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: "grant free rateless multiple access a novel massive access scheme for internet of things"
  Abstract: Rateless multiple access (RMA) is a novel non-orthogonal multiple access framework that is promising for massive access in Internet of Things due to its high efficiency and low complexity. In the framework, after certain registration, each active user, respectively, transmits to the access point randomly based on an assigned random access control function until receiving an acknowledgement. In this letter, by exploiting the intrinsic access pattern of each user, we propose a grant-free RMA scheme, which no longer needs the registration process as in the original RMA, thus greatly reduces the signaling overhead and system latency. Furthermore, we propose a low-complexity joint iterative detection and decoding algorithm in which the channel estimation, the active user detection, and the information decoding are done simultaneously. Finally, we propose a method based on density evolution to evaluate the system performance.

Connected through hyperedge HE-1 (induced by source paper "a dimension reduction based joint activity detection and channel estimation algorithm for massive access"):
  with members:
    - "design of non orthogonal beamspace multiple access for cellular internet of things"
    - "multi cell sparse activity detection for massive random access massive mimo versus cooperative mimo"
    - "improved scaling law for activity detection in massive mimo systems"
    - "grant free massive mtc enabled massive mimo a compressive sensing approach"
    - "sparse activity detection for massive connectivity"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "a new scaling law for activity detection in massive mimo systems"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"

Connected through hyperedge HE-2 (induced by source paper "joint activity detection and channel estimation for mmw thz wideband massive access"):
  with members:
    - "a dimension reduction based joint activity detection and channel estimation algorithm for massive access"
    - "faster activity and data detection in massive random access a multi armed bandit approach"
    - "grant free massive mtc enabled massive mimo a compressive sensing approach"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "millimeter wave channel estimation via exploiting joint sparse and low rank structures"
    - "massive mimo pilot decontamination and channel interpolation via wideband sparse channel estimation"
    - "simultaneously structured models with application to sparse and low rank matrices"

Connected through hyperedge HE-3 (induced by source paper "compressive massive access for internet of things cloud computing or fog computing"):
  with members:
    - "multi cell sparse activity detection for massive random access massive mimo versus cooperative mimo"
    - "towards massive connectivity support for scalable mmtc communications in 5g networks"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "compressive channel estimation and multi user detection in c ran"

Connected through hyperedge HE-4 (induced by source paper "compressive massive random access for massive machine type communications mmtc"):
  with members:
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "a random access protocol for pilot allocation in crowded massive mimo systems"
    - "compressive sensing techniques for next generation wireless communications"
    - "approximate message passing with nearest neighbor sparsity pattern learning"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "message passing algorithms for compressed sensing i motivation and construction"
    - "message passing algorithms for compressed sensing ii analysis and validation"

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)