human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "regularized zf in cooperative broadcast channels under distributed csit a large system analysis"
  Abstract: Obtaining accurate Channel State Information (CSI) at the transmitters (TX) is critical to many cooperation schemes such as Network MIMO, Interference Alignment etc. Practical CSI feedback and limited backhaul-based sharing inevitably creates degradations of CSI which are specific to each TX, giving rise to a distributed form of CSI. In the Distributed CSI (D-CSI) broadcast channel setting, the various TXs design elements of the precoder based on their individual estimates of the global multiuser channel matrix, which intuitively degrades performance when compared with the commonly used centralized CSI assumption. This paper tackles this challenging scenario and presents a first analysis of the rate performance for the distributed CSI multi-TX broadcast channel setting, in the large number of antenna regime. Using Random Matrix Theory (RMT) tools, we derive deterministic equivalents of the Signal to Interference plus Noise Ratio (SINR) for the popular regularized Zero-Forcing (ZF) precoder, allowing to unveil the price of distributedness for such cooperation methods.

Connected through hyperedge HE-1 (induced by source paper "hybrid precoding for massive mimo systems in cloud ran architecture with capacity limited fronthauls"):
  with members:
    - "layered downlink precoding for c ran systems with full dimensional mimo"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "on the number of rf chains and phase shifters and scheduling design with hybrid analog digital beamforming"
    - "channel covariance estimation in massive mimo frequency division duplex systems"
    - "hybrid beamforming for massive mimo a survey"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "fronthaul constrained cloud radio access networks insights and challenges"

Connected through hyperedge HE-2 (induced by source paper "robust regularized zf in cooperative broadcast channel under distributed csit"):
  with members:
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "network mimo transmitters with no csi can still be very useful"
    - "drone small cells in the clouds design deployment and performance analysis"
    - "linear precoding based on polynomial expansion reducing complexity in massive mimo"
    - "multihop backhaul compression for the uplink of cloud radio access networks"
    - "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback"
    - "completely stale transmitter channel state information is still very useful"
    - "a scalable limited feedback design for network mimo using per cell product codebook"

Question: Please tell me which class the center node 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)