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 "noma based random access with multichannel aloha"):
  Abstract: In nonorthogonal multiple access (NOMA), the power difference of multiple signals is exploited for multiple access and successive interference cancellation (SIC) is employed at a receiver to mitigate co-channel interference. Thus, NOMA is usually employed for coordinated transmissions and mostly applied to downlink transmissions where a base station (BS) per- forms coordination for downlink transmissions with full channel state information (CSI). In this paper, however, we show that NOMA can also be employed for non-coordinated transmissions such as random access for uplink transmissions. We apply a NOMA scheme to multichannel ALOHA and show that the throughput can be improved. In particular, the resulting scheme is suitable for random access when the number of subchannels is limited since NOMA can effectively increase the number of subchannels without any bandwidth expansion.

Includes members:
  Member "massive machine type communications in 5g physical and mac layer solutions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "the application of mimo to non orthogonal multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mimo noma networks relying on reconfigurable intelligent surface a signal cancellation based design")
  Member "a general mimo framework for noma downlink and uplink transmission based on signal alignment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mimo noma networks relying on reconfigurable intelligent surface a signal cancellation based design")
  Member "sparse signal processing concepts for efficient 5g system design":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "faster activity and data detection in massive random access a multi armed bandit approach")
  Member "uplink non orthogonal multiple access for 5g wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non orthogonal multiple access for 5g and beyond")
  Member "fundamentals of throughput maximization with random arrivals for m2m communications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")

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)