Longning Qi

Bio: Longning Qi is an academic researcher from Southeast University. The author has contributed to research in topics: Extended Kalman filter & Kalman filter. The author has an hindex of 8, co-authored 21 publications receiving 698 citations.

A Survey of Positioning Systems Using Visible LED Lights

Abstract: As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.

Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons.

Abstract: Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target’s location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy) with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy). The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of <2.56 m at 90% of the time with dense deployment of BLE beacons (1 beacon per 9 m), which performs 35.82% better than <3.99 m from the Propagation Model (PM) + EKF algorithm and 15.77% more accurate than <3.04 m from the FP + EKF algorithm. With sparse deployment (1 beacon per 18 m), the proposed algorithm achieves the accuracies of <3.88 m at 90% of the time, which performs 49.58% more accurate than <8.00 m from the PM + EKF algorithm and 21.41% better than <4.94 m from the FP + EKF algorithm. Therefore, the proposed algorithm is especially useful to improve the localization accuracy in environments with sparse beacon deployment.

A Two-Filter Integration of MEMS Sensors and WiFi Fingerprinting for Indoor Positioning

Abstract: Indoor positioning has become increasingly important in the past decade Some approaches for the integration of micro-electro-mechanical systems (MEMS) sensors and WiFi fingerprinting (FP) have been proposed for indoor positioning However, most of the existing integration approaches only focus on aiding MEMS sensors by WiFi FP This letter proposes a two-filter integration for MEMS sensors and WiFi FP In the proposed approach, the integrated positioning solution is used to constrain the search space of WiFi FP, and achieve a constrained constrained FP (CFP) solution Then, a Kalman filter serves for obtaining a smoothed CFP solution (SCFP) Finally, an extended Kalman filter serves for the integration of SCFP and MEMS sensors Field tests show the proposed integration approach can improve both positioning accuracy and computational efficiency

A Pervasive Integration Platform of Low-Cost MEMS Sensors and Wireless Signals for Indoor Localization

Abstract: Location service is fundamental to many Internet of Things applications such as smart home, wearables, smart city, and connected health. With existing infrastructures, wireless positioning is widely used to provide the location service. However, wireless positioning has the limitations such as highly depending on the distribution of access points (APs); providing a low sample-rate and noisy solution; requiring extensive labor costs to build databases; and having unstable RSS values in indoor environments. To reduce these limitations, this paper proposes an innovative integrated platform for indoor localization by integrating low-cost microelectromechanical systems (MEMS) sensors and wireless signals. This proposed platform consists of wireless AP localization engine and sensor fusion engine, which is suitable for both dense and sparse deployments of wireless APs. The proposed platform can automatically generate wireless databases for positioning, and provide a positioning solution even in the area with only one observed wireless AP, where the traditional trilateration method cannot work. This integration platform can integrate different kinds of wireless APs together for indoor localization (e.g., WiFi, Bluetooth low energy, and radio frequency identification). The platform fuses all of these wireless distances with low-cost MEMS sensors to provide a robust localization solution. A multilevel quality control mechanism is utilized to remove noisy RSS measurements from wireless APs and to further improve the localization accuracy. Preliminary experiments show the proposed integration platform can achieve the average accuracy of 3.30 m with the sparse deployment of wireless APs (1 AP per 800 m2).

Low-Power Centimeter-Level Localization for Indoor Mobile Robots Based on Ensemble Kalman Smoother Using Received Signal Strength

Abstract: How to provide a low-cost but accurate localization solution for the indoor mobile robots are essential in many Internet of Things applications, such as smart home and asset tracking. To achieve this goal, this paper originally proposes a modified two-filter smoother based on ensemble Kalman filter (KF) (denoted as EnKS) for the localization of indoor mobile robots. The proposed EnKS algorithm consists of both a forward part of an ensemble KF (EnKF) with statistical linear regression and a backward part of a modified information KF with state error vector. The EnKS based on stochastic sampling with ensemble members can achieve better positioning accuracy than other Kalman smoothers. When compared to EnKF, the proposed EnKS combines a backward filter to compensate for the estimation error of EnKF and further improves the accuracy. Furthermore, the implementation of the proposed EnKS is conducted in the real world visible light positioning (VLP) system using pre-existing LED lights for low-cost robot localization. To make a performance comparison, this paper also uses baseline smoothers based on extended KF and central difference KF in the VLP system. Preliminary experimental results imply that the proposed EnKS is able to achieve the best positioning accuracy, as high as 11.18 cm on average, but with a comparable computational complexity, which enables to meet the demands of many robot applications.

The Road Towards 6G: A Comprehensive Survey

Abstract: As of today, the fifth generation (5G) mobile communication system has been rolled out in many countries and the number of 5G subscribers already reaches a very large scale. It is time for academia and industry to shift their attention towards the next generation. At this crossroad, an overview of the current state of the art and a vision of future communications are definitely of interest. This article thus aims to provide a comprehensive survey to draw a picture of the sixth generation (6G) system in terms of drivers, use cases, usage scenarios, requirements, key performance indicators (KPIs), architecture, and enabling technologies. First, we attempt to answer the question of "Is there any need for 6G?" by shedding light on its key driving factors, in which we predict the explosive growth of mobile traffic until 2030, and envision potential use cases and usage scenarios. Second, the technical requirements of 6G are discussed and compared with those of 5G with respect to a set of KPIs in a quantitative manner. Third, the state-of-the-art 6G research efforts and activities from representative institutions and countries are summarized, and a tentative roadmap of definition, specification, standardization, and regulation is projected. Then, we identify a dozen of potential technologies and introduce their principles, advantages, challenges, and open research issues. Finally, the conclusions are drawn to paint a picture of "What 6G may look like?". This survey is intended to serve as an enlightening guideline to spur interests and further investigations for subsequent research and development of 6G communications systems.

A Survey of Positioning Systems Using Visible LED Lights

Abstract: As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.

The Road Towards 6G: A Comprehensive Survey

Abstract: As of today, the fifth generation (5G) mobile communication system has been rolled out in many countries and the number of 5G subscribers already reaches a very large scale It is time for academia and industry to shift their attention towards the next generation At this crossroad, an overview of the current state of the art and a vision of future communications are definitely of interest This article thus aims to provide a comprehensive survey to draw a picture of the sixth generation (6G) system in terms of drivers, use cases, usage scenarios, requirements, key performance indicators (KPIs), architecture, and enabling technologies First, we attempt to answer the question of “Is there any need for 6G?” by shedding light on its key driving factors, in which we predict the explosive growth of mobile traffic until 2030, and envision potential use cases and usage scenarios Second, the technical requirements of 6G are discussed and compared with those of 5G with respect to a set of KPIs in a quantitative manner Third, the state-of-the-art 6G research efforts and activities from representative institutions and countries are summarized, and a tentative roadmap of definition, specification, standardization, and regulation is projected Then, we identify a dozen of potential technologies and introduce their principles, advantages, challenges, and open research issues Finally, the conclusions are drawn to paint a picture of “What 6G may look like?” This survey is intended to serve as an enlightening guideline to spur interests and further investigations for subsequent research and development of 6G communications systems

Visible Light Communication: Concepts, Applications and Challenges

Abstract: During the last decade, the exponential growth of mobile devices and wireless services created a huge demand for radio frequency-based technologies. Meanwhile, the lighting industry has been revolutionized due to the popularization of LED light bulbs, which are more economical and efficient. In that context, visible light communication (VLC) is a disruptive technology based on LEDs that offers a free spectrum and high data rate, which can potentially serve as a complementary technology to the current radio frequency standards. In this paper, we present a comprehensive state-of-the-art survey of VLC, as well as the main concepts and challenges related to this emergent area. We overview VLC technology, from its physical aspects and communication architecture to its main applications and research challenges. Finally, we present the main research platforms available today, along with a deep analysis of the system design and future directions in the field.