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: "ergodic sum capacity of macrodiversity mimo systems in flat rayleigh fading"
  Abstract: The prospect of base station (BS) cooperation leading to joint combining at widely separated antennas has led to increased interest in macrodiversity systems, where both sources and receive antennas are geographically distributed. In this scenario, little is known analytically about channel capacity since the channel matrices have a very general form where each path may have a different power. Hence, in this paper we consider the ergodic sum capacity of a macrodiversity MIMO system with arbitrary numbers of sources and receive antennas operating over Rayleigh fading channels. For this system, we compute the exact ergodic capacity for a two-source system and a compact approximation for the general system, which is shown to be very accurate over a wide range of cases. Finally, we develop a highly simplified upper-bound which leads to insights into the relationship between capacity and the channel powers. Results are verified by Monte Carlo simulations and the impact on capacity of various channel power profiles is investigated

Connected through hyperedge HE-1 (induced by source paper "on the convergence and performance of mf precoding in distributed massive mu mimo systems"):
  with members:
    - "on the convergence of massive mimo systems"
    - "dealing with interference in distributed large scale mimo systems a statistical approach"
    - "massive mimo for next generation wireless systems"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "blind pilot decontamination"
    - "noncoherent trellis coded quantization a practical limited feedback technique for massive mimo systems"
    - "massive mu mimo downlink tdd systems with linear precoding and downlink pilots"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-2 (induced by source paper "performance analysis of macrodiversity mimo systems with mmse and zf receivers in flat rayleigh fading"):
  with members:
    - "performance analysis of dual user macrodiversity mimo systems with linear receivers in flat rayleigh fading"

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)