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Article: Exploiting Reconfigurable Intelligent Surfaces in Edge Caching: Joint Hybrid Beamforming and Content Placement Optimization

TitleExploiting Reconfigurable Intelligent Surfaces in Edge Caching: Joint Hybrid Beamforming and Content Placement Optimization
Authors
Issue Date2021
Citation
IEEE Transactions on Wireless Communications, 2021, v. 20, p. 7799-7812 How to Cite?
AbstractEdge caching can effectively reduce backhaul burden at core network and increase quality-of-service at wireless edge nodes. However, the beneficial role of edge caching cannot be fully realized when the offloading link is in deep fade. Fortunately, the impairments induced by wireless propagation environments could be renovated by a reconfigurable intelligent surface (RIS). In this paper, a new RIS-aided edge caching system is proposed, where a network cost minimization problem is formulated to optimize content placement at cache units, active beamforming at base station and passive phase shifting at RIS. After decoupling the content placement subproblem with the hybrid beamforming design, we propose an alternating optimization algorithm to tackle the active beamforming and passive phase shifting. For active beamforming, we transfer the problem into a semidefinite programming (SDP) and prove that the optimal solution of SDP is always rank-one. For passive phase shifting, we introduce the block coordinate descent method to alternately optimize the auxiliary variables and the RIS phase shifts. Further, a conjugate gradient algorithm based on manifold optimization is proposed to deal with the non-convex unit-modulus constraints. Numerical results show that our RIS-aided edge caching design can effectively decrease the network cost by improving the quality of offloading links.
Persistent Identifierhttp://hdl.handle.net/10722/320833
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, Y-
dc.contributor.authorWen, M-
dc.contributor.authorBasar, E-
dc.contributor.authorWu, YC-
dc.contributor.authorWang, L-
dc.contributor.authorLiu, W-
dc.date.accessioned2022-11-01T04:42:06Z-
dc.date.available2022-11-01T04:42:06Z-
dc.date.issued2021-
dc.identifier.citationIEEE Transactions on Wireless Communications, 2021, v. 20, p. 7799-7812-
dc.identifier.urihttp://hdl.handle.net/10722/320833-
dc.description.abstractEdge caching can effectively reduce backhaul burden at core network and increase quality-of-service at wireless edge nodes. However, the beneficial role of edge caching cannot be fully realized when the offloading link is in deep fade. Fortunately, the impairments induced by wireless propagation environments could be renovated by a reconfigurable intelligent surface (RIS). In this paper, a new RIS-aided edge caching system is proposed, where a network cost minimization problem is formulated to optimize content placement at cache units, active beamforming at base station and passive phase shifting at RIS. After decoupling the content placement subproblem with the hybrid beamforming design, we propose an alternating optimization algorithm to tackle the active beamforming and passive phase shifting. For active beamforming, we transfer the problem into a semidefinite programming (SDP) and prove that the optimal solution of SDP is always rank-one. For passive phase shifting, we introduce the block coordinate descent method to alternately optimize the auxiliary variables and the RIS phase shifts. Further, a conjugate gradient algorithm based on manifold optimization is proposed to deal with the non-convex unit-modulus constraints. Numerical results show that our RIS-aided edge caching design can effectively decrease the network cost by improving the quality of offloading links.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Wireless Communications-
dc.titleExploiting Reconfigurable Intelligent Surfaces in Edge Caching: Joint Hybrid Beamforming and Content Placement Optimization-
dc.typeArticle-
dc.identifier.emailWu, YC: ycwu@eee.hku.hk-
dc.identifier.authorityWu, YC=rp00195-
dc.identifier.doi10.1109/TWC.2021.3087912-
dc.identifier.hkuros341147-
dc.identifier.volume20-
dc.identifier.spage7799-
dc.identifier.epage7812-
dc.identifier.isiWOS:000728926400010-

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