human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "rrh clustering and transmit precoding for interference limited 5g cran downlink"):
  Abstract: In this work, we consider cloud RAN architecture and focus on the downlink of an antenna domain (AD) exposed to external interference from neighboring ADs. With system sum-rate as performance metric, and assuming that perfect channel state information is available at the aggregation node (AN), we implement i) a greedy user association algorithm, and ii) a greedy remote radio-head (RRH) clustering algorithm at the AN. We then vary the size of individual RRH clusters, and evaluate and compare the sum- rate gains due to two distinct transmit precoding schemes namely i) zero forcing beamforming (ZFBF), ii) coordinated beamforming (CB), when exposed to external interference of same kind. From system- level simulation results, we learn that in an interference-limited regime: i) RRH clustering helps, i.e., {\it cost-adjusted} performance when RRHs cooperate is superior to the performance when they don't, ii) for transmit precoding, the CB scheme is to be preferred over the ZFBF scheme. Finally, we discuss in detail the cost of RRH clustering, i.e., the piloting overhead (and the elements driving it), incorporate its impact on system sum-rate, and discuss its implications on the baseband processing capabilities of the RRHs.

Includes members:
  Member "fronthaul constrained cloud radio access networks insights and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the capacity regions of cloud radio access networks with limited orthogonal fronthaul")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "sparse beamforming and user centric clustering for downlink cloud radio access network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "secure millimeter wave cloud radio access networks relying on microwave multicast fronthaul")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)