Sparse Beamforming and User-Centric Clustering for Downlink Cloud Radio Access Network

By Binbin Dai, Wei Yu. IEEE Access, 2014

381 citations recorded by the source corpus.

This paper considers a downlink cloud radio access network (C-RAN) in which all the base-stations (BSs) are connected to a central computing cloud via digital backhaul links with finite capacities. Each user is associated with a user-centric cluster of BSs; the central processor shares the user's data with the BSs in the cluster, which then cooperatively serve the user through joint beamforming. Under this setup, this paper investigates the user scheduling, BS clustering, and beamforming design problem from a network utility maximization perspective. Differing from previous works, this paper explicitly considers the per-BS backhaul capacity constraints. We formulate the network utility maximization problem for the downlink C-RAN under two different models depending on whether the BS clustering for each user is dynamic or static over different user scheduling time slots. In the former case, the user-centric BS cluster is dynamically optimized for each scheduled user along with the beamforming vector in each time-frequency slot, whereas in the latter case, the user-centric BS cluster is fixed for each user and we jointly optimize the user scheduling and the beamforming vector to account for the backhaul constraints. In both cases, the nonconvex per-BS backhaul constraints are approximated using the reweighted ℓ1-norm technique. This approximation allows us to reformulate the per-BS backhaul constraints into weighted per-BS power constraints and solve the weighted sum rate maximization problem through a generalized weighted minimum mean square error approach. This paper shows that the proposed dynamic clustering algorithm can achieve significant performance gain over existing naive clustering schemes. This paper also proposes two heuristic static clustering schemes that can already achieve a substantial portion of the gain.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/6964dde286738d1965162656becfd84ac77598a1

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Citations in the corpus

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues (2016, methodology): “[60], [80], [101], [104] Norm approximation Suitable for problems involving integer variables and bein g equivalent to a l0-norm Sub-optimal solution”
User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions (2021, methodology): “Distributed resource allocation schemes help scale down the complexity of optimized resource allocation.”
Content-Centric Sparse Multicast Beamforming for Cache-Enabled Cloud RAN (2015, background): “In the traditional user-centric BS clustering without cache [15], [17], each user is most likely to be served by a cluster of BSs which are nearby and have good channel conditions.”