Ultra-wideband Devices Research Articles

Testing Time Optimization Method for IEEE 802.15.4z Ultra-wideband Integrated Circuits

IEEE 802.15.4z-compliant ultra-wideband (UWB) devices are becoming ever more popular in contemporary radio engineering systems. Such systems are capable of precisely measuring distances (with their accuracy expressed in centimeters), are immune to interference, offer low latency and transmit data in an energy-efficient manner. Widespread adoption of UWB technology has triggered significant demand for testing integrated circuits these systems rely on, prompting the development of new testing methods to meet the ever increasing requirements in terms of testing speed and reliability. The same applies to sensitivity tests, in the course of which up to 2000 different packets may be received. The process of generating and analyzing such a large number of packets is time consuming. Furthermore, if multiple devices need to be tested simultaneously, the duration of the test will be multiplied accordingly. In such a context, the article investigates the lead time required to generate 2000 UWB packets using conventional methods and proposes a novel approach to significantly reduce packet generation time and improve testing efficiency.

Leveraging Attention-reinforced UWB Signals to Monitor Respiration during Sleep

The respiration state during overnight sleep is an important indicator of human health. However, existing contactless solutions for sleep respiration monitoring either perform in controlled environments and have low usability in practical scenarios or only provide coarse-grained respiration rates, being unable to accurately detect abnormal events in patients. In this article, we propose Respnea, a non-intrusive sleep respiration monitoring system using an ultra-wideband device. Particularly, we propose a profiling algorithm, which can locate the sleep positions in non-controlled environments and identify different subject states. Further, we construct a deep learning model that adopts a multi-head self-attention mechanism and learns the patterns implicit in the respiration signals to distinguish sleep respiration events at a granularity of seconds. To improve the generalization of the model, we propose a contrastive learning strategy to learn a robust representation of the respiration signals. We deploy our system in hospital and home scenarios and conduct experiments on data from healthy subjects and patients with sleep disorders. The experimental results show that Respnea achieves high temporal coverage and low errors (a median error of 0.27 bpm) in respiration rate estimation and reaches an accuracy of 94.44% on diagnosing the severity of sleep apnea-hypopnea syndrome.

Hypnos: A Contactless Sleep Stage Monitoring System Using UWB Signals

As a fundamental physiological process, sleep plays a vital role in human health. High-quality sleep requires a reasonable distribution of sleep duration over different sleep stages. Recently, contactless solutions have been used for in-home sleep stage monitoring via wireless signals as it enables monitoring daily sleep in a non-intrusive manner. However, various factors, such as the subject's physiological characteristics during sleep, the subject's health status, and even the sleep environment, pose challenges to wireless signal analysis. In this paper, we propose Hypnos, a contactless sleep monitoring system that identifies different sleep stages using an ultra-wideband (UWB) device. Hypnos enables automated bed localization and extracts signals containing coarse-grained body movements and fine-grained chest movements due to breathing and heartbeat from the subject, which acts as the preparation step for sleep staging. The key to our system is a seq2seq deep learning model, which adopts an attention-based sequence encoder to learn the patterns and transitions within and between sleep epochs and combines with contrastive learning to improve the generalizability of the encoder. Particularly, we incorporate sleep apnea detection as an auxiliary task into the model to reduce the interference of sleep apnea with sleep staging. Moreover, we design a two-step training for better adaptation of subjects with different severities of sleep disorders. We conduct extensive experiments on 100 subjects, including healthy individuals and patients with sleep disorders, and the experimental results show that Hypnos achieves excellent performance in multi-stage sleep classification (including 5-stage sleep classification), and outperforms other baseline methods.

Push the Limit of Highly Accurate Ranging on Commercial UWB Devices

Ranging plays a crucial role in many wireless sensing applications. Among the wireless techniques employed for ranging, Ultra-Wideband (UWB) has received much attention due to its excellent performance and widespread integration into consumer-level electronics. However, the ranging accuracy of the current UWB systems is limited to the centimeter level due to bandwidth limitation, hindering their use for applications that require a very high resolution. This paper proposes a novel system that achieves sub-millimeter-level ranging accuracy on commercial UWB devices for the first time. Our approach leverages the fine-grained phase information of commercial UWB devices. To eliminate the phase drift, we design a fine-grained phase recovery method by utilizing the bi-directional messages in UWB two-way ranging. We further present a dual-frequency switching method to resolve phase ambiguity. Building upon this, we design and implement the ranging system on commercial UWB modules. Extensive experiments demonstrate that our system achieves a median ranging error of just 0.77 mm, reducing the error by 96.54% compared to the state-of-the-art method. We also present three real-life applications to showcase the fine-grained sensing capabilities of our system, including i) smart speaker control, ii) free-style user handwriting, and iii) 3D tracking for virtual-reality (VR) controllers.

Research on collaborative localization technology of UAVs based on INS and UWB

The trend of miniaturization and low-cost development in cluster systems restricts the ability of all UAVs within the cluster system to be equipped with expensive high-precision navigation equipment. Relying solely on their low-precision INS (inertial navigation system) will cause navigation errors to quickly diverge. To improve the navigation accuracy of UAVs, a distributed collaborative localization method combining leader and wingman is proposed, and the corresponding mathematical model is derived. The wingman obtains the position information and distance information of the leader through UWB (Ultra-Wide Band) devices and then applies the Kalman filter algorithm to fuse it with its inertial navigation solution information, thereby improving the positioning accuracy of the wingman. On this basis, to address the issue of height channel divergence when the number of leaders decreases, it is proposed to add a barometer and maintain collaborative positioning accuracy by introducing height information assistance. Finally, the feasibility of this method was verified through mathematical simulation, and the simulation results show that compared with inertial navigation, the collaborative navigation and positioning method is more suitable for long-endurance navigation.

Integrated Localization and Planning for Cruise Control of UGV Platoons in Infrastructure-Free Environments

This paper investigates the cruise control problem of unmanned ground vehicle (UGV) platoons from the implementation perspective. Unlike most existing works related to platoon cruise control which rely on positioning infrastructures such as lane markings, roadside units, and global navigation satellite systems (GNSS), this paper explores a new problem: platoon cruise control in environments without positioning infrastructures. The introduction of this constraint disables most existing cruise control approaches. To address this problem, an integrated localization and planning framework is proposed, which is composed of three modular algorithms. Firstly, to localize multiple vehicles in a common coordinate system, a collaborative localization algorithm is developed through matching local perceptions of different vehicles. Secondly, to maintain the desired platoon configuration, the historical trajectory of the preceding vehicle is reconstructed, based on which the target state is planned for the following vehicle. Finally, a virtual controller based algorithm is designed to generate feasible trajectories for the following vehicle in real time. The proposed framework has two salient features. Firstly, it does not depend on positioning infrastructures and does not introduce additional positioning sensors, such as GNSS/INS modules, ultra-wideband (UWB) devices, magnetic meters and so on, as long as each vehicle is equipped with a perception sensor (Lidar, radar or camera), which however is essential equipment for nowaday autonomous systems. Secondly, the proposed framework does not depend on direct observations between vehicles to achieve relative localization, making it applicable in non-line-of-sight (non-LOS) situations. Real-world experiments have been conducted to validate the effectiveness, robustness and practicality of the proposed framework.

Ranging and multipath‐enhanced device‐free localisation with densely‐meshed ultra‐wideband devices

AbstractDevice‐free localisation (DFL) is a prominent example of radio sensing and radio frequency (RF)‐based passive localisation. RF‐based passive localisation approaches determine the position of a non‐cooperative user based on the user's impact on radio propagation. In this regard, DFL systems measure user‐induced changes in the properties of the received RF signals. With multipath‐enhanced device‐free localisation (MDFL), a novel passive localisation approach which is taking the advantage of user‐induced fading in the multipath signals, that is, reflected and scattered signals is introduced. In this work, the authors realise an MDFL system using low‐cost ultra‐wideband (UWB) devices. Specifically, the Qorvo (DecaWave) DW1000 module is used, for which how to access the channel impulse response is described in detail. Additionally, an overview of the required signal processing for MDFL is provided and a possible sequential Bayesian approach is introduced. Moreover, an efficient ranging scheme based on time‐division multiple access (TDMA) and message broadcasting is outlined, which allows the deployment of a large number of interconnected UWB devices. Using an exemplary network of interconnected UWB devices, the localisation performance of both DFL and MDFL for an indoor scenario is evaluated. Thereby, MDFL is shown to clearly outperform DFL in terms of robustness and accuracy. Furthermore, a TDMA‐based ranging scheme for active localisation is used, that is, for localising an UWB device carried by the user, allowing for a direct comparison between active and passive localisation. Achieving a sub‐decimetre accuracy, the active localisation outperforms both DFL and MDFL, and thus, shows the possibility of using an active localisation device to initialize MDFL.

UWB Positioning System Based on LSTM Classification With Mitigated NLOS Effects

It is known that an ultrawideband (UWB)-based indoor positioning system (IPS) has superior positioning performance and can meet the requirements of location-based services (LBSs) as the Internet of Things (IoT) applications. However, there is a limitation of UWB positioning when it is conducted at the nonline-of-sight (NLOS) channels degrading the UWB ranging accuracy at indoor environments. In this article, we propose an artificial intelligence (AI) applied UWB positioning system that can enhance the positioning performance by classifying channel conditions with channel impulse response (CIR) of the received UWB signal. The proposed system mitigates the positioning degradation caused by the NLOS situations by performing extended Kalman filter (EKF) localization and long short-term memory (LSTM) training of the observed channel status. The main feature of the proposed UWB positioning method is that it can be used even at unknown locations not trained with the LSTM model learning the channel status, because of our training strategy of not the position coordinates, but the UWB ranging error between UWB devices corresponding to CIR of the received UWB signal. This article provides the experimental setup and performance evaluation results of the proposed system. The evaluation results showed that the proposed AI-applied UWB positioning method significantly improved its accuracy performance compared with the existing positioning methods.

Passive IR-UWB Localization System for UAV-Based Electric Facility Inspection During GPS Outage

A practical localization system is proposed for a substation inspection unmanned aerial vehicle (UAV) performing its mission under global positioning system (GPS) signal blockage. The sensor hardware consists of a single transmitter and a cruciform receiver array, which produces the range difference (RD) information used for UAV positioning. The use of impulse-radio ultra wide-band (IR-UWB) devices secures the robustness against RF interference often caused by an exogenous electromagnetic field. With this hardware configuration, the UAV localization can be formulated as the state estimation problem for an uncertain linear state space model and be solved by using the computationally efficient robust weighted least squares (RWLS) estimator. Since the standard RWLS estimator could be sensitive to the imperfectness of prior knowledge on the noise statistic, a geometric constraint expressed in terms of a UAV position is exploited to secure the reliable localization performance in practice. Through experimental results, it is verified that the proposed solution provides reliable UAV positioning performance despite using the imperfect measurement noise statistics for the localization system.

The Small UWB Monopole Antenna with Stable Omnidirectional Radiation Pattern

Ultra Wideband (UWB) technology is an unmodulated wireless digital communication system that uses an extremely short duration pulse to transmit information bit. Because of this pulse, the UWB system needs a very wide bandwidth. Federal Communication Commission (FCC) has regulated the 3.1 – 10.6 GHz frequency spectrum for UWB. Since FCC released this frequency, many research in telecommunication have been done on UWB systems. One of them is a development of an Antenna that is suitable for UWB devices. UWB antenna characteristics require FCC band, omnidirectional radiation pattern, and compact size. In order to meet these needs, an antenna with a simple structure in the form of a monopole patch antenna with a similar patch size and ground width has been designed. The antenna is built on an FR4 – epoxy substrate material, with 4.4 dielectric constant and 1.6 mm thickness. The antenna feeding structure consists of two 100 Ω and 50 Ω lines with a wideband impedance matching scheme using tapered side and tapered transformers. The antenna design and optimization processes are conducted using electromagnetic simulation software, and measurements are carried out in an anechoic chamber. Simulation and measurement results show good agreement, and the antenna can work at frequencies 3.5 - 11.3 GHz with a gain of 1.5 – 3.25 dBi and stable omnidirectional radiation patterns. The antenna has dimensions of 27 × 8 × 1.6 mm, which are smaller than the antenna reported in the last research and suitable to be applied on various UWB devices.

ECG-grained Cardiac Monitoring Using UWB Signals

With the development of wireless sensing, researchers have proposed many contactless vital sign monitoring systems, which can be used to monitor respiration rates, heart rates, cardiac cycles and etc. However, these vital signs are ones of coarse granularity, so they are less helpful in the diagnosis of cardiovascular diseases (CVDs). Considering that electrocardiogram (ECG) is an important evidence base for the diagnoses of CVDs, we propose to generate ECGs from ultra-wideband (UWB) signals in a contactless manner as a fine-grained cardiac monitoring solution. Specifically, we analyze the properties of UWB signals containing heartbeats and respiration, and design two complementary heartbeat signal restoration methods to perfectly recover heartbeat signal variation. To establish the mapping between the mechanical activity of the heart sensed by UWB devices and the electrical activity of the heart recorded in ECGs, we construct a conditional generative adversarial network to encode the mapping between mechanical activity and electrical activity and propose a contrastive learning strategy to reduce the interference from noise in UWB signals. We build the corresponding cardiac monitoring system named RF-ECG and conduct extensive experiments using about 120,000 heartbeats from more than 40 participants. The experimental results show that the ECGs generated by RF-ECG have good performance in both ECG intervals and morphology compared with the ground truth. Moreover, diseases such as tachycardia/bradycardia, sinus arrhythmia, and premature contractions can be diagnosed from the ECGs generated by our RF-ECG.

Photonics-based modular multistate digital coherent system

Objectives. The study aimed to develop interspecies and interclass methods for constructing coherent radio engineering systems based on a modular complementary structure.Methods. A set of modules and submodules having no narrow specialization and together constituting a flexible broadband hardware-reconfigurable software-defined radio engineering structure is considered as the basic set for constructing a digital radio photonic system path. Due to their broadbandness and complementary structure, modules and submodules have many applications both as self-sustained devices and as part of more complex systems.Results. Functional diagrams of modern digital receiver-shapers, as well as modules for amplifying radio frequency signals and converting radio frequency signals into an optical signal are presented along with a radio photonic synchronization network for generating clock signals. Calculations of the introduced phase error of a quartz singlemode fiber and graphs of the dependence of the change in the signal phase on external influencing factors are given. A concept for integrating the presented modules into the construction of a modular transceiver multiposition wideband coherent digital radio photonic system is proposed. The results of calculating radiation patterns and mathematical modeling the beam deflection of a broadband antenna array are presented along with antenna systems based thereon.Conclusions. The proposed circuit design solutions allow the time required for developing new types of systems to be significantly reduced due to the range of ready-made technical solutions. Not only are the parameters of the developed devices comparable to the best world analogues, but they also surpass existing solutions in terms of system integration. The developments have been tested under R&D project at the Kaluga Scientific Research Institute of Radio Technology and Hardware Solution Technologies (TAR). The proposed solutions are integrated at the subsystem level into advanced developments of products for civil and special purpose. Further development of the concept of building ultra-wideband devices allows reaching a new level in the technology of constructing modular multiposition coherent digital radio photonic systems.

High-Accuracy Ranging and Localization With Ultrawideband Communications for Energy-Constrained Devices

Ultrawideband (UWB) communications have gained popularity in recent years for being able to provide distance measurements and localization with high accuracy, which can enhance the capabilities of devices in the Internet of Things (IoT). Since energy efficiency is of utmost concern in such applications, in this work, we evaluate the power and energy consumption, distance measurements, and localization performance of two types of UWB physical interfaces (PHYs), which use either a low- or high-rate pulse repetition (LRP and HRP, respectively). The evaluation is done through measurements acquired in identical conditions, which is crucial in order to have a fair comparison between the devices. We performed measurements in typical line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. Our results suggest that the LRP interface allows a lower power and energy consumption than the HRP one. Both types of devices achieved ranging and localization errors within the same order of magnitude and their performance depended on the type of NLOS obstruction. We propose theoretical models for the distance errors obtained with LRP devices in these situations, which can be used to simulate realistic building deployments and we illustrate such an example. This article, therefore, provides a comprehensive overview of the energy demands, ranging characteristics, and localization performance of state-of-the-art UWB devices.

An Overview of UWB Standards and Organizations (IEEE 802.15.4, FiRa, Apple): Interoperability Aspects and Future Research Directions

The increasing popularity of ultra-wideband (UWB) technology for location-based services, such as access control and real-time indoor track&tracing, as well as UWB support in new consumer devices such as smartphones, has resulted in the availability of multiple new UWB radio chips. However, due to this increase in UWB device availability, the question of which (industry) standards and configuration factors impact UWB interoperability and compatibility becomes increasingly important. In this paper, the fundamentals of UWB compatibility are investigated by first giving an overview of different UWB radio chips on the market. After that, an overview of UWB standards and organizations is given. Next, this overview is used to discuss the focus of these different standards and to identify the differences between them. We describe compatibility issues and associated interoperability aspects related to physical (PHY), medium-access-control (MAC) and upper layers. For the PHY layer, compatibility is possible for all UWB radio chips if the correct settings are configured. For the MAC layer, the implementation of the multiple access scheme as well as the localization technique is mostly proprietary. For the device discovery, several standards are currently being drafted. Finally, future challenges related to UWB interoperability are discussed.

Device-Free Pedestrian Tracking Using Low-Cost Ultrawideband Devices

Ultrawideband (UWB) attracts extensive attention for the Internet-of-Things applications, especially the fine-grained location-based services. Rather than active tracking, this article explores the UWB-based device-free pedestrian tracking problem. Concerning the challenges of fine-grained passive tracking for the low-cost commodity UWB devices, we propose a variance-based temporary-spatial (VATS) mapping algorithm, which relieves the background interference from the perspective of the Bayesian framework. Moreover, a particle filter algorithm has been designed to track the position likelihood changing and to avoid likelihood ambiguity. Experimental results show that the proposed VATS mapping algorithm achieves 50th and 90th percentile errors 0.156 and 0.272 m, respectively, which is promising for practical applications.

Autonomous Navigation System for a Delivery Drone

The use of delivery services is an increasing trend worldwide, further enhanced by the COVID pandemic. In this context, drone delivery systems are of great interest as they may allow for faster and cheaper deliveries. This paper presented a navigation system that makes feasible the delivery of parcels with autonomous drones. The system generates a path between a start and a final point and controls the drone to follow this path based on its localization obtained through GPS, 9DoF IMU, and barometer. In the landing phase, information of poses estimated by a marker (ArUco) detection technique using a camera, ultrawideband (UWB) devices, and the drone’s software estimation are merged by utilizing an extended Kalman filter algorithm to improve the landing precision. A vector field-based method controls the drone to follow the desired path smoothly, reducing vibrations or harsh movements that could harm the transported parcel. Real experiments validate the delivery strategy and allow the evaluation of the performance of the adopted techniques. Preliminary results state the viability of our proposal for autonomous drone delivery.

Where do we find missing data in a commercial real-time location system? Evidence from 2 dairy farms

Real-time indoor positioning using ultra-wideband devices provides an opportunity for modern dairy farms to monitor the behavior of individual cows; however, missing data from these devices hinders reliable continuous monitoring and analysis of animal movement and social behavior. The objective of this study was to examine the data quality, in terms of missing data, in one commercially available ultra-wideband–based real-time location system for dairy cows. The focus was on detecting major obstacles, or sections, inside open freestall barns that resulted in increased levels of missing data. The study was conducted on 2 dairy farms with an existing commercial real-time location system. Position data were recorded for 6 full days from 69 cows on farm 1 and from 59 cows on farm 2. These data were used in subsequent analyses to determine the locations within the dairy barns where position data were missing for individual cows. The proportions of missing data were found to be evenly distributed within the 2 barns after fitting a linear mixed model with spatial smoothing to logit-transformed proportions (mean = 18% vs. 4% missing data for farm 1 and farm 2, respectively), with the exception of larger proportions of missing data along one of the walls on both farms. On farm 1, the variation between individual tags was large (range: 9–49%) compared with farm 2 (range: 12–38%). This greater individual variation of proportions of missing data indicates a potential problem with the individual tag, such as a battery malfunction or tag placement issue. Further research is needed to guide researchers in identifying problems relating to data capture problems in real-time monitoring systems on dairy farms. This is especially important when undertaking detailed analyses of animal movement and social interactions between animals.

ASSESSMENT OF CAR COLLABORATIVE POSITIONING WITH UWB AND VISION

Abstract. During the last decades the role of positioning and navigation systems is drastically changed in the everyday life of common people, influencing people behavior even multiple times each day. One of the most common applications of this kind of systems is that of terrestrial vehicle navigation: the use of GPS in the automotive navigation sector started thirty years ago, and, nowadays, it commonly assists drivers in reaching most of their non-standard destinations. Despite the popularity of global navigation satellite systems (GNSS), their usability is quite limited in certain working conditions, such as in urban canyons, in tunnels and indoors. While the latter case is typically not particularly interesting for the automotive sector, the first two scenarios represent important cases of interest for automotive navigation. In addition to the market request for increasing the usability of navigation systems on consumer devices, the recent increasing eagerness for autonomous driving is also attracting a lot of researchers’ attention on the development of alternative positioning systems, able to compensate for the unavailability or unreliability of GNSS. In accordance with the motivations mentioned above, this paper focuses on the development of a positioning system based on collaborative positioning between vehicles with UltraWide-Band devices and vision. To be more specific, this work focuses on assessing the performance of the developed system in successfully accomplishing three tasks, associated to different levels of gathered information: 1) assessing distance between vehicles, 2) determining the vehicle relative positions, 3) estimating the absolute car positions. The obtained results show that a) UWB can be reliably used (error of few decimeters error) to assess distances when vehicles are relatively close to each other (e.g. less than 40 m), b) the combination of UWB and vision allows to obtain good results in the computation of relative positions between vehicles, c) UWB-based collaborative positioning can be used for determining the absolute vehicle positions if a sufficient number of UWB range measurements can be ensured (sub-meter error for vehicles connected with a static UWB infrastructure, whereas error at meter level for those exploiting only vehicle-to-vehicle UWB communications).

Human Sensing in Reverberant Environments: RF-Based Occupancy and Fall Detection in Ships

In this paper, we explore the possibility of estimating the number of people inside a below-deck ship compartment using the theory of room electromagnetics. Most RF-based occupancy detection solutions focus on residential environments. Confined metallic spaces such in industrial environments are more hostile and exhibit features of a reverberant cavity. The theory of room electromagnetics provides a simple characterization of microwave propagation in such environments. By considering the indoor environment as a lossy cavity, the exponential decay rate of the power-delay profile (PDP), also known as reverberation time (RT), is related to the total absorption inside the room. First, we verify the reverberating nature of the room by measuring the RT at different locations inside the room. The PDPs are calculated from the channel impulse response (CIR) measured using the MIMOSA radio channel sounder. Then, the relation between RT and the number of people inside the room is investigated. We show that it is possible to estimate the number of stationary people with a good accuracy, depending on the number of antennas used. With a success rate of 88%, the estimation error is only one person when 16 spatially averaged PDPs are used. Higher success rates are achievable with more spatial averaging. Moreover, off-the-shelf (OTS) ultra wide band (UWB) devices are used to estimate the number of people inside the same room. Results show that temporal averaging of PDPs can further improve the success rate to 95% when people inside the room are moving. In addition, the detection of a lone person falling to the ground is investigated based on the Doppler analysis of the measured CIRs. It is shown that the Doppler spread in case of a fall has higher peak values compared to normal activities, such as walking and sitting. With the use of a simple Bayes classifier, a fall is detected with 98% accuracy and 100% sensitivity.

Map-aided and UWB-based anchor placement method in indoor localization

Nowadays, ultra wideband (UWB) has been popular in indoor positioning systems. Because of obstacles such as walls, doors, desks and pedestrians in the indoor area, UWB devices have to be conducted in a non-line-of-sight (NLOS) environment. The placement of nodes has significant influences on the performance of localization. In this paper, an anchor placement method for the target’s trajectory based on genetic heuristic differential evolution algorithm is proposed to improve the UWB localization accuracy. To be specific, in an area with low anchor densities, a target does not have enough anchors for multilateration localization; thus, a coverage degree criterion is defined. Meanwhile, the Cramer–Rao lower bound (CRLB) is used as an evaluation metric for localization accuracy, and both of CRLB and coverage degree criterion are incorporated into the evaluation function of the differential evolution (DE) algorithm. Furthermore, instead of using the liner distance path loss model, the more practical UWB-based through-wall signal propagation model is adopted to reflect the influences of obstacles that are widespread in indoor environments. In addition, a software application is developed to visualize the indoor scenario, signal propagation status and anchor placement results. Finally, field experiments and simulations are performed, and a thorough case study confirms the effectiveness of the proposed method. The average localization error of the proposed placement scheme can be reduced by 28.2% and 12.5% compared to the random scheme and the default DE-based scheme.