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 "seek and decode random access with physical layer network coding and multiuser detection"):
  Abstract: We present a novel cross layer approach to random access (RA) that combines physical-layer network coding (PLNC) with multiuser detection (MUD). PLNC and MUD are applied jointly at the physical level in order to extract any linear combination of messages experiencing a collision. The set of combinations extracted from a whole frame is then processed by the receiver to recover the original packets. A simple pre-coding stage at the transmitting terminals allows the receiver to further increase system diversity. We derive an analytical bound on the system throughput and present simulation results for the decoding at the physical level as well as several performance measures at frame level in block fading channels, namely throughput, packet loss rate and energy efficiency. The results we present are promising and suggest that a cross layer approach leveraging on the joint use of PLNC and MUD can significantly improve the performance of RA systems.

Includes members:
  Member "on the subtleties of q pam linear physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coherent detection for short packet physical layer network coding with fsk modulation")
  Member "coded slotted aloha a graph based method for uncoordinated multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "phase transition analysis for covariance based massive random access with massive mimo")
  Member "coded random access applying codes on graphs to design random access protocols":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "massive unsourced random access based on uncoupled compressive sensing another blessing of massive mimo")
  Member "improved channel estimation for interference cancellation in random access methods for satellite communications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "estimation of timing offsets and phase shifts between packet replicas in marsala random access")
  Member "characterization of coded random access with compressive sensing based multi user detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards massive connectivity support for scalable mmtc communications in 5g networks")
  Member "network coded multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "random access for massive machine type communications")
  Member "random access with physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "random access for massive machine type communications")
  Member "reliable physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "towards massive connectivity support for scalable mmtc communications in 5g networks")

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.NI(Networking and Internet Architecture)