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: "joint transmission mode and tilt adaptation in coordinated small cell wireless networks"
  Abstract: We focus on downlink transmission in a wireless network consisting of small-sized cells, denoted as a small-cell network (SCN). We consider multi-antenna base stations (BSs) and single-antenna users, BS coordination, downlink training and channel estimation, 3D antenna patterns, distant-dependent pathloss, and fair scheduling. We investigate the impact of the variable parameter that controls the elevation angleof the BS antenna pattern, denoted as tilt, on the performance of the considered SCN when employing either a conventional uncoordinated transmission mode or a fully coordinated transmission mode. Using the results of this investigation, we propose a novel hybrid-mode transmission technique that can achieve a performance comparable to that of a fully coordinated transmission but with a significantly lower complexity and signaling requirement. The main idea is to divide the coverage area into two so-called vertical regions and jointly adapt the transmission mode and the tilt at the BSs when serving each region. A fair scheduler is used to share the time-slots between the vertical regions and among the users in each region. To make the performance analysis computationally efficient, analytical expressions for the user ergodic rates at different transmission modes are also derived.

Connected through hyperedge HE-1 (induced by source paper "large scale mimo versus network mimo for multicell interference mitigation"):
  with members:
    - "massive mimo for next generation wireless systems"
    - "downlink mimo hetnets modeling ordering results and performance analysis"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling"
    - "downlink sdma with limited feedback in interference limited wireless networks"
    - "multi cell mimo downlink with cell cooperation and fair scheduling a large system limit analysis"
    - "multi antenna communication in ad hoc networks achieving mimo gains with simo transmission"
    - "base station cooperation on the downlink large system analysis"

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)