arXiv subjects

Nan Yang

Publications and source records attributed to Nan Yang.

At least 199 records · Page 11Linked to original sources

arXiv2018

Sequential Copying Networks

Copying mechanism shows effectiveness in sequence-to-sequence based neural network models for text generation tasks, such as abstractive sentence summarization and question generation. However, existing works on modeling copying or pointing mechanism only considers single word copying from the source sentences. In this paper, we propose a novel copying framework, named Sequential Copying Networks (SeqCopyNet), which not only learns to copy single words, but also copies sequences from the input sentence. It leverages the pointer networks to explicitly select a sub-span from the source side to target side, and integrates this sequential copying mechanism to the generation process in the encoder-decoder paradigm. Experiments on abstractive sentence summarization and question generation tasks show that the proposed SeqCopyNet can copy meaningful spans and outperforms the baseline models.

cs.CL↗

arXiv2018

Neural Document Summarization by Jointly Learning to Score and Select Sentences

Sentence scoring and sentence selection are two main steps in extractive document summarization systems. However, previous works treat them as two separated subtasks. In this paper, we present a novel end-to-end neural network framework for extractive document summarization by jointly learning to score and select sentences. It first reads the document sentences with a hierarchical encoder to obtain the representation of sentences. Then it builds the output summary by extracting sentences one by one. Different from previous methods, our approach integrates the selection strategy into the scoring model, which directly predicts the relative importance given previously selected sentences. Experiments on the CNN/Daily Mail dataset show that the proposed framework significantly outperforms the state-of-the-art extractive summarization models.

cs.CL↗

arXiv2018

Beamforming Design and Power Allocation for Secure Transmission with NOMA

In this work, we propose a novel beamforming design to enhance physical layer security of a non-orthogonal multiple access (NOMA) system with the aid of artificial noise (AN). The proposed design uses two scalars to balance the useful signal strength and interference at the strong and weak users, which is a generalized version of the existing beamforming designs in the context of physical layer security for NOMA. We determine the optimal power allocation among useful signals and AN together with the two optimal beamforming scalars in order to maximize the secrecy sum rate (SSR). Our asymptotic analysis in the high signal-to-noise ratio regime provides an efficient and near-optimal solution to optimizing the beamforming scalars and power allocation coefficients. Our analysis indicates that it is not optimal to form a beam towards either the strong user or the weak user in NOMA systems for security enhancement. In addition, the asymptotically optimal power allocation informs that, as the transmit power increases, more power should be allocated to the weak user or AN signals, while the power allocated to the strong user keeps constant. Our examination shows that the proposed novel beamforming design can significantly outperform two benchmark schemes.

cs.IT↗

arXiv2018

Joint Beamforming and Power Allocation in Downlink NOMA Multiuser MIMO Networks

In this paper, a novel joint design of beamforming and power allocation is proposed for a multi-cell multiuser multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) network. In this network, base stations (BSs) adopt coordinated multipoint (CoMP) for downlink transmission. We study a new scenario where the users are divided into two groups according to their quality-of-service (QoS) requirements, rather than their channel qualities as investigated in the literature. Our proposed joint design aims to maximize the sum-rate of the users in one group with the best-effort while guaranteeing the minimum required target rates of the users in the other group. The joint design is formulated as a non-convex NP-hard problem. To make the problem tractable, a series of transformations are adopted to simplify the design problem. Then, an iterative suboptimal resource allocation algorithm based on successive convex approximation is proposed. In each iteration, a rank-constrained optimization problem is solved optimally via semidefinite program relaxation. Numerical results reveal that the proposed scheme offers significant sum-rate gains compared to the existing schemes and converges fast to a suboptimal solution.

cs.IT↗

arXiv2018

Short-Packet Downlink Transmission with Non-Orthogonal Multiple Access

This work introduces downlink non-orthogonal multiple access (NOMA) into short-packet communications. NOMA has great potential to improve fairness and spectral efficiency with respect to orthogonal multiple access (OMA) for low-latency downlink transmission, thus making it attractive for the emerging Internet of Things. We consider a two-user downlink NOMA system with finite blocklength constraints, in which the transmission rates and power allocation are optimized. To this end, we investigate the trade-off among the transmission rate, decoding error probability, and the transmission latency measured in blocklength. Then, a one-dimensional search algorithm is proposed to resolve the challenges mainly due to the achievable rate affected by the finite blocklength and the unguaranteed successive interference cancellation. We also analyze the performance of OMA as a benchmark to fully demonstrate the benefit of NOMA. Our simulation results show that NOMA significantly outperforms OMA in terms of achieving a higher effective throughput subject to the same finite blocklength constraint, or incurring a lower latency to achieve the same effective throughput target. Interestingly, we further find that with the finite blocklength, the advantage of NOMA relative to OMA is more prominent when the effective throughput targets at the two users become more comparable.

cs.IT↗

arXiv2018

Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect

Monocular visual odometry (VO) and simultaneous localization and mapping (SLAM) have seen tremendous improvements in accuracy, robustness and efficiency, and have gained increasing popularity over recent years. Nevertheless, not so many discussions have been carried out to reveal the influences of three very influential yet easily overlooked aspects: photometric calibration, motion bias and rolling shutter effect. In this work, we evaluate these three aspects quantitatively on the state of the art of direct, feature-based and semi-direct methods, providing the community with useful practical knowledge both for better applying existing methods and developing new algorithms of VO and SLAM. Conclusions (some of which are counter-intuitive) are drawn with both technical and empirical analyses to all of our experiments. Possible improvements on existing methods are directed or proposed, such as a sub-pixel accuracy refinement of ORB-SLAM which boosts its performance.

cs.CV↗

arXiv2018

Location-Aware Pilot Allocation in Multi-Cell Multi-User Massive MIMO Networks

We propose a location-aware pilot allocation algorithm for a massive multiple-input multiple-output (MIMO) network with high-mobility users, where the wireless channels are subject to Rician fading. Pilot allocation in massive MIMO is a hard combinatorial problem and depends on the locations of users. As such, it is highly complex to achieve the optimal pilot allocation in real-time for a network with high-mobility users. Against this background, we propose a low-complexity pilot allocation algorithm, which exploits the behavior of line-of-sight (LOS) interference among the users and allocate the same pilot sequence to the users with small LOS interference. Our examination demonstrates that our proposed algorithm significantly outperforms the existing algorithms, even with localization errors. Specifically, for the system considered in this work, our proposed algorithm provides up to 37.26% improvement in sum spectral efficiency (SE) and improves the sum SE of the worst interference-affected users by up to 2.57 bits/sec/Hz, as compared to the existing algorithms.

cs.IT↗

arXiv2018

A New Simulation Algorithm for Absorbing Receiver in Molecular Communication

The simulation of diffusion-based molecular communication systems with absorbing receivers often requires a high computational complexity to produce accurate results. In this work, a new a priori Monte Carlo (APMC) algorithm is proposed to precisely simulate the molecules absorbed at a spherical receiver when the simulation time step length is relatively large. This algorithm addresses the limitations of the current refined Monte Carlo (RMC) algorithm, since the RMC algorithm provides accurate simulation only for a relatively small time step length. The APMC algorithm is demonstrated to achieve a higher simulation efficiency than the existing algorithms by finding that the APMC algorithm, for a relatively large time step length, absorbs the fraction of molecules expected by analysis, while other algorithms do not.

cs.ET↗

arXiv2018

Downlink Power Control in Massive MIMO Networks with Distributed Antenna Arrays

In this paper, we investigate downlink power control in massive multiple-input multiple-output (MIMO) networks with distributed antenna arrays. The base station (BS) in each cell consists of multiple antenna arrays, which are deployed in arbitrary locations within the cell. Due to the spatial separation between antenna arrays, the large-scale propagation effect is different from a user to different antenna arrays in a cell, which makes power control a challenging problem as compared to conventional massive MIMO. We assume that the BS in each cell obtains the channel estimates via uplink pilots. Based on the channel estimates, the BSs perform maximum ratio transmission for the downlink. We then derive a closed-form spectral efficiency (SE) expression, where the channels are subject to correlated fading. Utilizing the derived expression, we propose a max-min power control algorithm to ensure that each user in the network receives a uniform quality of service. Numerical results demonstrate that, for the network considered in this work, optimizing for max-min SE through the max-min power control improves the sum SE of the network as compared to equal power allocation.

cs.IT↗

arXiv2018

Convex Optimization of Distributed Cooperative Detection in Multi-Receiver Molecular Communication

In this paper, the error performance achieved by cooperative detection among K distributed receivers in a diffusion-based molecular communication (MC) system is analyzed and optimized. In this system, the receivers first make local hard decisions on the transmitted symbol and then report these decisions to a fusion center (FC). The FC combines the local hard decisions to make a global decision using an N-out-of-K fusion rule. Two reporting scenarios, namely, perfect reporting and noisy reporting, are considered. Closed-form expressions are derived for the expected global error probability of the system for both reporting scenarios. New approximated expressions are also derived for the expected error probability. Convex constraints are then found to make the approximated expressions jointly convex with respect to the decision thresholds at the receivers and the FC. Based on such constraints, suboptimal convex optimization problems are formulated and solved to determine the optimal decision thresholds which minimize the expected error probability of the system. Numerical and simulation results reveal that the system error performance is greatly improved by combining the detection information of distributed receivers. They also reveal that the solutions to the formulated suboptimal convex optimization problems achieve near-optimal global error performance.

cs.IT↗

arXiv2018

Maximum Likelihood Detection for Cooperative Molecular Communication

In this paper, symbol-by-symbol maximum likelihood (ML) detection is proposed for a cooperative diffusion-based molecular communication (MC) system. In this system, a fusion center (FC) chooses the transmitter's symbol that is more likely, given the likelihood of the observations from multiple receivers (RXs). We propose three different ML detection variants according to different constraints on the information available to the FC, which enables us to demonstrate trade-offs in their performance versus the information available. The system error probability for one variant is derived in closed form. Numerical and simulation results show that the ML detection variants provide lower bounds on the error performance of the simpler cooperative variants and demonstrate that majority rule detection has performance comparable to ML detection when the reporting is noisy.

cs.IT↗

arXiv2018

Chaotic synchronization of two optical cavity modes in optomechanical systems

The synchronization of the motion of microresonators has attracted considerable attention. Here we present theoretical methods to synchronize the chaotic motion of two optical cavity modes in an optomechanical system, in which one of the optical modes is strongly driven into chaotic motion and is coupled to another weakly-driven optical mode mediated by a mechanical resonator. In these optomechanical systems, we can obtain both complete and phase synchronization of the optical cavity modes in chaotic motion, starting from different initial states. We find that complete synchronization of chaos can be achieved in two identical cavity modes. In the strong-coupling small-detuning regime, we also {produce} phase synchronization of chaos between two nonidentical cavity modes.

quant-ph↗

arXiv2018

On Channel Reciprocity to Activate Uplink Channel Training for Downlink Wireless Transmission in Tactile Internet Applications

We determine, for the first time, the requirement on channel reciprocity to activate uplink channel training, instead of downlink channel training, to achieve a higher data rate for the downlink transmission from a multi-antenna base station to a single-antenna user. We first derive novel closed-form expressions for the lower bounds on the data rates achieved by the two channel training strategies by considering the impact of finite blocklength. The performance comparison result of these two strategies is determined by the amount of channel reciprocity that is utilized in the uplink channel training. We then derive an approximated expression for the minimum channel reciprocity that enables the uplink channel training to outperform the downlink channel training. Through numerical results, we demonstrate that this minimum channel reciprocity decreases as the blocklength decreases or the number of transmit antennas increases, which shows the necessity and benefits of activating the uplink channel training for short-packet communications with multiple transmit antennas. This work provides pivotal and unprecedented guidelines on choosing channel training strategies and channel reciprocity calibrations, offering valuable insights into latency reduction in the Tactile Internet applications.

cs.IT↗

arXiv2018

S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension

In this paper, we present a novel approach to machine reading comprehension for the MS-MARCO dataset. Unlike the SQuAD dataset that aims to answer a question with exact text spans in a passage, the MS-MARCO dataset defines the task as answering a question from multiple passages and the words in the answer are not necessary in the passages. We therefore develop an extraction-then-synthesis framework to synthesize answers from extraction results. Specifically, the answer extraction model is first employed to predict the most important sub-spans from the passage as evidence, and the answer synthesis model takes the evidence as additional features along with the question and passage to further elaborate the final answers. We build the answer extraction model with state-of-the-art neural networks for single passage reading comprehension, and propose an additional task of passage ranking to help answer extraction in multiple passages. The answer synthesis model is based on the sequence-to-sequence neural networks with extracted evidences as features. Experiments show that our extraction-then-synthesis method outperforms state-of-the-art methods.

cs.CL↗

arXiv2017

Existence and stability of circular orbits in static and axisymmetric spacetimes

The existence and stability of timelike and null circular orbits (COs) in the equatorial plane of general static and axisymmetric (SAS) spacetime are investigated in this work. Using the fixed point approach, we first obtained a necessary and sufficient condition for the non-existence of timelike COs. It is then proven that there will always exist timelike COs at large $ρ$ in an asymptotically flat SAS spacetime with a positive ADM mass and moreover, these timelike COs are stable. Some other sufficient conditions on the stability of timelike COs are also solved. We then found the necessary and sufficient condition on the existence of null COs. It is generally shown that the existence of timelike COs in SAS spacetime does not imply the existence of null COs, and vice-versa, regardless whether the spacetime is asymptotically flat or the ADM mass is positive or not. These results are then used to show the existence of timelike COs and their stability in an SAS Einstein-Yang-Mills-Dilaton spacetimes whose metric is not completely known. We also used the theorems to deduce the existence of timelike and null COs in some known SAS spacetimes.

gr-qc↗

arXiv2017

Optimal Load Balancing in Millimeter Wave Cellular Heterogeneous Networks

In this paper, we propose a novel and effective approach to optimizing the load balancing in a millimeter wave (mmWave) cellular heterogeneous network (HetNet) with a macro-tier and a micro-tier. The unique characteristics of mmWave transmission are incorporated into the network by adopting the Poisson point process (PPP) for base station (BS) location, the line-of-sight (LoS) ball model for mmWave links, the sectored antenna model for key antenna array characteristics, and Nakagami-$m$ fading for wireless channels. To reduce the load of macro-tier BSs, we consider a bias factor $A_{s}$ in the network for offloading user equipments (UEs) to micro-tier BSs. For this network, we first analyze the loads of macro- and micro-tier BSs. Then we derive a new expression for the rate coverage probability of the network, based on which the optimal $A_{s}$ maximizing the rate coverage probability is found. Through numerical results, we demonstrate the correctness of our analysis and the validity of the optimal $A_{s}$. Importantly, the optimal $A_{s}$ can bring a profound improvement in the rate coverage probability relative to a fixed $A_{s}$. Furthermore, we evaluate the impact of various network parameters, e.g., the densities and the beamwidths of BSs, on the rate coverage probability and the optimal $A_{s}$, offering valuable guidelines into practical mmWave HetNet design.

cs.IT↗

arXiv2017

Short-Packet Communications in Non-Orthogonal Multiple Access Systems

This work introduces, for the first time, non-orthogonal multiple access (NOMA) into short-packet communications to achieve low latency in wireless networks. Specifically, we address the optimization of transmission rates and power allocation to maximize the effective throughput of the user with a higher channel gain while guaranteeing the other user achieving a certain level of effective throughput. To demonstrate the benefits of NOMA, we analyze the performance of orthogonal multiple access (OMA) as a benchmark. Our examination shows that NOMA can significantly outperform OMA by achieving a higher effective throughput with the same latency or incurring a lower latency to achieve the same effective throughput targets. Surprisingly, we find that the performance gap between NOMA and OMA becomes more prominent when the effective throughput targets at the two users become closer to each other. This demonstrates that NOMA can significantly reduce the latency in the context of short-packet communications with practical constraints.

cs.IT↗

arXiv2017

Simplified Cooperative Detection for Multi-Receiver Molecular Communication

Diffusion-based molecular communication (MC) systems experience significant reliability losses. To boost the reliability, an MC scheme where multiple receivers (RXs) work cooperatively to decide the signal of a transmitter (TX) by sending the same type of molecules to a fusion center (FC) is proposed in this paper. The FC observes the total number of molecules received and compares this number with a threshold to determine the TX's signal. The proposed scheme is more bio-realistic and requires relatively low computational complexity compared to existing cooperative schemes where the RXs send and the FC recognizes different types of molecules. Asymmetric and symmetric topologies are considered, and closed-form expressions are derived for the global error probability for both topologies. Results show that the trade-off for simplified computations leads to a slight reduction in error performance, compared to the existing cooperative schemes.

cs.IT↗