human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "characterization of coded random access with compressive sensing based multi user detection"
  Abstract: The emergence of Machine-to-Machine (M2M) communication requires new Medium Access Control (MAC) schemes and physical (PHY) layer concepts to support a massive number of access requests. The concept of coded random access, introduced recently, greatly outperforms other random access methods and is inherently capable to take advantage of the capture effect from the PHY layer. Furthermore, at the PHY layer, compressive sensing based multi-user detection (CS-MUD) is a novel technique that exploits sparsity in multi-user detection to achieve a joint activity and data detection. In this paper, we combine coded random access with CS-MUD on the PHY layer and show very promising results for the resulting protocol.

Connected through hyperedge HE-1 (induced by source paper "towards massive connectivity support for scalable mmtc communications in 5g networks"):
  with members:
    - "a random access protocol for pilot allocation in crowded massive mimo systems"
    - "compressive coded random access for massive mtc traffic in 5g systems"
    - "reliable and efficient access for alarm initiated and regular m2m traffic in ieee 802 11ah systems"
    - "massive machine type communication mmtc access with integrated authentication"
    - "reliable recovery of hierarchically sparse signals and application in machine type communications"
    - "pulse shaped ofdm for 5g systems"
    - "coded pilot access a random access solution for massive mimo systems"
    - "random access for massive mimo systems with intra cell pilot contamination"

Connected through hyperedge HE-2 (induced by source paper "performance of hierarchical sparse detectors for massive mtc"):
  with members:
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "random pilot and data access in massive mimo for machine type communications"
    - "reliable recovery of hierarchically sparse signals and application in machine type communications"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "compressive random access using a common overloaded control channel"
    - "asynchronous code division random access using convex optimization"
    - "model based compressive sensing"

Connected through hyperedge HE-3 (induced by source paper "a pseudo bayesian approach to sign compute resolve slotted aloha"):
  with members:
    - "coded random access applying codes on graphs to design random access protocols"
    - "sign compute resolve for random access"
    - "bounded contention coding for wireless networks in the high snr regime"
    - "random access with physical layer network coding"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-4 (induced by source paper "compressive coded random access for massive mtc traffic in 5g systems"):
  with members:
    - "compressive random access using a common overloaded control channel"
    - "sparse signal processing concepts for efficient 5g system design"
    - "coded random access applying codes on graphs to design random access protocols"
    - "coded random access how coding theory helps to build random access protocols"
    - "exploiting capture effect in frameless aloha for massive wireless random access"

Connected through hyperedge HE-5 (induced by source paper "sparse signal processing concepts for efficient 5g system design"):
  with members:
    - "self calibration and biconvex compressive sensing"
    - "robust iterative interference alignment for cellular networks with limited feedback"
    - "the achievable performance of convex demixing"
    - "a stability result for sparse convolutions"
    - "fundamentals of throughput maximization with random arrivals for m2m communications"
    - "five disruptive technology directions for 5g"
    - "the papr problem in ofdm transmission new directions for a long lasting problem"
    - "simultaneously structured models with application to sparse and low rank matrices"

Connected through hyperedge HE-6 (induced by source paper "cooperative slotted aloha for multi base station systems"):
  with members:
    - "coded slotted aloha a graph based method for uncoordinated multiple access"
    - "slotted aloha for networked base stations with spatial and temporal diversity"
    - "slotted aloha for networked base stations"
    - "coded random access how coding theory helps to build random access protocols"
    - "exploiting capture effect in frameless aloha for massive wireless random access"
    - "the throughput of slotted aloha with diversity"
    - "aloha random access that operates as a rateless code"
    - "spatially coupled random access on graphs"

Connected through hyperedge HE-7 (induced by source paper "seek and decode random access with physical layer network coding and multiuser detection"):
  with members:
    - "on the subtleties of q pam linear physical layer network coding"
    - "coded slotted aloha a graph based method for uncoordinated multiple access"
    - "coded random access applying codes on graphs to design random access protocols"
    - "improved channel estimation for interference cancellation in random access methods for satellite communications"
    - "network coded multiple access"
    - "random access with physical layer network coding"
    - "reliable physical layer network coding"

Question: Please tell me which class the center node 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)