Joint Distributed Link Scheduling and Power Allocation for Content Delivery in Wireless Caching Networks
- Authors
- Choi, Minseok; Molisch, Andreas F.; Kim, Joongheon
- Issue Date
- 12월-2020
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Wireless communication; Scheduling; Interference; Resource management; Peer-to-peer computing; Delays; Clustering algorithms; Belief propagation; link scheduling; power allocation; matching algorithm; wireless caching
- Citation
- IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, v.19, no.12, pp.7810 - 7824
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
- Volume
- 19
- Number
- 12
- Start Page
- 7810
- End Page
- 7824
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/51339
- DOI
- 10.1109/TWC.2020.3016562
- ISSN
- 1536-1276
- Abstract
- In wireless caching networks, the design of the content delivery method must consider random user requests, caching states, network topology, and interference management. In this article, we establish a general framework for content delivery in wireless caching networks without stringent assumptions that restrict the network structure and interference model. Based on the framework, we propose a dynamic and distributed link scheduling and power allocation scheme for content delivery that is assisted by belief-propagation (BP) algorithms. The proposed scheme achieves three critical purposes of wireless caching networks: 1) limiting the delay of user request satisfactions, 2) maintaining the power efficiency of caching nodes, and 3) managing interference among users. In addition, we address the intrinsic problem of the BP algorithm in our network model, proposing a matching algorithm for one-to-one link scheduling. Simulation results show that the proposed scheme provides almost the same delay performance as the optimal scheme found through an exhaustive search at the expense of a little additional power consumption and does not require a clustering method and orthogonal resources in a large-scale D2D network.
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