Energy Efficient User Association, Resource Allocation and Caching Deployment in Fog Radio Access Networks

Liu, Xiangnan; Zhang, Haijun; Long, Keping; Nallanathan, Arumugam; Leung, Victor C. M.

doi:10.1109/tvt.2021.3131720

Cited by 19 publications

(3 citation statements)

References 33 publications

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“…However, the challenge with this algorithm include computational complexity and potential suboptimality. The investigation in [33] optimized RAN for energy efficiency, reducing interference, and addressing power, bandwidth, and cache concerns.…”

Section: Literature Reviewmentioning

confidence: 99%

Framework for Optimized Resource Allocation in Multi-User, Multi-Service, Multi-Device Aerial Networks

Mushtaq,

Chughtai,

Zhang

et al. 2024

IEEE Access

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With the increasing prevalence of multi-user, multi-service, and heterogeneous multi-device environments, there is a need to address the imperative for efficient resource allocation in contemporary wireless networks, such as those involving unmanned aerial vehicles (UAVs) or drones. In this regard, this work addresses the challenges within a five-dimensional heterogeneous wireless network model, focusing on diverse services such as Big Data Analytics, Video Rendering, and Computer-Aided Design, and the allocation of resources among heterogeneous devices, including UAVs, tethered balloons, and multi-rotors. The resource allocation is facilitated through multiple interfaces like LTE, Wifi, LoRa, and Sigfox, catering to the diverse needs of users operating in aerial Networks. Additionally, this work introduces a novel Intelligent Relaxation using the Penalty Function (IRPF) approach for resource allocation, treating it as an integer programming problem to balance user needs while ensuring affordability. A comparative analysis is conducted between the proposed approach and the traditional branch-and-bound algorithm. In scenarios requiring resource allocation for numerous services based on user demand and device capabilities, the proposed work presents a penalty-based integrality gap solution adept at managing fractional values. The resulting optimization framework is meticulously designed to minimize activation and operating costs while optimizing utility. Additionally, the computing efficiency of the proposed approach is demonstrated by extensive simulations that prove its superiority over the traditional algorithm. Consequently, this research emphasizes the essential role of the proposed model in navigating the intricate challenges of resource allocation in modern drone-centric wireless networks.

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Section: Literature Reviewmentioning

confidence: 99%

Framework for Optimized Resource Allocation in Multi-User, Multi-Service, Multi-Device Aerial Networks

Mushtaq,

Chughtai,

Zhang

et al. 2024

IEEE Access

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“…In general, PRS Muting can be regarded as an interference management method for positioning purposes. For communication services in cellular networks, popular methods like power and channel access allocation [40], [41], task offloading [42] and user association [43] are widely used recently to improve the system utility. However, due to the difference between communication and positioning applications, the above management methods cannot be utilized in cellular positioning in a direct way.…”

Section: B Related Workmentioning

confidence: 99%

Management of Positioning Functions in Cellular Networks for Time-Sensitive Transportation Applications

Liu

Zhang

et al. 2023

IEEE Trans. Intell. Transport. Syst.

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“…It is assumed that the popularity distribution of files follows ZipF distribution [38]. The popularity will influence the caching effect.…”

Section: A System Modelmentioning

confidence: 99%

Multi-Agent DRL for Resource Allocation and Cache Design in Terrestrial-Satellite Networks

Zhang

Zhou

et al. 2023

IEEE Trans. Wireless Commun.

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In the past few years, satellite communications have greatly affected our daily lives, and the integrated terrestrialsatellite network can combine the advantages of satellite and base stations (BSs) to provide wider coverage and lower cost. Because the resources of terrestrial-satellite network are limited, how to allocate resources of terrestrial-satellite network through effective methods has become a major challenge. This paper proposes a framework for resource allocation of terrestrial-satellite network based on non-orthogonal multiple access (NOMA). Then, a deployment method of local cache pools is given to achieve lower time delay and maximize energy efficiency in terrestrialsatellite network. In the proposed framework, we adopt a multiagent deep deterministic policy gradient (MADDPG) method to obtain the maximum energy efficiency by user association, power control, and cache design. The MADDPG algorithm is divided into two stages, users and BSs are set as agents to complete the optimization problem in the framework. Finally, the simulation results show that the proposed method has better optimized performance compared with the traditional single-agent deep reinforcement learning algorithm and can efficiently solve the problems of resource allocation and cache design in the integrated terrestrial-satellite network.

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Energy Efficient User Association, Resource Allocation and Caching Deployment in Fog Radio Access Networks

Cited by 19 publications

References 33 publications

Framework for Optimized Resource Allocation in Multi-User, Multi-Service, Multi-Device Aerial Networks

Framework for Optimized Resource Allocation in Multi-User, Multi-Service, Multi-Device Aerial Networks

Management of Positioning Functions in Cellular Networks for Time-Sensitive Transportation Applications

Multi-Agent DRL for Resource Allocation and Cache Design in Terrestrial-Satellite Networks

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