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: "compressive random access using a common overloaded control channel"
  Abstract: We introduce a "one shot" random access procedure where users can send a message without a priori synchronizing with the network. In this procedure a common overloaded control channel is used to jointly detect sparse user activity and sparse channel profiles. The detected information is subsequently used to demodulate the data in dedicated frequency slots. We analyze the system theoretically and provide a link between achievable rates and standard compressing sensing estimates in terms of explicit expressions and scaling laws. Finally, we support our findings with simulations in an LTE-A-like setting allowing "one shot" sparse random access of 100 users in 1ms.

Connected through hyperedge HE-1 (induced by source paper "random access for massive machine type communications"):
  with members:
    - "beamwidth control for noma in hybrid mmwave communication systems"
    - "design of non orthogonal beamspace multiple access for cellular internet of things"
    - "on the performance gain of noma over oma in uplink single cell systems"
    - "multi beam noma for hybrid mmwave systems"
    - "joint pilot and payload power control for uplink mimo noma with mrc sic receivers"
    - "reliability based windowed decoding for spatially coupled ldpc codes"
    - "short packet downlink transmission with non orthogonal multiple access"
    - "a multi beam noma framework for hybrid mmwave systems"

Connected through hyperedge HE-2 (induced by source paper "joint active user detection and channel estimation in massive access systems exploiting reed muller sequences"):
  with members:
    - "reed muller sequences for 5g grant free massive access"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "random access for machine type communication based on bloom filtering"
    - "code expanded random access for machine type communications"
    - "reed muller sensing matrices and the lasso"

Connected through hyperedge HE-3 (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-4 (induced by source paper "hierarchical restricted isometry property for kronecker product measurements"):
  with members:
    - "low overhead hierarchically sparse channel estimation for multiuser wideband massive mimo"
    - "secure massive iot using hierarchical fast blind deconvolution"
    - "performance of hierarchical sparse detectors for massive mtc"
    - "hierarchical sparse channel estimation for massive mimo"
    - "channel acquisition for massive mimo ofdm with adjustable phase shift pilots"
    - "reliable recovery of hierarchically sparse signals and application in machine type communications"
    - "blind deconvolution meets blind demixing algorithms and performance bounds"
    - "sparse signal processing concepts for efficient 5g system design"

Connected through hyperedge HE-5 (induced by source paper "massive connectivity with massive mimo part i device activity detection and channel estimation"):
  with members:
    - "sparse activity detection for massive connectivity"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "a random access protocol for pilot allocation in crowded massive mimo systems"
    - "capacity of gaussian many access channels"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "sparse signal processing concepts for efficient 5g system design"
    - "massive mimo for next generation wireless systems"
    - "efficient high dimensional inference in the multiple measurement vector problem"

Connected through hyperedge HE-6 (induced by source paper "sparse activity detection for massive connectivity"):
  with members:
    - "capacity of gaussian many access channels"
    - "sparse signal processing concepts for efficient 5g system design"
    - "what will 5g be"
    - "efficient high dimensional inference in the multiple measurement vector problem"
    - "belief propagation for joint sparse recovery"
    - "accurate prediction of phase transitions in compressed sensing via a connection to minimax denoising"
    - "asymptotic analysis of complex lasso via complex approximate message passing camp"
    - "the dynamics of message passing on dense graphs with applications to compressed sensing"

Connected through hyperedge HE-7 (induced by source paper "secure massive iot using hierarchical fast blind deconvolution"):
  with members:
    - "regularized gradient descent a nonconvex recipe for fast joint blind deconvolution and demixing"
    - "compressive coded random access for massive mtc traffic in 5g systems"
    - "blind demixing and deconvolution at near optimal rate"
    - "rapid robust and reliable blind deconvolution via nonconvex optimization"
    - "reliable recovery of hierarchically sparse signals and application in machine type communications"
    - "blind deconvolution meets blind demixing algorithms and performance bounds"
    - "sparse signal processing concepts for efficient 5g system design"
    - "simultaneously structured models with application to sparse and low rank matrices"

Connected through hyperedge HE-8 (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"
    - "characterization of coded random access with compressive sensing based multi user detection"
    - "asynchronous code division random access using convex optimization"
    - "model based compressive sensing"

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)