communication system in terms of power, size, and reliability, is quite a big task. By looking at similar research to body-worn devices, it is noted, that most devices deal with a 10 times lower data rate than the current device. On top of that, it is noted that the absorption of the body is causing problems on the link reliability. Based on these observations, it is decided to focus the research of this Thesis on the reduction of the data load, and the optimization of the transmission part of the smart sensor pants. The Thesis is split into two parts, the first part will show the use of lossless data compression. The second part will start with showing the benefit of using a patch antenna over a dipole antenna and continues by showing the benefit of using a dual antenna configuration over a single antenna configuration. To be more specific, the first part of this Thesis starts by comparing different lossless data compression algorithms, from which the FELACS algorithm is chosen as most suited. This algorithm is then implemented on the current hardware and tested on data from the smart sensor pants in a realistic football scenario. These results show an average compression ratio of 43 %-45 % in the most intensive 5-minutes of a football game, with a minimum of 38 % in an interval of 10 s. To improve the compression algorithm, an adjustment to the FELACS algorithm is proposed. This adjustment is theoretically tested and shown to outperform the FELACS algorithm with a higher compression ratio. In the second part, the use of a dual antenna configuration is discussed, whereby the use of a patch antenna is compared to a dipole antenna. It will be shown, that a dual antenna configuration can significantly improve the signal strength around the player, resulting in an almost isotropic radiation pattern, using pattern diversity. On top of that, this form of pattern diversity is observed to increase the reliability of the link, using switched combining. Moreover, it will be shown that a patch antenna will be more suited for this application, due to the higher gain in the front, and the robustness against interference when placed close to a conducting material. In summary, the two main contributions of this Thesis, are the reductions in data load, and the testing and verification of the dual patch antenna configuration. These contributions provide the basis for the communication part of the smart sensor pants.

This thesis details the design of a selection operator used in a Genetic Algorithm. The Genetic Algorithm is used for loudspeaker filter design of three way loudspeakers for which tournament selection was chosen as selection operator. A methodology is proposed and used to tune the parameters of tournament selection, which is based on diversity and fitness of the population. Besides basic tournament selection, two new adaptive selection operators based on tournament selection are proposed to improve its functionality. The first adaptive selection operator uses noise proportional to the fitness variance of the population to improve the efficiency of the genetic algorithm. The second adaptive selection operator uses a convergence stage to speed up the convergence towards the optimal filter. After the presented tuning process in this thesis, the latter adaptive selection operator was found to perform better. The optimal selection operator and parameters found in this thesis will not translate to every application, because they heavily depend on the design and the application of the genetic algorithm. However, the presented comparison of selection operators, the provided performance metrics and design methodology can still be used to guide the choice and the tuning process of a selection operator used in any genetic algorithm.

This thesis is part of the Bachelor Graduation Project of Electrical Engineering at Delft University of Tech-nology. This contains the complete design process of an analogue implementation of a Motional Feedbackcontroller. Although the complete controller has been designed, no significant test results have yet beenacquired. However, theoretically the linear distortion at20H zis reduced by99.88%by the controller. Alsois predicted that the nonlinear distortion is suppressed, because of the high loop gain. The feedback signalis generated using an accelerometer. The controller mainly consists of a PI-controller and a predistortionfilter by means of a Linkwitz Transform.

This thesis describes the design and implementation of a controller and GUI for an AI loudspeaker filter design program. This program uses a genetic algorithm to create a combination of analog passive filters, one for each driver in a loudspeaker system. In the controller, two cost functions are designed to evaluate these filter combinations, and when the genetic algorithm has created its final filters, unnecessary components are removed and all component values are optimized. A GUI is created to allow easy user interaction. For selecting a cost function, not enough data was obtained to make a deliberate decision based on performance. Therefore, this decision was based on theory and subordinate features. Nonetheless, the final program is able to create flat acoustic responses in a margin of 2 dB.

The aim of this research is to create a nonlinear model of a loudspeaker to analyze the open-loop distortion as well as the closed loop performance with linear and nonlinear controllers. A method is proposed for measuring the dominant nonlinear parameters of a loudspeakers. Furthermore, the loudspeaker distortion is both measured experimentally and simulated using the nonlinear model. The method for nonlinear system identification suffers from poor accuracy and takes into account neither the Eddy current losses, frequency dependent compliance and damping nor visco-elastic effects of the loudspeaker surround material. The simulations and measurements of distortion are not in agreement.

This paper reports the design of a part of a genetic algorithm, which is made to design analog filters for loudspeakers. The part in this report is the part which deals with the representation of electrical filter circuits, the mutation of these filters, and finding their transfer function. The considered representations are graph coding and a tree data structure. They are compared on intuitiveness, how well mutations can be performed, and the complexity of calculating the transfer function. The tree structure is reasoned to be the most suitable. Described is which mutations can be performed on a filter by the final program, as well as how embryo circuits are made, how the transfer function is calculated, and which hyperparameters were designed and how they were set. Finally, the design is implemented using Python and the operations are tested.

This report focuses on the design and implementation of both a detection system and an enclosure, which are designed to be used in a quantum random number generator. These parts are designed to be manufactured using off-the-shelf components to make the quantum random number generator affordable and accessible to a completely new user-group that cannot afford and operate the currently existing alternatives for quantum random number generation. After implementing the designed systems it is found that although the output of the system is random, true-randomness cannot be guaranteed using off the shelf components, because of the interference of classical noise sources.

The uprising of Long Range (LoRa) technology for Low-Power Wide Area Network (LPWAN) has gained popularity in IoT applications. As LoRa utilizes the license-free ISM-bands, many network providers have deployed their LoRa networks that adhere to the LoRaWAN specification. With so many deployed networks, it is likely that devices belonging to neighboring networks will interfere and lead to increased packet loss due to collisions. However, not all colliding frames attribute to packet loss, because of the capture effect in LoRa. In this thesis, we investigate the performance of LoRaWAN, particularly on frame collision and packet loss, through small-scale measurements, which is then followed by the evaluation in a large-scale setup involving multiple gateways. It is expected that adding more gateways can reduce packet loss. By estimating the Data Extraction Rate (DER) from the measurements and validating the result with simulations, we found that adding more gateways, to some extent, does improve the DER when the capture effect is considered. However, downlink traffic can significantly decrease DER of a single gateway as the currently available gateways operate in half-duplex mode. The impact of different spreading factor parameters to the network performance is also evaluated. We also characterize and evaluate the two major LoRaWAN networks in the Netherlands, namely The Things Network (TTN) and KPN, which respectively represent the crowdsourced and commercial usage of LoRaWAN networks. The influence of traffic from end-devices belonging to other networks on the channel utilization is evaluated. The results can be used as an empirical basis for developing more accurate models and simulations to better understand the capabilities of LoRaWAN.

This thesis describes the digital implementation of a motional feedback system for a bass loudspeaker. Motional feedback is used to suppress the linear and non-linear distortions produced by the loudspeaker, especially at the low frequencies. An accelerometer is mounted on the cone of the loudspeaker to provide the feedback signal. The controller which consists of a PI controller and an equalizer are implemented on an FPGA. The equalizer, which is the inverse of the linear model of the loudspeaker, is used to compensate for the linear distortion. The PI controller with negative feedback is used to suppress the non-linear distortion. Not all measurement results are available at the moment of submission of this thesis. However, simulations were carried out on the model of the loudspeakers which show that the linear distortion is fully suppressed. The reduction of the non-linear distortion due to the controller can not be seen in the simulations.

Over the last two decades, we have witnessed a tremendous evolution of wireless communication systems. For example, the data rates in mobile wireless systems have increased from a few tens of kilobits per second to 10 gigabits per second between the first and last, i.e., fifth generation (5G). The main enablers for this growth are signal processing and radio frequency (RF) hardware innovations, which led to more efficient modulation and coding schemes and high-performance RF transceivers. Following these trends, future wireless systems such as 6G and WiFi-7 aim for even higher data rates, requiring higher frequency ranges, wider bandwidths, and massive antenna arrays. These developments pave the way toward joint communication and sensing RF systems with very high range, Doppler, and angular resolutions. In particular, favorable signal and RF transceiver properties such as large bandwidth will enable precise RF localization in rich scattering environments such as indoor or urban canyons where multipath effects severely impair the performance of traditional localization systems like GNSS (Global Navigation Satellite Systems). At the same time, the wide range of emerging applications in areas of autonomous navigation, assisted living, and Internet-of-Things require precise localization, often to cm-level degree accuracy. Therefore, it is evident that new localization approaches and signal processing algorithms that can exploit signal and transceiver properties of emerging wireless systems are needed to solve the problem of precise localization in multipath environments and lead the way to novel applications. The goal of this thesis is to design signal processing algorithms and protocols that will enable precise ranging in multipath environments while using practical single-antenna RF transceivers. In the first part of this thesis, we introduce a multiband channel model to describe multipath channel measurements collected over multiple separate frequency bands using narrowband and wideband RF transceivers. This model shows that multiband channel measurements have multiple shift-invariance property and that by increasing the frequency aperture of the multiband measurements, we can improve the resolution of multipath time-delay estimation. We use this property of the measurements to develop high-resolution time-delay estimation algorithms based on subspace estimation. To illustrate the performance of these algorithms, we perform extensive numerical experiments which demonstrate that the proposed algorithms are statistically efficient and that multiband time-delay estimation enables precise ranging in multipath environments. However, the aforementioned results also show that the proposed algorithms are sensitive to errors introduced by hardware impairments of RF transceivers and imperfect calibration. In the second part of the thesis, we focus on the problem of joint RF transceiver calibration and high-resolution time-delay estimation. For example, in practical scenarios, the frequency response of RF transceivers might not be known nor calibrated, and performing time-delay estimation without calibrating these effects will lead to biased estimates. We show that the problem of joint RF transceiver calibration and time-delay estimation can be formulated as a particular case of covariance matching, which after reformulation, can be solved using a simple group Lasso algorithm. Likewise, due to imperfections of oscillators used in RF transceivers, the mobile and anchor nodes are usually not frequency synchronized. This frequency offset severely deteriorates the performance of multiband ranging methods. To solve this issue, we design a two-way protocol for collecting multiband channel measurements and a weighted least squares-based algorithm that enable joint clock synchronization and ranging. Finally, in the last part of the thesis, we validate our modeling assumptions and illustrate the performance of the multiband time-delay estimation algorithms by considering practical scenarios of localization in future WiFi-7 networks. For these experiments, we use real indoor multipath channel measurements collected in a hospital and a university building environment. The results of the experiments show that using multiband channel measurements with a total bandwidth of 320 MHz, the absolute ranging error is smaller than 4 cm in 80% of the cases. Likewise, using the same scenario setup and three anchors to localize the mobile node, it is observed that the positioning error is below 24 cm in 95% of the cases. These results show that by using the advanced signal processing techniques to design estimation algorithms and channel measurement protocols that can exploit the properties and degrees of freedom offered by future wireless systems and RF transceivers, decimeter-level accurate positioning is achievable. The signal processing models presented in this thesis are common to the wide area of array signal processing applications, such as radar and ultrasound imaging. Therefore, the results presented in this thesis impact these application areas as well. @en

The advent of the digital era has revolutionized many aspect of our society and has significantly improved the quality of our lives. Consequently, signal processing has gained a considerable attention as the science behind the digital life. Among different applications for signal processing theory and algorithms, wireless communications remains one of the attractive and popular ones due to the widespread use of mobile devices. This thesis is dedicated to develop signal processing algorithms to design highspeed wireless transceivers that can perform in highly reflective and harsh environments. The start of this research work initiated as a collaboration between TU Delft and an industrial partner, on a research aimed at short range gigabit wireless link within a lithography machine. The underlying unique wireless environment, together with the challenging specifications of the communication link for mechatronic systems, made this a compelling research project.@en

This thesis report focuses on possible methods of digital implementation of motional feedback in a bass loudspeaker. In this thesis, the control system will be created for a monopole and a dipole speaker specifically. It does so by sketching the outlines of such a system and examining possible designs for the components required to suppress distortion which is mainly created by the speaker. This thesis shows that the digital implementation indeed allows filtering with very little latency but there are limitations in accuracy due to the conversion from the analogue to the digital domain. It is shown in this thesis that a partly analogue and partly digital system is desired for better error correction. A desired input-output gain of 30=29.54dB is achieved. The controller that is suggested is a controller based on the transfer function of the speaker. By transforming the input signal with the inverse of this open-loop transfer, the closed-loop transfer will be flattened. The instrumentation amplifier used to subtract the feedback signal from the input signal is designed such that the influence of the quantization noise is minimized. Loop-gain is added by the instrumentation amplifier, the controller and voltage-to-current amplifier. By creating loop-gain as much as possible using the digital implementation, noise is suppressed from 30dB up to 90dB within the range of frequencies of interest. The designed components in the motional feedback system allow a loop-gain up to 70dB and an input to output voltage gain of 30dB before instability occurs.

Many wheelchair users actively engage in wheelchair sports, for instance in the Paralympics. Trainers increasingly use the developments in sports technology for analysis. But wheelchair athletes do not benefit as much from these developments. A wheelchair can, for instance, disturb signal transmission. Recently, a set of studies describe the development of a wheelchair measurement system, the Wheelchair Mobility Performance Monitor (WMPM). It monitors wheelchair kinematics based on a wheelchair model and two Inertial Measurement Units (IMUs). The WMPM also gives relative location and orientation i.e. relative pose. But this does not allow for game analysis, which requires the absolute location of an athlete. A way to obtain the absolute location of an athlete is the use of Ultra-wideband (UWB) technology. It is often used due to its relatively high ranging accuracy and affordability. However, UWB signal transmission can be disturbed due to Non-Line-Of-Sight (NLoS) situations, where the body of an athlete, or the wheelchair, is located between two UWB nodes. This reduces the localization precision and accuracy. Game dynamics, i.e. quick changes in direction and velocity, also reduce the UWB localization precision and accuracy. Separately, UWB and the WMPM are not sufficient for proper absolute pose tracking. But a combination of these systems, i.e. sensor fusion, could be a good alternative. To provide trainers with real-time tracking data, the sensor data of these systems need to be fused on an embedded system. This requires an efficient UWB localization solution. A recent algorithm by Larsson formulates a localization problem with an easier-to-compute linear eigenvalue approach. In this work, this approach is validated and compared with a previous implementation via simulations and measurements. We show a execution time that is 5 times faster, without accuracy loss. An Unscented Kalman Filter (UKF) is implemented to fuse WMPM and UWB data and it is improved with a Rauch-Tung-Striebel smoother. An IR-camera system (Optitrack), providing the ground truth, is used to validate the UKF. The solution has a Root Mean Square Error (RMSE) of less than 20 cm in dynamic wheelchair situations. This work provides a basis for further development of a platform where WMPM and UWB are integrated for paralympic sports.

Traditionally, antenna design involves optimizing the design parameters such as gain, minimum sidelobe level, scan range, half power beamwidth, for a particular application. Since 5G systems are pushing the boundaries for cellular communications by introducing unique challenges such as multiple beam antennas, beamforming etc. in the field of antenna design. Although separate studies do exist on these challenges, the concept antenna synthesis using different disciplines is relatively new. This work presents a 5G simulation model using a recently proposed hybrid beamforming technique employing cosecant power flux equalization in elevation plane with digital beamforming in azimuth plane. Various beamforming algorithms in azimuth domain are investigated for concurrent users sharing same frequency spectrum and their impact on system performance such as signal to interference plus noise ratio (SINR) is statistically analyzed. Moreover, the impact of antenna sidelobe levels on system SINR performance is investigated in detail. The simulation results shows that the cosecant subarray hybrid beamforming performs better than traditional hybrid beamforming in terms of SINR for cell edge users. In addition to that, this work provides a unique perspective to system engineers for intuitively analyzing the impact of antenna system on communication link and to derive design requirements that would be crucial in the antenna system synthesis

A phase-domain analog-to-digital converter (PhADC) is a promising alternative to a pair of amplitude-domain in-phase and quadrature (IQ) ADCs for low power FSK/PSK demodulation, but due to the nonlinear amplitude-to-phase conversion, IQ offsets and gain mismatch can produce nonlinear phase distortions which that can lead to phase errors and an increase in bit-error rate (BER). An IQ offset and gain mismatch detection technique is developed for PhADCs and verified. The offset and gain mismatch is estimated by detecting the phase vector distribution imbalance among the four phase quadrants after the analog-to-phase conversion. A feedback path has been constructed between the PhADC output and the offset/mismatch compensation interface. The closed loop will help the compensation interface to settle to the proper compensation values of the offset and mismatch. Incorporating this cancellation loop in a receiver system can improve its sensitivity and robustness. In a conventional IQ ADC receiver we have two quantizations, i.e., one for I and one for Q, and then process the information to extract the phase. By contrast, the PhADC, due to its embedded demodulation attribute, performs only phase quantization. So only one quantization is needed. Because of its compactness, the hardware is simpler and thereby consumes less energy. Moreover the PhADC is immune to magnitude variations, because in an IQ ADC, amplitude quantization noise produces larger phase quantization noise at small vector magnitudes, while in a PhADC a larger vector has the same phase quantization error as a small vector. Because of these advantages the PhADC is a very good candidate for low power communication. A detection algorithm has been developed that detects the phase vector distribution imbalance between the left and right IQ complex half plane in case of I offset and between the top and bottom of IQ complex half plane in case of Q offset. Using this imbalance we can determine the sign and size of IQ offset. A similar approach has been done for IQ gain mismatch, where the phase vector distribution imbalance is detected between the four phase quadrants in the IQ complex plane. A mixed-signal approach, i.e., detecting the offset and mismatch in the digital domain and compensate in the analog domain. It is well known that in the IQ ADC receiver the offset and mismatch can be detected and calibrated if necessary before the amplitude is converted into phase in the digital domain, but in the PhADC receiver the offset and mismatch cannot be determined directly due to the absence of amplitude information. Here, we use phase information rather than amplitude information for detection and compensation. For this reason, we have created a direct mismatch and offset detection technique using the output phase signal of the PhADC. The relation between signal-to-noise power ratio (SNR) and its digital counter parts bit-energy-to-noise density (Eb/No) and symbol-energy-to-noise density (Es/No) is established and is used to show the effect of IQ offset and gain mismatch on the BER as a function of channel and phase quantization noise from the PhADC. It is shown that Eb/No and or Es/No are not the same as SNR and less understood ratios that are often confused with SNR. The relation between SNR and Eb/No, or for higher dimensions (i.e., multiple bits per symbol), the Es/No depends on the modulation parameters. For π/4 DQPSK modulation, the following relationship holds:Eb/No = SNR + 0.97 dB. An ideal PhADC receiver for π/4 DQPSK demodulation, with a noise-free channel, can tolerate a maximum IQ offset of 28 mV and a gain mismatch of ± 25 dB for a required BER of 10-5 according to the IEEE802.15.6 standard. But with a channel noise of SNR= 21dB these become 22 mV and ± 6 dB, respectively. A practical PhADC receiver with the same channel noise can tolerate a maximum IQ offset of 14mV and a gain mismatch of ± 3 dB. An approach is presented to convert the PhADC receiver analog channel select filter to a digital one for discrete modeling purposes in Matlab Simulink. First, the Laplace transfer functions of the filter stages and from those the overall Laplace transfer function of the total filter are derived. A mapping procedure is proposed to convert the continuous time domain Laplace transfer function to a discrete one.

LoRa (Long Range) is a low-power, long-range and low-cost wireless communication system that can facilitate a wide variety of infrastructures for the Internet of Things (IoT). Current algorithms to locate LoRa tags have a resolution of 100 m in practice, and a question is if that can be improved without changing the tags or adding too much to the gateways (basestations). Conventional delay estimation ranging algorithms extract useful information from the channel frequency response and use this information to estimate delays. In this thesis, three localization techniques are presented: the matched filter, FBCM-MUSIC and TLS-ESPRIT algorithms. Then a multiband architecture is proposed and integrated into the matched filter. These algorithms are implemented in the LoRa system model. The simulations indicate that FBCM-MUSIC and TLS-ESPRIT have better performance than the matched filter in NLOS channels. The results also show that TLS-ESPRIT is more effective and robust compared to MUSIC. The proposed multiband architecture can improve the resolution of TOA estimation and decreases the 90th percentile error by around 40%.

LoRa is being widely adopted by industrial communities for its long range, robustness and low power wireless communication capabilities. In fact LoRa is gaining more popularity even amongst the common people as it is an affordable solution and operates in the unlicensed radio spectrum. However, LoRa provides a widely heterogeneous coverage; it can reach hundreds of meters or up to tens of kilometers, depending on the surrounding environment. Determining the coverage of LoRa stations is key to provide a good quality of service. On one hand, the traditional method of expensive measurement campaigns can be employed to estimate LoRa's coverage; but this is impractical due to the large geographical areas involved. On the other hand, popular channel models can be adopted; but many of them are yet to be explored for LoRa or rely entirely on the user predening the type of environment to estimate coverage. Neither of those approach are suitable for thousands of non-expert citizens and organizations around the world looking forward to understanding the coverage of their LoRa stations. The aim of the thesis is to automatically estimate the coverage of LoRa, before the deployment of the gateway and without relying on on-site measurements or the user's perception of the environment. Moreover, the estimation must be carried out in a simple, low cost and low eort approach. Considering that the surrounding environment determines in a fundamental manner, the coverage of wireless technologies including LoRa, we use readily available remote sensing information coming from satellites to estimate the characteristics of an area. In this manner, we free up the user from providing any type of data. Based on this remote sensing approach, the thesis provides two main contributions: First we analyze a group of parametric models (ITU-R 1812 and Okumura Hata model) and determine that the Okumura Hata model is better suited for LoRa. Second we improve the performance of using the basic Okumura Hata model by proposing an automated approach that explores remotely sensed height models and land cover maps to automatically congure channel model parameters. The performance is evaluated based on a relative comparison due to some unknown transmitter setting parameters and assess which algorithm accurately tracks the changes in the real path loss. A validation using a relative comparison approach on 18000+ samples of real LoRa data shows that the modied algorithm gives an improved performance compared to the novel approach in path loss prediction and the ITU model. The modied algorithm could improve the coverage up to a factor of 5 compared to the novel approach in free space ranges. Moreover, in an urban built-up city the modied algorithm could improve the coverage by up to 1.5 km compared to the novel approach.

Indoor positioning has several variants as a result of multiple years of study on the topic. Using WiFi signals as the technology to compute the position of the target device is one of the most extended and researched techniques. WiFi Access Points are extensively deployed in all indoor environments where WiFi indoor localization has a potential application. Several of these indoor localization techniques use the Received Signal Strength (RSS) to compute the location of the device. However, the accuracy of the methods that use this parameter is usually low, in the meter range. Eight years ago, the new advances in wireless communications allowed to retrieve the phase of an incoming signal from a commercial chipset, and not only its strength. With the phase, we can use the physical and mathematical principles of signal transmission to compute the distance to a device. In the long term, it can contribute to having a more robust and long-lasting method to perform indoor localization if we can overcome the challenge of obtaining a delay-free phase measurement. For indoor distances, a small delay in the time estimation can be translated into a significant error in the ranging result. In this work, we re-implement the ranging technique of the paper Chronos: Decimeter-Level Localization with a Single WiFi Access Point. This well-known research work explains how to obtain an accurate phase measurement from a WiFi chipset and the technique to compute the distance to the target. We provide a guide of the installation and implementation of the hardware and software required for a system like this, indicating the critical points to allow future researchers a quick set up of the equipment. We revisit the procedure of Chronos to obtain a delay-free phase measurement and show how to re-implement it from scratch. Finally, we perform a validation of the system in four different steps, from the use of ideal data to progressively introducing the real distortions of indoor wireless data. The evaluation of the performance of the system leads us to present the finding of a non-linear delay that can produce significant distance errors.