A5014004455- Cooperative Communication and Network Coding
- Caching and Content Delivery
- Advanced MIMO Systems Optimization
- Opportunistic and Delay-Tolerant Networks
- Advanced Wireless Communication Technologies
- Advanced Wireless Network Optimization
- Advanced Wireless Communication Techniques
- Energy Harvesting in Wireless Networks
- Wireless Communication Networks Research
- PAPR reduction in OFDM
- Recommender Systems and Techniques
- Full-Duplex Wireless Communications
- Millimeter-Wave Propagation and Modeling
- Antenna Design and Analysis
- Green IT and Sustainability
- IoT and Edge/Fog Computing
- Wireless Networks and Protocols
- Power Line Communications and Noise
- Microwave Dielectric Ceramics Synthesis
- Wireless Communication Security Techniques
- Indoor and Outdoor Localization Technologies
- Molecular Communication and Nanonetworks
- Multiferroics and related materials
- Cellular Automata and Applications
- Sharing Economy and Platforms
Southeast University
2016-2025
University of Jinan
2024
Harbin Institute of Technology
2021-2022
Shanghai Institute of Microsystem and Information Technology
2018-2020
Xidian University
2018-2020
Shanghai Research Center for Wireless Communications
2018-2019
Chinese Academy of Sciences
2018-2019
Central South University
2007
Hunan University
2004-2007
Jensen Hughes (United States)
2003
Abstract The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities in the process of standardized, such as mass connectivity, ultra-reliability, guaranteed low latency. However, 5G will not meet all requirements future 2030 beyond, sixth (6G) expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level security, etc. To these requirements, 6G rely on new enabling technologies, i.e., air...
In this paper, joint resource allocation and power control for energy-efficient device-to-device (D2D) communications underlaying cellular networks are investigated. The optimized maximization of the energy efficiency (EE) D2D communications. Exploiting properties fractional programming, we transform original nonconvex optimization problem in form into an equivalent subtractive form. Then, efficient iterative scheme is proposed. each iteration, part constraints EE removed by exploiting...
In this paper, the edge caching problem in fog radio access network (F-RAN) is investigated. By maximizing overall cache hit rate, optimization formulated to find optimal policy. Content popularity terms of time and space considered from perspective regional users. We propose an online content prediction algorithm by leveraging features user preferences, offline preference learning using gradient descent (OGD) method follow (proximally) regularized leader (FTRL-Proximal) method. Our proposed...
Base station cooperation in heterogeneous wireless networks (HetNets) is a promising approach to improve the network performance, but it also imposes significant challenge on backhaul. On other hand, caching at small base stations (SBSs) considered as an efficient way reduce backhaul load HetNets. In this paper, we jointly consider SBS and downlink large-scale HetNet. We propose two cooperative transmission schemes under random SBSs with distribution design parameter. Using tools from...
In this paper, the edge caching optimization problem in fog radio access networks (F-RANs) is investigated. Taking into account time-variant user requests and ultra-dense deployment of points (F-APs), we propose a distributed scheme to jointly minimize request service delay fronthaul traffic load. Considering interactive relationship among F-APs, model as stochastic differential game (SDG) which captures dynamics F-AP states. To address both intractability SDG capacity constraint, solve...
In this article, the edge caching policy in fog radio access networks (F-RANs) is optimized via deep learning. Considering that it hard for points (F-APs) to collect sufficient data of massive content features, our proposed only utilizes number requests and user location. an offline phase, we propose learn corresponding popularity prediction model every trend class location models make accurate, adaptive targeted. Moreover, develop a loss function avoid overfitting increase sensitivity high...
In this paper, we investigate the problem of asynchronous coded caching in fog radio access networks (F-RANs). To minimize fronthaul load, encoding set collapsing rule and partition method are proposed to establish relationship between coded-multicasting contents for synchronous caching. Furthermore, a decentralized scheme is proposed, which provides transmission methods different delay requirements. The closed-form expression load established special case where number requests during each...
In this paper, the hierarchical cooperative caching problem in fog radio access networks (F-RANs) is investigated. To minimize content request delay, we formulate optimization based on local popularity to find optimal policy, where both horizontal cooperation among points (F-APs) and vertical between cloud server F-APs are jointly considered. Considering non-deterministic polynomial hard (NP-hard) property of problem, propose a brain storm (BSO) approach which utilizes penalty-based fitness...
In this paper, the edge caching problem in fog radio access networks (F-RAN) is investigated. By maximizing cache hit rate, we formulate optimization to find optimal policy. Considering that users prefer request contents they are interested in, propose implement online content popularity prediction by leveraging features and user preferences, offline preference learning using "Follow The (Proximally) Regularized Leader" (FTRL-Proximal) algorithm "Online Gradient Descent" (OGD) method. Our...
In this paper, the distributed edge caching problem in fog radio access networks (F-RANs) is investigated. By considering unknown spatio-temporal content popularity and user preference, a request model based on hidden Markov process proposed to characterize fluctuant traffic demands F-RANs. Then, Q-learning method reinforcement learning (RL) framework put forth seek optimal policy manner, which enables points (F-APs) learn track potential dynamic without extra communications cost....
In this paper, energy efficient power allocation for downlink massive MIMO systems is investigated.A constrained non-convex optimization problem formulated to maximize the efficiency (EE), which takes into account quality of service (QoS) requirements.By exploiting properties fractional programming and lower bound user data rate, transformed a convex problem.The Lagrangian dual function method utilized convert an unconstrained one.Due multi-variable coupling caused by intra-user...
In this paper, the edge caching optimization problem in fog radio access networks (F-RANs) is investigated. Considering that points (F-APs) can offer cooperation gain by jointly transmitting same file or content diversity concurrently coded subfiles, we propose to use both joint transmission (JT) strategy and parallel (PT) serve users. Using tools from stochastic geometry, first derive expressions of successful probability (STP) under different strategies, then fractional offloaded traffic...
In this paper, cooperative edge caching problem is investigated in fog radio access networks (F-RANs). By considering the non-deterministic polynomial hard (NP-hard) property of problem, a federated deep reinforcement learning (FDRL) framework put forth to learn content strategy. Then, order overcome dimensionality curse and improve overall performance, we propose dueling Q-network based method find optimal policy distributed manner. Furthermore, horizontal (HFL) applied address issues...
To make better use of file diversity provided by random caching and improve the successful transmission probability (STP) a file, we consider retransmissions with discontinuous (DTX) in large-scale cache-enabled heterogeneous wireless network employing caching. We analyze optimize STP two mobility scenarios, i.e., high scenario static scenario. First, each scenario, using tools from stochastic geometry, obtain closed-form expression for general signal-to-interference ratio (SIR) threshold...
In this article, delay and energy efficiency (EE) are investigated in fog radio access networks (F-RANs) with hybrid caching. With multiple caching transmission strategies, offers great flexibility for file placement fetching. By using tools from stochastic geometry, we firstly derive tractable expressions of coded cached, non-partitioned cached uncached files. Then, EE by jointly considering power consumed circuits, transmissions fronthaul links. To balance EE, the corresponding...
As an important part of beyond the fifth-generation (B5G) and sixth-generation (6G) mobile communication systems, ultra-reliable low latency communications (uRLLC) puts forward strict requirements for delay reliability (e.g., 99.9999% <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$500 \mu \text{s}$ </tex-math></inline-formula> latency). At present, evaluation measures are usually based on infinite block...
In this paper, the content popularity prediction problem in cache-enabled fog radio access networks (F-RANs) is investigated. order to make accurate and adaptive, we propose learn corresponding model for every class from preprocessed series by training a simplified bidirectional long short-term memory (Bi-LSTM) network, further use it help build classifier terms of trend phase. Then, can be predicted right with respect predicting Considering that hard collect enough data about numerous...
In this paper, the cooperative caching problem in fog radio access networks (F-RAN) is investigated. To maximize incremental offloaded traffic, we formulate clustering optimization with consideration of and local content popularity, which falls into scope combinatorial programming. We then propose an effective graph-based approach to solve challenging problem. Firstly, a node graph constructed its vertex set representing considered points (F-APs) edge reflecting potential cooperations among...