Sparse Beamforming and User-Centric Clustering for Downlink Cloud Radio Access Network
Citations
468 citations
Cites background from "Sparse Beamforming and User-Centric..."
...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....
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Cites methods from "Sparse Beamforming and User-Centric..."
...Such a group sparsity property inspires us to apply CS to active RRH selection in green C-RANs to minimize the network power consumption [68], [69]....
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References
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Additional excerpts
...This equivalent expression allows us to use ideas from the compressive sensing literature [43], where a nonconvex l0-norm optimization objective can often be approximated by a convex reweightedl1-norm, i....
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1,911 citations
"Sparse Beamforming and User-Centric..." refers methods in this paper
...The C-RAN architecture can be thought of as a platform for the practical implementation of network multiple-inpu t multiple-output (MIMO) and coordinated multi-point (CoMP ) transmission concepts [3]....
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933 citations
"Sparse Beamforming and User-Centric..." refers methods in this paper
...The total number of variables in the equivalent SOCP problem is KLM and the computation complexity of using interiorpoint method to solve such an SOCP problem is approximately O((KLM)) [45]....
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882 citations
"Sparse Beamforming and User-Centric..." refers methods in this paper
...As related work, the WMMSE approach has also been adapted to solve the max-min fairness problem for MIMO interfering broadcast channel [36], a link flow rate control problem for the radio access network [37] and a power minimization problem under time-averaged user rate constraints for the CoMP architectur [38]....
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...It is not difficult to see that the generalized WMMSE equivalence established in [12] also extends to the problem (11) with the newly introduced weighted per-BS power constraint (11c)....
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...In this paper, we also adopt the WSR utility but point out that the proposed scheme can be readily extend to any utility function that holds an equivalence relationship with the WMMSE problem (see [12] for a sufficient condition on the utility functions holding such an equivalence)....
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...We explicitly take per-BS ba ckhaul capacity constraints into account in the network utili ty maximization framework, and use the l1-norm reweighting technique in compressive sensing and a generalized weighte d minimum mean square error (WMMSE) [11], [12] approach to solve the problem....
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...2) A novel application of the WMMSE approach is proposed to solve the utility maximization problem with backhaul constraints....
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