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 probability of erasure for mimo ofdm"):
  Abstract: Detecting the presence of a valid signal is an important task of a telecommunication receiver. When the receiver is unable to detect the presence of a valid signal, due to noise and fading, it is referred to as an erasure. This work deals with the probability of erasure computation for orthogonal frequency division multiplexed (OFDM) signals used by multiple input multiple output (MIMO) systems. The theoretical results are validated by computer simulations. OFDM is widely used in present day wireless communication systems due to its ability to mitigate intersymbol interference (ISI) caused by frequency selective fading channels. MIMO systems offer the advantage of spatial multiplexing, resulting in increased bit-rate, which is the main requirement of the recent wireless standards like 5G and beyond.

Includes members:
  Member "data detection in single user massive mimo using re transmissions":
    also connected through other hyperedges:
      (none)
  Member "near capacity signaling over fading channels using coherent turbo coded ofdm and massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "data detection in single user massive mimo using re transmissions")
  Member "coherent detection of turbo coded ofdm signals transmitted through frequency selective rayleigh fading channels with receiver diversity and increased throughput":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data detection in single user massive mimo using re transmissions")

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)