Sparse Beamforming and User-Centric Clustering for Downlink Cloud Radio Access Network
Binbin Dai,Wei Yu +1 more
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TLDR
The proposed dynamic clustering algorithm can achieve significant performance gain over existing naive clustering schemes and is shown to solve the weighted sum rate maximization problem through a generalized weighted minimum mean square error approach.Abstract:
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 l 1 -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.read more
Citations
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A Joint Solution for Scheduling and Precoding in Multiuser MISO Downlink Channels
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Delay Guaranteed Network Association for Mobile Machines in Heterogeneous Cloud Radio Access Network
TL;DR: It is proved that this proactive network association scheme can guarantee that the queueing delay performance and the delay violation probability can be both smaller than a corresponding upper bound, which means both low-latency and ultra-reliable communication can be guaranteed.
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A two-timescale approach for network slicing in C-RAN.
He Zhang,Vincent W. S. Wong +1 more
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Posted Content
Energy Efficiency of Downlink Transmission Strategies for Cloud Radio Access Networks
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RRH clustering and transmit precoding for interference-limited 5G CRAN downlink
TL;DR: This work considers cloud RAN architecture and focuses on the downlink of an antenna domain (AD) exposed to external interference from neighboring ADs, and learns that in an interference-limited regime RRH clustering helps, i.e., performance when RRHs cooperate is superior to the performance when they don't.
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