arXiv subjects

Meng Hua

Publications and source records attributed to Meng Hua.

62 records · Page 4Linked to original sources

arXiv2020

Weighted Sum-Rate Maximization for Multi-IRS Aided Cooperative Transmission

This paper investigates multiple intelligent reflecting surfaces (IRSs) aided wireless network, where the IRSs are deployed to cooperatively assist communications between a multi-antenna base station (BS) and multiple single-antenna cell-edge users. We aim at maximizing the weighted sum rate of all the cell-edge users by jointly optimizing the BS's transmit beamforming and IRS's phase shifts. Especially, the beamforming is optimally solved by the Lagrangian method, and the phase shifts are obtained based on the Riemannian manifold conjugate gradient (RMCG) method. Numerical results show that a significant throughput is improved with aid of multiple IRSs.

eess.SP↗

arXiv2019

Throughput Maximization for Full-Duplex UAV Aided Small Cell Wireless Systems

This paper investigates full-duplex unmanned aerial vehicle (UAV) aided small cell wireless systems, where the UAV serving as the base station (BS) is designed to transmit data to the downlink users and receive data from the uplink users simultaneously. To maximize the total system capacity, including uplink and downlink capacity, the UAV trajectory, downlink/uplink user scheduling, and uplink user transmit power are alternately optimized. The resulting optimization problem is mixed-integer and non-convex, which is challenging to solve. To address it, the block coordinate descent method and successive convex approximation techniques are leveraged. Simulation results demonstrate the significant capacity gain can be achieved by our design compared with the other designs.

cs.IT↗

arXiv2019

Throughput Maximization for UAV-aided Backscatter Communication Networks

This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV trajectory. Different static/dynamic circuit power consumption models for the two protocols are analyzed. The resulting optimization problems are shown to be non-convex, which are challenging to solve. We first consider the dynamic circuit power consumption model, and decompose the original problems into three sub-problems, namely time allocation optimization with fixed UAV trajectory and reflection coefficient, reflection coefficient optimization with fixed UAV trajectory and time allocation, and UAV trajectory optimization with fixed reflection coefficient and time allocation. Then, an efficient iterative algorithm is proposed for both protocols by leveraging the block coordinate descent method and successive convex approximation (SCA) techniques. In addition, for the static circuit power consumption model, we obtain the optimal time allocation with a given reflection coefficient and UAV trajectory and the optimal reflection coefficient with low computational complexity by using the Lagrangian dual method. Simulation results show that the proposed protocols are able to achieve significant throughput gains over the compared benchmarks.

cs.IT↗

arXiv2019

Energy-Efficient Cooperative Secure Transmission in Multi-UAV Enabled Wireless Networks

This paper investigates a multiple unmanned aerial vehicles (UAVs) enabled cooperative secure transmission scheme in the presence of multiple potential eavesdroppers. Specifically, multiple source UAVs (SUAVs) send confidential information to multiple legitimate ground users and in the meantime multiple jamming UAVs (JUAVs) cooperatively transmit interference signals to multiple eavesdroppers in order to improve the legitimate users' achievable secrecy rate. By taking into account the limited energy budget of UAV, our goal is to maximize the system secrecy energy efficiency (SEE), namely the achievable secrecy rate per energy consumption unit, by jointly optimizing the UAV trajectory, transmit power and user scheduling under the constraints of UAV mobility as well as the maximum transmit power. The resulting optimization problem is shown to be a non-convex and mixed-integer fractional optimization problem, which is challenging to solve. We decompose the original problem into three sub-problems, and then an efficient iterative algorithm is proposed by leveraging the block coordinate descent and Dinkelbach method in combination with successive convex approximation techniques. Simulation results show that the proposed scheme outperforms the other benchmarks significantly in terms of the system SEE.

cs.IT↗

arXiv2018

Energy Optimization for Cellular-Connected Multi-UAV Mobile Edge Computing Systems with Multi-Access Schemes

In this paper, a cellular-connected unmanned aerial vehicles (UAV) mobile edge computing system is studied in which the multiple UAVs are served by terrestrial base station (TBS) for computation task offloading. Our goal is to minimize the total UAVs energy consumption, including propulsion energy, computation energy and communication energy, while ensuring that the total number of bits of UAVs are completely computed. For tackling the large amount of bits for computation, we propose a resource partitioning strategy where one portion of tasks is migrated to TBS for computation and the other portion of tasks is locally computed at UAV. For deeply comprehending the impacts of access manners on the system performance, we consider four access schemes in the uplink transmission, i.e., time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), One-by-One access and non-orthogonal multiple access (NOMA). The problem of jointly optimizing bit allocation, power allocation, resource partitioning as well as UAV trajectory under TBS's energy budget is formulated and tackled by means of successive convex approximation (SCA) technique. The numerical results show that the proposed schemes save much energy compared with benchmark schemes.

cs.IT↗

arXiv2018

Placement Delivery Array Design via Attention-Based Deep Neural Network

A decentralized coded caching scheme has been proposed by Maddah-Ali and Niesen, and has been shown to alleviate the load of networks. Recently, placement delivery array (PDA) was proposed to characterize the coded caching scheme. In this paper, a neural architecture is first proposed to learn the construction of PDAs. Our model solves the problem of variable size PDAs using mechanism of neural attention and reinforcement learning. It differs from the previous attempts in that, instead of using combined optimization algorithms to get PDAs, it uses sequence-to-sequence model to learn construct PDAs. Numerical results are given to demonstrate that the proposed method can effectively implement coded caching. We also show that the complexity of our method to construct PDAs is low.

cs.IT↗

arXiv2018

Cache-Enabled Dynamic Rate Allocation via Deep Self-Transfer Reinforcement Learning

Caching and rate allocation are two promising approaches to support video streaming over wireless network. However, existing rate allocation designs do not fully exploit the advantages of the two approaches. This paper investigates the problem of cache-enabled QoE-driven video rate allocation problem. We establish a mathematical model for this problem, and point out that it is difficult to solve the problem with traditional dynamic programming. Then we propose a deep reinforcement learning approaches to solve it. First, we model the problem as a Markov decision problem. Then we present a deep Q-learning algorithm with a special knowledge transfer process to find out effective allocation policy. Finally, numerical results are given to demonstrate that the proposed solution can effectively maintain high-quality user experience of mobile user moving among small cells. We also investigate the impact of configuration of critical parameters on the performance of our algorithm.

cs.NI↗

arXiv2015

Classification of stable Dirac and Weyl semimetals with reflection and rotational symmetry

Three dimensional (3D) Dirac semimetal is a novel state of quantum matter, characterized by the gapless bulk four-fold degeneracy near Fermi energy. Soon after its discovery, the classification of stable 3D Dirac semimetals with inversion and rotational symmetry have been studied. However, only ten out of thirty-two point groups have both inversion and rotational symmetry, and we need a more complete classification of stable 3D Dirac semimetals. Here we classify stable 3D Dirac semimetals with reflection symmetry and rotational symmetry in the presence of time reversal symmetry, which belong to seventeen different point groups. These systems include the systems preserving inversion symmetry except $\mathrm{C_{3i}}$. They have two classes of reflection symmetry, with the mirror plane parallel to rotation axis and the mirror plane perpendicular to rotation axis. In both cases two types of Dirac semimetals are determined by four different reflection symmetries. The first type of Dirac semimetals will appear through accidental band crossing (ABC). The second type of Dirac semimetals have a Dirac point at a time reversal invariant momentum (TBC). We show that in both mirror parallel and perpendicular cases, $C_{2,3}$ symmetry can only protect stable Dirac points via TBC, while $C_{4,6}$ symmetry can have stable Dirac points as ABC or TBC. We further discuss that Weyl line nodes and Dirac semimetal can exist in Brillouin zone at the same time using $\mathrm{C_{4v}}$ symmetry as an example. Finally we classify Dirac line nodes and Weyl line nodes to show in which types of mirror plane they can exist.

cond-mat.mes-hall↗