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Learning to Deployment: Data-Driven On-Demand UAV Placement for Throughput Maximization
Leiyu Wang;Haixia Zhang;Shuaishuai Guo;Dongyang Li;Dongfeng Yuan
Unmanned Aerial Vehicles (UAVs) communications appear to be one of the most promising paradigms for future wireless communication networks, because of their high flexibility in providing on-demand communication services. In this context, this article investigates a fast and fine-grained UAV deployment scheme so as to improve the network throughput and meet the real-time communication demands of us...Show More
Deep Learning-Enabled Joint Edge Content Caching and Power Allocation Strategy in Wireless Networks
Edge content caching has emerged as a promising solution against network latency by pre-caching popular contents at the edge of networks. However, the edge content caching and wireless resource allocation are intertwined with each other. The content downloading latency depends not only on the edge content caching strategy, but also highly on the wireless resource allocation strategy. To cope with ...Show More
Communication-, Computation-, and Control-Enabled UAV Mobile Communication Networks
IEEE Internet of Things Journal
Cited by: Papers (10)
Unmanned-aerial-vehicles (UAVs)-enabled mobile-edge computing (MEC) networks have shown a huge advantage in providing on-demand communication and computation service for the ground users. To reap the benefit of these integrated networks, reducing their energy consumption becomes a key issue, since both UAVs and ground users are energy-limited devices. To address this problem, this article attempts...Show More
3D UAV Deployment in Multi-UAV Networks With Statistical User Position Information
IEEE Communications Letters
Cited by: Papers (27)
Unmanned aerial vehicle (UAV) carried base stations can provide on-demand deployment for ground users. Given a target area to be serviced, this letter proposes a three-dimensional (3D) deployment method for multiple UAVs based on the knowledge of statistical user position information to maximize the total network throughput. The 3D deployment problem is divided into horizontal deployment problem a...Show More
Deployment and Association of Multiple UAVs in UAV-Assisted Cellular Networks With the Knowledge of Statistical User Position
Exploiting unmanned aerial vehicles (UAVs) as flying relays is becoming an indispensable strategy to assist terrestrial cellular networks to enhance coverage. One challenging problem for UAV-integrated cellular networks is how to design their deployment and association schemes to provide on-demand coverage with minimum network power consumption. In this paper, the uplink transmission in a UAV-assi...Show More
Adaptive Task Offloading in Vehicular Edge Computing Networks Based on Deep Reinforcement Learning
2021 IEEE/CIC International Conference on Communications in China (ICCC)
Year: 2021 | Conference Paper |
Cited by: Papers (4)
To support the delay-sensitive application for vehicular communications, edge servers are adopted and deployed in the roadside units to provide abundant computing resources for vehicles forming vehicular edge computing networks (VECNs). This paper tries to optimize the task offloading scheme to reduce the total task processing delay as much as possible in VECNs. Considering the dynamic nature of v...Show More
Profit Maximization Task Offloading Mechanism with D2D Collaboration in MEC Networks
Weijie Sun;Haixia Zhang;Leiyu Wang;Shuaishuai Guo;Dongfeng Yuan
2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)
Year: 2019 | Conference Paper |
Cited by: Papers (7)
This paper investigates an optimal offloading mechanism for multi-access edge computing networks with the aid of device-to-device (D2D) communication technology. Specifically, due to the existence of idle devices in the networks, the communication tasks can be offloaded to them for fully utilizing their computing resources. Thus, in order to encourage the idle devices to join the collaboration off...Show More
Generalized Beamspace Modulation Using Multiplexing: A Breakthrough in mmWave MIMO
Shuaishuai Guo;Haixia Zhang;Peng Zhang;Pengjie Zhao;Leiyu Wang;Mohamed-Slim Alouini
This paper proposes a generalized beamspace modulation using multiplexing (GBMM) scheme for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communications with reduced radio frequency (RF) chains. Besides achieving a multiplexing gain over the selected beamspace set, GBMM additionally makes use of the index of the beamspace set to carry information. In the proposed GBMM, the beamspa...Show More
Generalized Beamspace Modulation using Multiplexing for mmWave MIMO
Shuaishuai Guo;Haixia Zhang;Peng Zhang;Pengjie Zhao;Leiyu Wang;Mohamed-Slim Alouini
ICC 2019 - 2019 IEEE International Conference on Communications (ICC)
Year: 2019 | Conference Paper |
Spatial multiplexing (SMX) multiple-input multiple-output (MIMO) over the best beamspace was considered as the best solution for millimeter wave (mm ave) communications regarding spectral efficiency (SE), referred as the best beamspace selection (BBS) solution. The equivalent MIMO water-filling (F-MIMO) channel capacity was treated as an unsurpassed SE upper bound. Recently, researchers have propo...Show More
Energy-Delay Aware User Association in mmWave Backhaul Networks using Matching Theory
Leiyu Wang;Haixia Zhang;Jingping Qiao;Xiaotian Zhou;Dongfeng Yuan
ICC 2019 - 2019 IEEE International Conference on Communications (ICC)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
This paper investigates an energy efficiency (EE) and delay aware user association problem in millimeter wave (mmWave) downlink networks, in which the wire backhaul links are replaced by the wireless backhaul links to transmit traffic data. To characterize the mmWave network delay performance, the queue theory is adopted and an M/M/1 tandem queuing model is introduced to capture the ...Show More
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