Machine reading comprehension with multi-hop reasoning always suffers from reasoning path breaking due to the lack of world knowledge, which always results in wrong answer detection. In this paper, we analyze what knowledge the previous work lacks, e.g., dependency relations and commonsense. Based on our analysis, we propose a Multi-dimensional Knowledge enhanced Graph Network, named MKGN, which exploits specific knowledge to repair the knowledge gap in reasoning process. Specifically, our approach incorporates not only entities and dependency relations through various graph neural networks, but also commonsense knowledge by a bidirectional attention mechanism, which aims to enhance representations of both question and contexts. Besides, to make the most of multi-dimensional knowledge, we investigate two kinds of fusion architectures, i.e., in the sequential and parallel manner. Experimental results on HotpotQA dataset demonstrate the effectiveness of our approach and verify that using multi-dimensional knowledge, especially dependency relations and commonsense, can indeed improve the reasoning process and contribute to correct answer detection.

Limited Random Sequence (LRS) is quite important for Analog-to-Information Converter (AIC) because it determines the random sampling scheme and the resultant performance. LRS is established with the elements of “0” and “1”. The “1” appears randomly in the segment of the sequence, so that the production of the original signal and LRS can be considered as the approximation of the random sampling of the original signal. The random sampling result can perfectly recover the signal with Compressive Sensing (CS) algorithm. In this paper, a high order LRS is proposed for the AIC design in Distributed Compressive Sensing (DCS), which has the following three typical features: 1) The high order LRS has the elements of integer which can indicate the index number of the sensor in DCS. 2) High order LRS can adapt to the sparsity variation of the original signal detected by each sensor. 3) Employing the AIC with high order LRS, the DCS algorithm can recover the signal with very low sampling rate, usually above 2 orders less than the traditional distributed sensors. In the paper, the scheme and the construction algorithm of high order LRS are proposed. The performance is evaluated with the application studies of the distributed sensor network and the camera picture correspondingly.

Safety is the foremost requirement of avionics systems on aircraft. So far, avionics systems have evolved into an integrated system, i.e., integrated avionics system, and the derivative functions occur when the avionics systems are upgraded. However, the traditional safety analysis method is insufficient to be utilized in upgraded avionics systems due to these derivative functions. In this letter, a safety evaluation scheme is proposed to quantitatively evaluate the safety of the upgraded avionics systems. All the functions including the derivative functions can be traced and covered. Meanwhile, a set of safety issues based on different views is established to evaluate the safety capability from three layers, i.e., the mission layer, function layer and resource layer. The proposed scheme can be considered as an efficient scheme in the safety validation and verification in the upgraded avionics systems.

The pilot symbols in the broadband Air-to-Ground (A/G) communications system, e.g., L-band Digital Aeronautical Communications System (L-DACS1), are expected to be also utilized for navigation. In order to identify the co-channel signals from different Ground Stations (GSs), the N-Shift Zero Correlation Zone (NS-ZCZ) sequences are employed for pilot sequences. The ideal correlation property of the proposed pilot sequence in ZCZ can maintain the signal with less co-channel interference. The simulation confirms that the more co-channel GSs are employed, the higher navigation accuracy can be achieved.

Due to the high speed mobile environment, the aeronautical Cognitive Radio (CR) communications base on the channel with the time-variant stochastic non-continuous spectrum. The traditional fading channel models, such as Rayleigh, Rice, Nakagami-m and multipath channel models, can not describe the whole property of the channels of CR communications. In this letter, the statistical channel modeling scheme for aeronautical CR communications is proposed with a M/M/s(1) queuing model, which properly describes the random spectrum occupation of the primary users, i.e. aircrafts in aeronautical communications. The proposed channel model can be easily utilized in the channel simulation to testify the validity and efficiency of the aeronautical CR communications.

A narrowband interference (NBI) estimation and mitigation method based on compressive sensing (CS) for communication systems with repeated training sequences is investigated in this letter. The proposed CS-based differential measuring method is performed through the differential operation on the inter-block-interference-free regions of the received adjacent training sequences. The sparse NBI signal can be accurately recovered from a time-domain measurement vector of small size under the CS framework, without requiring channel information or dedicated resources. Theoretical analysis and simulation results show that the proposed method is robust to NBI under multi-path fading channels.

In this letter, we enhance Complementary Code Keying (CCK) modulation with Pseudo-Periodic Sequence. It has been proved that the new Pseudo-Periodic CCK modulation is more efficient and robust fighting against multi-path interference. In order to support our new scheme, we design and implement the corresponding simulation. The in-depth analysis of the reason why Pseudo-Periodic Sequence can do a favor to CCK is also presented and emphasized.

Large Area Synchronized (LAS)-CDMA, actually composed of LA codes and pulse compressing LS codes, has been proposed as a most promising scheme in 3G and 4G wireless communications. LS codes are famous for the Zero Correlation Zone (ZCZ) in the auto-correlation and cross-correlation functions, which endows the codes with the capability to perfectly reduce the Multiple Access Interference (MAI) and Inter Symbol Interference (ISI) if the maximum transmission delay is less than the length of ZCZ. In this letter, we provide a general and systematic method to construct LS codes from the set of complete complementary sequences. Our method is much more general than the ordinary LS construction method revealed previously.

Rotate magnetic field can be used for ranging, especially the environment where electronic filed suffers a deep fading and attenuation, such as drilling underground. However, magnetic field is still affected by the ferromagnetic materials, e.g., oil casing pipe. The measurement error is not endurable for single measurement. In this paper, the Geometric Predicted Unscented Kalman Filtering (GP-UKF) algorithm is developed for rotate magnetic ranging system underground. With GP-UKF, the Root Mean Square Error (RMSE) can be suppressed. It is really important in a long range detection by magnetic field, i.e., more than 50 meters.

Trellis coded modulation (TCM) concept is applied to the mode constellation points of orbital angular momentum (OAM) modulation. OAM modulation considers the multiple OAM modes as additional constellation points and maps a first part of a block of information bits to the transmitting OAM modes. Therefore, spatial multiplexing gains are retained and spectral efficiency is boosted. The second part of the block of information bits is mapped to a complex symbol using conventional digital modulation schemes. At any particular time instant, only one OAM mode is active. The receiver estimates the transmitted symbol and the active OAM mode, then uses the two estimates to retrieve the original block of data bits. Simulation reveals that with the TCM employed both for the OAM constellation points and the signal constellation points, a considerable bit error rate (BER) gain can be obtained under all turbulence conditions, compared with that of the no coding scheme.

In recent years, many variants of key point based image descriptors have been designed for the image matching, and they have achieved remarkable performances. However, to some images, local features appear to be inapplicable. Since theses images usually have many local changes around key points compared with a normal image, we define this special image category as the image with local changes (IL). An IL pair (ILP) refers to an image pair which contains a normal image and its IL. ILP usually loses local visual similarities between two images while still holding global visual similarity. When an IL is given as a query image, the purpose of this work is to match the corresponding ILP in a large scale image set. As a solution, we use a compressed HOG feature descriptor to extract global visual similarity. For the nearest neighbor search problem, we propose random projection indexed KD-tree forests (rKDFs) to match ILP efficiently instead of exhaustive linear search. rKDFs is built with large scale low-dimensional KD-trees. Each KD-tree is built in a random projection indexed subspace and contributes to the final result equally through a voting mechanism. We evaluated our method by a benchmark which contains 35,000 candidate images and 5,000 query images. The results show that our method is efficient for solving local-changes invariant image matching problems.

The pilot contamination is a serious problem which hinders the capacity increasing in the massive MIMO system. Similar to Fractional Frequency Reuse (FFR) in the OFDMA system, Fractional Pilot Reuse (FPR) is proposed for the massive MIMO system. The FPR can be further classified as the strict FPR and soft FPR. Meanwhile, the detailed FPR schemes with pilot assignment and the mathematical models are provided. With FPR, the capacity and the transmission quality can be improved with metrics such as the higher Signal to Interference and Noise Ratio (SINR) of the pilots, the higher coverage probability, and the higher system capacity.

Sequence set with Three Zero Correlation Zones (T-ZCZ) can efficiently mitigate the Multiple Access Interference (MAI) and Inter Symbol Interference (ISI) caused by multi-path in CDMA system. In this paper, an algorithm for generating T-ZCZ sequence set is presented. Moreover, in order to study the restrictions among the parameters such as the length of the sequence, the number of the sequences and the length of the T-ZCZ etc., the corresponding theoretical bound is investigated and proved. Additionally, the performance of T-ZCZ sequence in MC-CDMA system is evaluated to confirm the capability of interference cancellation as well as system capacity improvement.

An unsupervised adaptive signal processing method of principal components analysis (PCA) neural networks (NN) based on signal eigen-analysis is proposed to permit the eigenstructure analysis of lower signal to noise ratios (SNR) direct sequence spread spectrum (DS) signals. The objective of eigenstructure analysis is to estimate the pseudo noise (PN) of DS signals blindly. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, which duration is two periods of PN sequence. Then an autocorrelation matrix is computed and accumulated by these signal vectors one by one. Lastly, the PN sequence can be estimated by the principal eigenvector of autocorrelation matrix. Since the duration of temporal window is two periods of PN sequence, the PN sequence can be reconstructed by the first principal eigenvector only. Additionally, the eigen-analysis method becomes inefficient when the estimated PN sequence is long. We can use an unsupervised adaptive method of PCA NN to realize the PN sequence estimation from lower SNR input DS-SS signals effectively.

Sequence set with Three Zero Correlation Zones (T-ZCZ) is applied in Quasi-Synchronized CDMA communication system to reduce the Multiple Access Interference (MAI) and Inter Symbol Interference (ISI). In this letter, we present a class of sequence set with Three Low Correlation Zones (T-LCZ), which has more sequences and flexibility than T-ZCZ sequence set. Moreover, the theoretical bound on T-LCZ sequences is derived for estimating the performance of such sequence set.

Channel modeling, which is quite important for wireless communications system design, is difficult to be statistically generated from experimental results due to the expense and time constraints. However, with the computational electromagnetics method, the Electro-Magnetic (EM) field can be emulated and the corresponding EM wave propagation scenario can be analyzed. In this letter, the Finite Integration Technique (FIT) method is utilized to calculate the EM wave propagation of the onboard mobile communications in the cabin of an aircraft. With the simulation results, the channel model is established. Compared with Finite-Difference Time-Domain (FDTD), the proposed scheme is more accurate, which is promising to be used in the cabin channel modeling for onboard mobile system design.

Doppler diversity has been proven effective to combat time variation caused by Doppler spread in single carrier systems. However, it is not efficient to directly apply Doppler diversity into Multi-Carrier Code Division Multiple Access (MC-CDMA) systems because Inter-Carrier-Interference (ICI) increases with the artificial frequency shifts in diversity branches. In this paper, a novel Doppler diversity scheme in MC-CDMA with Three Zero Correlation Zones (T-ZCZ) sequences is proposed to further improve the performance of Doppler diversity. Particularly, zero correlation zones are employed in frequency domain for ICI cancelation caused by Doppler spread, which confirms the validity of the contribution to the wideband wireless communications in high speed mobile environment.

We address the problem of measuring matching similarity in terms of template matching. A novel method called two-side agreement learning (TAL) is proposed which learns the implicit correlation between two sets of multi-dimensional data points. TAL learns from a matching exemplar to construct a symmetric tree-structured model. Two points from source set and target set agree to form a two-side agreement (TA) pair if each point falls into the same leaf cluster of the model. In the training stage, unsupervised weak hyper-planes of each node are learned at first. After then, tree selection based on a cost function yields final model. In the test stage, points are propagated down to leaf nodes and TA pairs are observed to quantify the similarity. Using TAL can reduce the ambiguity in defining similarity which is hard to be objectively defined and lead to more convergent results. Experiments show the effectiveness against the state-of-the-art methods qualitatively and quantitatively.

Zero Correlation Zone (ZCZ) sequences have been confirmed the capability in interference mitigation in multipath fading channel. On the other hand, Orthogonal Variable Spreading Factor (OVSF) codes have been successfully applied in WCDMA for separating different channels with different transmission capacity. In this paper, novel OVSF-ZCZ sequences originated from LS and GO sequences have been proposed for CDMA systems with different service requirements. The construction method is discussed and the performance of the system is evaluated.

Angular Momentum (AM) has been considered as a new dimension of wireless transmissions as well as the intrinsic property of Electro-Magnetic (EM) waves. So far, AM is utilized as a discrete mode not only in the quantum states, but also in the statistical beam forming. Traditionally, the continuous value of AM is ignored and only the quantized mode number is identified. However, the recent discovery on electrons in spiral motion producing twisted radiation with AM, including Spin Angular Momentum (SAM) and Orbital Angular Momentum (OAM), proves that the continuous value of AM is available in the statistical EM wave beam. This is also revealed by the so-called fractional OAM, which is reported in optical OAM beams. Then, as the new dimension with continuous real number field, AM should turn out to be a certain spectrum, similar to the frequency spectrum usually in the wireless signal processing. In this letter, we mathematically define the AM spectrum and show the applications in the information theory analysis, which is expected to be an efficient tool for the future wireless communications with AM.