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 "on the exact and approximate eigenvalue distribution for sum of wishart matrices"):
  Abstract: The sum of Wishart matrices has an important role in multiple-input multiple-output (MIMO) multiple access channel (MAC) and MIMO relay channel. In this paper, we present a new closed-form expression for the marginal density of one of the unordered eigenvalues of a sum of   $K$   complex central Wishart matrices having covariance matrices proportional to the identity matrix. The expression is general and allows for any set of linear coefficients. The derived expression is used to obtain the ergodic sum-rate capacity for the MIMO-MAC and MIMO relay cases, both as closed-form expressions. We also present a very simple expression to approximate the sum of Wishart matrices by one equivalent Wishart matrix. The agreement between the exact eigenvalue distribution and numerical simulations is perfect, whereas for the approximate solution the difference is indistinguishable.

Includes members:
  Member "new results on the sum of gamma random variates with application to the performance of wireless communication systems over nakagami m fading channels":
    also connected through other hyperedges:
      (none)
  Member "mimo multichannel beamforming ser and outage using new eigenvalue distributions of complex noncentral wishart matrices":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "eigenvalue dynamics of a central wishart matrix with application to mimo systems")
  Member "capacity and character expansions moment generating function and other exact results for mimo correlated channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the capacity of fractal d2d social networks with hierarchical communications")

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)