arXiv subjects

Di Yuan

Publications and source records attributed to Di Yuan.

At least 55 records · Page 3Linked to original sources

arXiv2019

Nuclear mass parabola and its applications

We propose a method to extract the properties of the isobaric mass parabola based on the total double $β$ decay energies of isobaric nuclei. Two important parameters of the mass parabola, the location of the most $β$-stable nuclei $Z_{A}$ and the curvature parameter $b_{A}$, are obtained for 251 A values based on the total double $β$ decay energies of nuclei compiled in AME2016 database.The advantage of this approach is that we can remove the pairing energy term $P_{A}$ caused by odd-even variation, and the mass excess $M(A,Z_{A})$ of the most stable nuclide for mass number $A$ in the performance process, which are used in the mass parabolic fitting method. The Coulomb energy coefficient $a_{c}=0.6910$ MeV is determined by the mass difference relation of mirror nuclei, and the symmetry energy coefficient is also studied by the relation $a_{\rm sym}(A)=0.25b_{A}Z_{A}$.

nucl-th↗

arXiv2019

Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking

Existing deep Thermal InfraRed (TIR) trackers only use semantic features to describe the TIR object, which lack the sufficient discriminative capacity for handling distractors. This becomes worse when the feature extraction network is only trained on RGB images.To address this issue, we propose a multi-level similarity model under a Siamese framework for robust TIR object tracking. Specifically, we compute different pattern similarities on two convolutional layers using the proposed multi-level similarity network. One of them focuses on the global semantic similarity and the other computes the local structural similarity of the TIR object. These two similarities complement each other and hence enhance the discriminative capacity of the network for handling distractors. In addition, we design a simple while effective relative entropy based ensemble subnetwork to integrate the semantic and structural similarities. This subnetwork can adaptive learn the weights of the semantic and structural similarities at the training stage. To further enhance the discriminative capacity of the tracker, we construct the first large scale TIR video sequence dataset for training the proposed model. The proposed TIR dataset not only benefits the training for TIR tracking but also can be applied to numerous TIR vision tasks. Extensive experimental results on the VOT-TIR2015 and VOT-TIR2017 benchmarks demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods.

cs.CV↗

arXiv2019

Routing and Scheduling of Network Flows with Deadlines and Discrete Capacity Allocation

Joint scheduling and routing of data flows with deadline constraints in communication networks has been attracting research interest. This type of problem distinguishes from conventional multicommodity flows due to the presence of the time dimension. In this paper, we address a flow routing and scheduling problem with delivery deadline, where the assignment of link capacity occurs in discrete units. Discrete capacity allocation is motivated by applications in communication systems, where it is common to have a base unit of capacity (e.g., wavelength channel in optical communications). We present and prove complexity results of the problem. Next, we give an optimization formulation based on a time slicing approach (TSA), which amounts to a discretization of the time into time slices to enable to formulate the deadline constraints. We then derive an effective reformulation of the problem, via which a column generation algorithm (CGA) is developed. In addition, we propose a simple and fast Max-Flow based Algorithm (MFA). We use a number of network and traffic scenarios to study various performance aspects of the algorithms.

cs.DM↗

arXiv2019

Joint Scheduling and Power Control for V2V Broadcast Communication with Adjacent Channel Interference

This paper investigates how to mitigate the impact of adjacent channel interference (ACI) in vehicular broadcast communication, using scheduling and power control. Our objective is to maximize the number of connected vehicles. First, we formulate the joint scheduling and power control problem as a mixed Boolean linear programming (MBLP) problem. From this problem formulation, we derive scheduling alone problem as Boolean linear programming (BLP) problem, and power control alone problem as an MBLP problem. Due to the hardness in solving joint scheduling and power control for multiple timeslots, we propose a column generation method to reduce the computational complexity. We also observe that the problem is highly numerically sensitive due to the high dynamic range of channel parameters and adjacent channel interference ratio (ACIR) values. Therefore, we propose a novel sensitivity reduction technique, which can compute the optimal solution. Finally, we compare the results for optimal scheduling, near-optimal joint scheduling and power control schemes, and conclude that the effective scheduling and power control schemes indeed significantly improve the performance.

eess.SP↗

arXiv2019

On the Benefits of Network-Level Cooperation in Millimeter-Wave Communications

Relaying techniques for millimeter-wave wireless networks represent a powerful solution for improving the transmission performance. In this work, we quantify the benefits in terms of delay and throughput for a random-access multi-user millimeter-wave wireless network, assisted by a full-duplex network cooperative relay. The relay is equipped with a queue for which we analyze the performance characteristics (e.g., arrival rate, service rate, average size, and stability condition). Moreover, we study two possible transmission schemes: fully directional and broadcast. In the former, the source nodes transmit a packet either to the relay or to the destination by using narrow beams, whereas, in the latter, the nodes transmit to both the destination and the relay in the same timeslot by using a wider beam, but with lower beamforming gain. In our analysis, we also take into account the beam alignment phase that occurs every time a transmitter node changes the destination node. We show how the beam alignment duration, as well as position and number of transmitting nodes, significantly affect the network performance. Moreover, we illustrate the optimal transmission scheme (i.e., broadcast or fully directional) for several system parameters and show that a fully directional transmission is not always beneficial, but, in some scenarios, broadcasting and relaying can improve the performance in terms of throughput and delay.

cs.NI↗

arXiv2019

BS-assisted Task Offloading for D2D Networks with Presence of User Mobility

Task offloading is a key component in mobile edge computing. Offloading a task to a remote server takes communication and networking resources. An alternative is device-todevice (D2D) offloading, where a task of a device is offloaded to some device having computational resource available. The latter requires that the devices are within the range of each other, first for task collection, and later for result gathering. Hence, in mobility scenarios, the performance of D2D offloading will suffer if the contact rates between the devices are low. We enhance the setup to base station (BS) assisted D2D offloading, namely, a BS can act as a relay for task distribution or result collection. However, this would imply additional consumption of wireless resource. The associated cost and the improvement in completion time of task offloading compose a fundamental trade-off. For the resulting optimization problem, we mathematically prove the complexity, and propose an algorithm using Lagrangian duality. The simulation results demonstrate not only that the algorithm has close-to-optimal performance, but also provide structural insights of the optimal trade-off.

cs.DC↗

arXiv2019

On Optimal Proactive and Retention-Aware Caching with User Mobility

Caching popular contents at edge devices is an effective solution to alleviate the burden of the backhaul networks. Earlier investigations commonly neglected the storage cost in caching. More recently, retention-aware caching, where both the downloading cost and storage cost are accounted for, is attracting attention. Motivated by this, we address proactive and retention-aware caching with user mobility, optimizing the sum of the two types of costs. This is a combinatorial optimization problem. However, we derive a stream of analytical results and they together lead to an algorithm that guarantees global optimum with polynomial-time complexity. Numerical results show significant improvements in comparison to popular caching and random caching.

cs.DC↗

arXiv2018

Maximum Throughput Scheduling for Multi-connectivity in Millimeter-Wave Networks

Multi-connectivity is emerging as promising solution to provide reliable communications and seamless connectivity at the millimeter-wave frequency range. Due to the obstacles that cause frequent interruptions at such high frequency range, connectivity to multiple cells can drastically increase the network performance in terms of throughput and reliability by coordination among the network elements. In this paper, we propose an algorithm for the link scheduling optimization that maximizes the network throughput for multi-connectivity in millimeter-wave cellular networks. The considered approach exploits a centralized architecture, fast link switching, proactive context preparation and data forwarding between millimeter-wave access points and the users. The proposed algorithm is able to numerically approach the global optimum and to quantify the potential gain of multi-connectivity in millimeter-wave cellular networks.

cs.NI↗

arXiv2018

Throughput Analysis for Relay-Assisted Millimeter-Wave Wireless Networks

In this work, we analyze the throughput of random access multi-user relay-assisted millimeter-wave wireless networks, in which both the destination and the relay have multipacket reception capability. We consider a full-duplex network cooperative relay that stores the successfully received packets in a queue, for which we analyze the performance. Moreover, we study the effects on the network throughput of two different strategies, by which the source nodes transmit either a packet to both the destination and the relay in the same timeslot by using wider beams (broadcast approach) or to only one of these two by using narrower beams (fully directional approach). We consider the inter-beam interference at the receiver and show the optimal strategy with respect to several system parameters, e.g., positions and number of the nodes.

cs.NI↗

arXiv2018

Resource Optimization with Flexible Numerology and Frame Structure for Heterogeneous Services

We explore the potential of optimizing resource allocation with flexible numerology in frequency domain and variable frame structure in time domain, in presence of services with different types of requirements. We analyze the computational complexity and propose a scalable optimization algorithm based on searching in both the primal space and dual space that are complementary to each other. Numerical results show significant advantages of adopting flexibility in both time and frequency domains for capacity enhancement and meeting the requirements of mission critical services.

cs.IT↗

arXiv2018

Modeling and Analysis of MPTCP Proxy-based LTE-WLAN Path Aggregation

Long Term Evolution (LTE)-Wireless Local Area Network (WLAN) Path Aggregation (LWPA) based on Multi-path Transmission Control Protocol (MPTCP) has been under standardization procedure as a promising and cost-efficient solution to boost Downlink (DL) data rate and handle the rapidly increasing data traffic. This paper aims at providing tractable analysis for the DL performance evaluation of large-scale LWPA networks with the help of tools from stochastic geometry. We consider a simple yet practical model to determine under which conditions a native WLAN Access Point (AP) will work under LWPA mode to help increasing the received data rate. Using stochastic spatial models for the distribution of WLAN APs and LTE Base Stations (BSs), we analyze the density of active LWPA-mode WiFi APs in the considered network model, which further leads to closed-form expressions on the DL data rate and area spectral efficiency (ASE) improvement. Our numerical results illustrate the impact of different network parameters on the performance of LWPA networks, which can be useful for further performance optimization.

cs.NI↗

arXiv2018

Device Caching for Network Offloading: Delay Minimization with Presence of User Mobility

A delay-optimal caching problem (DOCP) in deviceto- device (D2D) networks with moblity is modelled. The problem arises in the context of achieving offloading using device caching, and the offloading effect is represented by the expected network load ratio (NLR) which is the percentage of data that has to be downloaded from the network. Compared with the related studies, this work considers minimizing delay with NLR guarantee in mobility scenarios. A lower bound of global optimum is derived, thus enabling performance benchmarking of any sub-optimal algorithm. For problem-solving, an effective search algorithm (ESA) is proposed based on the bound. Simulations are conducted to evaluate the effectiveness of the ESA algorithm.

cs.NI↗

arXiv2017

A Framework for Optimizing Multi-cell NOMA: Delivering Demand with Less Resource

Non-orthogonal multiple access (NOMA) allows multiple users to simultaneously access the same time-frequency resource by using superposition coding and successive interference cancellation (SIC). Thus far, most papers on NOMA have focused on performance gain for one or sometimes two base stations. In this paper, we study multi-cell NOMA and provide a general framework for user clustering and power allocation, taking into account inter-cell interference, for optimizing resource allocation of NOMA in multi-cell networks of arbitrary topology. We provide a series of theoretical analysis, to algorithmically enable optimization approaches. The resulting algorithmic notion is very general. Namely, we prove that for any performance metric that monotonically increases in the cells' resource consumption, we have convergence guarantee for global optimum. We apply the framework with its algorithmic concept to a multi-cell scenario to demonstrate the gain of NOMA in achieving significantly higher efficiency.

cs.IT↗

arXiv2017

Wireless Network-Level Partial Relay Cooperation: A Stable Throughput Analysis

In this work, we study the benefit of partial relay cooperation. We consider a two-node system consisting of one source and one relay node transmitting information to a common destination. The source and the relay have external traffic and in addition, the relay is equipped with a flow controller to regulate the incoming traffic from the source node. The cooperation is performed at the network level. A collision channel with erasures is considered. We provide an exact characterization of the stability region of the system and we also prove that the system with partial cooperation is always better or at least equal to the system without the flow controller.

cs.IT↗

arXiv2017

Load Optimization with User Association in Cooperative and Load-Coupled LTE Networks

We extend the problem of optimizing user association for load balancing in cellular networks along two dimensions. First, we consider joint transmission (JT), which is one of the coordinated multipoint (CoMP) techniques, with which a user may be simultaneously served by multiple base stations. Second, we account for, mathematically, the coupling relation between the base stations' load levels that are dependent on each other due to inter-cell interference. We formulate two optimization problems, sum load minimization (MinSumL) and maximum load minimization (MinMaxL). We prove that both MinSumL and MinMaxL are NP-hard. We propose a mixed integer linear programming (MILP) based scheme by means of linearization. This approach also leads to a bounding scheme for performance benchmarking. Then, we derive a set of partial optimality conditions. Fulfillment of the conditions will guarantee performance improvement for both MinSumL and MinMaxL. A solution algorithm is then derived based on the conditions. Simulation results are provided to demonstrate the effectiveness of the approaches.

cs.IT↗

arXiv2017

Optimizing Power and User Association for Energy Saving in Load-Coupled Cooperative LTE

We consider an energy minimization problem for cooperative LTE networks. To reduce energy consumption, we investigate how to jointly optimize the transmit power and the association between cells and user equipments (UEs), by taking into consideration joint transmission (JT), one of the coordinated multipoint (CoMP) techniques. We formulate the optimization problem mathematically. For solving the problem, a dynamic power allocation algorithm that adjusts the transmit power of all cells, and an algorithm for optimizing the cell-UE association, are proposed. The two algorithms are iteratively used in an algorithmic framework to enhance the energy performance. Numerically, the proposed algorithms can lead to lower energy consumption than the optimal energy setting in the non-JT case. In comparison to fixed power allocation in JT, the proposed dynamic power allocation algorithm is able to significantly reduce the energy consumption.

cs.IT↗

arXiv2017

Load Balancing via Joint Transmission in Heterogeneous LTE: Modeling and Computation

As one of the Coordinated Multipoint (CoMP) techniques, Joint Transmission (JT) can improve the overall system performance. In this paper, from the load balancing perspective, we study how the maximum load can be reduced by optimizing JT pattern that characterizes the association between cells and User Equipments (UEs). To give a model of the interference caused by cells with different time-frequency resource usage, we extend a load coupling model, by taking into account JT. In this model, the mutual interference depends on the load of cells coupled in a non-linear system with each other. Under this model, we study a two-cell case and proved that the optimality is achieved in linear time in the number of UEs. After showing the complexity of load balancing in the general network scenario, an iterative algorithm for minimizing the maximum load, named JT-MinMax, is proposed. We evaluate JT-MinMax in a Heterogeneous Network (HetNet), though it is not limited to this type of scenarios. Numerical results demonstrate the significant performance improvement of JT-MinMax on min-max cell load, compared to the conventional non-JT solution where each UE is served by the cell with best received transmit signal.

cs.IT↗

arXiv2017

Range Assignment for Power Optimization in Load-Coupled Heterogeneous Networks

We consider the problem of transmission energy op- timization via range assignment for Low Power Nodes (LPNs) in Long Term Evolution (LTE) Heterogenous Networks (HetNets). The optimization is subject to the load coupling model, where the cells interfere with one another. Each cell provides data service for its users so as to maintain a target Quality-of-Service (QoS). We prove that, irrespective the presence of maximum power limit or its value, operating at full load is optimal. We perform energy minimization by optimizing the association between User Equipments (UEs) and cells via selecting cell- specific offsets on LPNs. Moreover, the optimization problem is proved to be NP-hard. We propose a tabu search algorithm for offset optimization (TSO). For each offset, TSO computes the optimal power solution such that all cells operate at full load. Numerical results demonstrate the significant performance improvement of TSO on optimizing the sum transmission energy, compared to the conventional solution where uniform offset is used for all LPNs.

cs.IT↗