Kaihua Liu

MaPIT: An Enhanced Pending Interest Table for NDN With Mapping Bloom Filter

Named Data Networking (NDN) is a recent paradigm conceived for future Internet architectures, where communications are driven by contents instead of host addresses. To realize this paradigm, a novel data structure for forwarding processes, namely Pending Interest Table (PIT), is utilized in NDN node. Designing and evaluating a quick enough PIT with high capacity is a major challenge within the overall NDN research area. In this letter, based on our proposed Mapping Bloom filter, which is a modified data structure of Bloom filter, we present an enhanced implementation of PIT called MaPIT. Our evaluations indicate that MaPIT can minimize the on-chip memory consumption to 2.097 MB. And the probability of false positive is under 1% for 2 million names. It allows MaPIT to use SRAM as on-chip memory and satisfy the current network requirements.

An anti-collision algorithm based on smart antenna in RFID system

In radio frequency identification (RFID) system, one of the problems we must solve is the collision between tags which lowers the efficiency of RFID system. Now, most of the popular anti-collision algorithms are based on time division multiple access (TDMA) and the space distributing characteristic of tags is not considered. In this paper, a novel algorithm based on smart antenna is proposed. Fast Fourier transform (FFT) algorithm is adopted to produce fixed equally spaced beams which divide the reader field into several sub- spaces. Tags in different sub-spaces can be distributed in the same time slot and frequency. This algorithm is fully compatible with other anti-collision algorithms and can be combined with them according to the specific application circumstances. The experiment results show that this algorithm is viable and cost- effective that an improvement of nearly 50 percent can be achieved.

Joint TOA and DOA Localization in Indoor Environment Using Virtual Stations

This letter presents a geometrical localization approach that is able to locate a mobile station in non-line-of-sight (NLOS) and multipath conditions using time-of-arrival (TOA) and direction-of-arrival (DOA) estimates. The novelty of our work resides in converting the NLOS problem into a line-of-sight problem with virtual stations, even if the signal undergoes multiple-bound scattering, which has not been resolved in previous works. We also develop a two-step weighted least squares (TSWLS) positioning estimator using the hybrid TOA and DOA values. Simulation results demonstrate the effectiveness of the proposed method.

A Multipath Mitigation Localization Algorithm Based on MDS for Passive UHF RFID

Traditional localization algorithms are vulnerable in multipath environment for passive UHF RFID tag localization. To improve the localization accuracy, this letter proposes a robust algorithm named residual weighted multidimensional scaling (RWMDS) based on the multipath channel model. The RWMDS algorithm first utilizes reader-to-tag distances derived from received signal phase. To obtain the squared distance matrix required in the algorithm, the inter-tag distances are estimated using a few reference tags by establishing the relationship between inter-tag distance and phase information vectors measurement. Based on the modeling of ranging error in multipath environment, the RWMDS lgorithm can be applied to determine the estimated locations of the tags through a few iterations. Simulation results show that the RWMDS algorithm achieves higher localization accuracy than traditional algorithms in multipath environment.

Geometry Influence on GDOP in TOA and AOA Positioning Systems

Geometric dilution of precision (GDOP) is defined as the ratio of the root-mean-square position determination error to the root-mean-square measurement error. Based on the Cramer-Rao lower bound (CRLB), new mathematical expressions of GDOP are presented in Time-of-Arrival (TOA) and Angle-of-Arrival (AOA) positioning systems in this paper. The expressions obviously reveal that the geometrical shape of the anchor nodes make a significant influence on GDOP. Then the influence of adding a new anchor node at different locations is analyzed. Simulations show that in both positioning systems, two optimal placement angles exist to make the GDOP smallest, when the original anchor nodes are no uniformly scattered. However, when uniformly scattered, the GDOP keeps constant no matter what angle the new anchor node is placed at. In AOA positioning systems, the GDOP is also affected by the distance between the newly added anchor node and the target, and increases when the distance increases. Meanwhile, the GDOP is always reduced when more anchor nodes are used.

An improved k-NN algorithm for localization in multipath environments

To improve the localization accuracy in multipath environments, this paper presents an effective localization approach with the utilization of reference tags. In this approach, an improved k-nearest neighbor (k-NN) algorithm is proposed based on radio-frequency (RF) phases. The traditional k-NN algorithm only focuses on the weighting factors of the coordinates of the selected reference tags, while the improved k-NN algorithm aims at the estimation of direct distance from a reader antenna to a target tag. Then, the location is estimated by linear least squares with a new reference selection scheme. Simulation results show that our approach is superior to the traditional localization approaches under multipath environments. In addition, we conclude that phase has the superiority over strength in the selection of reference tags for range estimation, and range estimation is more accurate than coordinate estimation with k-NN algorithm for localization.

Modeling the colored background noise of power line communication channel based on artificial neural network

Power-line network is not specifically designed for high frequency signal transmission. Some tests and documents verify that power-line channel takes on many adverse characteristics that are not conducive to high frequency signal transmission, and noise characteristics are important parameters to describe the nature of power-line communication channel interference. The paper studied noise classification of the power-line communication channel, and specially analyzed the colored background noise characteristic and its mathematical model. Based on artificial neural network, optimization model is studied for the colored background noise of power-line communication channel. The paper educed the neural network algorithm used for modeling colored background noise. Through simulation, amplitude-frequency response curve is derived for neural network filter. And also time domain waveform and power spectrum density of colored noise are achieved from the neural model. The results indicate that artificial neural network modeling method is effective for modeling the colored background noise of power-line communication channel. It is helpful to construct the basis for simulation actual power-line channel.

Similarity Analysis-Based Indoor Localization Algorithm With Backscatter Information of Passive UHF RFID Tags

Passive radio frequency identification (RFID) is a low cost and low complexity localization technology. With introduction of reference tags, RFID technology can provide on-line reference information for pattern matching localization algorithms. One of the most popular algorithms is k -nearest neighbor algorithm. While how to decide the K value in estimation is still a problem. In addition, traditional received signal strength indicator (RSSI)-based algorithms suffer from multipath effects, it is difficult to further improve the localization accuracy. In this paper, we analyze the similarity of backscatter signals and present a novel range based indoor localization method, SAIL. According to the propagation distances of signals, reference tags that have similar distances to a reader antenna can be considered as a group. Inspired by the idea of grouping, clustering algorithm is utilized to get candidate tags for ranging. This method does not need to fix the number of reference tags in estimation. Besides RSSI, the RFID reader can also extract phase of signals coming from backscattered signals of responding tags. This guides us to combine RSSI and phase in similarity measure for clustering. In the simulation and experimental tests, SAIL is superior to other RFID schemes considering cost, location estimation error, and flexibility.

An Indoor Multi-Tag Cooperative Localization Algorithm Based on NMDS for RFID

For radio frequency identification (RFID) system, the location information is very important in many applications, such as Internet of Things, logistics, library management, and so on. Most of traditional RFID localization algorithms can only locate one tag at a time. However, multitag localization is desired in many RFID applications. In this paper, we propose a novel range-free algorithm named nonmetric multidimensional scaling (NMDS)-RFID(F), which combines NMDS algorithm and the fingerprinting localization algorithm to achieve indoor RFID multitag cooperative localization. The NMDS-RFID(F) algorithm firstly uses received signal strength Euclidean distance based on fingerprinting method to get the rank order of the distance for all pairs of tags, and then NMDS algorithm is used to generate the relative coordinates of tags. Finally, due to the coordinates of reference tags are known, we can use the coordinate system registration algorithm to get the absolute coordinates of tags. Simulation results show that the NMDS-RFID(F) algorithm outperforms some previous RFID localization algorithms.

A mobile RFID localization algorithm based on instantaneous frequency estimation

In recent years, the application demand for mobile location techniques have kept rising and the potential market is enormous. In this paper, analysis on the characteristic of receiving signal of mobile reader and time-frequency change caused by relative movement between reader and tags are performed. Then, the Doppler shift estimation method is introduced in RFID system for feature extraction of mobile targets. On the basis of that above, a mobile RFID localization algorithm based on instantaneous frequency estimation is presented. By mining the function relationship among Doppler frequency shift, speed and position of reader, the evaluation of position and speed of mobile target has been solved. The experiment results show that the location algorithm is able to meet the requirement of low complexity, less computation and real-time processing features required by mobile RFID systems.