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 "approximate capacity of the mimo relay channel"):
  Abstract: Capacity bounds are studied for the multiple-antenna complex Gaussian relay channel with t1 transmitting antennas at the sender, r2 receiving and t2 transmitting antennas at the relay, and r3 receiving antennas at the receiver. It is shown that the partial decode-forward coding scheme achieves within min(t1,r2) bits from the cutset bound and at least one half of the cutset bound, establishing a good approximate expression of the capacity. A similar additive gap of min(t1 + t2, r3) + r2 bits is shown to be achieved by the compress-forward coding scheme.

Includes members:
  Member "distributed decode forward for relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "capacity approximations for gaussian relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the arbitrarily varying relay channel")
  Member "the optimal input distribution for partial decode and forward in the mimo relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "uplink user assisted relaying in cellular networks")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "transmit signal and bandwidth optimization in multiple antenna relay channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "maximizing the partial decode and forward rate in the gaussian mimo relay channel")
  Member "slepian wolf coding over cooperative relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "gaussian relay channel capacity to within a fixed number of bits":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the capacity of the half duplex mimo gaussian diamond channel")
  Member "rate bounds for mimo relay channels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "maximizing the partial decode and forward rate in the gaussian mimo relay channel")

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)