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: "coded slotted aloha a graph based method for uncoordinated multiple access"
  Abstract: In this paper, a random access scheme is introduced, which relies on the combination of packet erasure correcting codes and successive interference cancellation (SIC). The scheme is named coded slotted ALOHA. A bipartite graph representation of the SIC process, resembling iterative decoding of generalized low-density parity-check codes over the erasure channel, is exploited to optimize the selection probabilities of the component erasure correcting codes through a density evolution analysis. The capacity (in packets per slot) of the scheme is then analyzed in the context of the collision channel without feedback. Moreover, a capacity bound is developed, and component code distributions tightly approaching the bound are derived.

Connected through hyperedge HE-1 (induced by source paper "phase transition analysis for covariance based massive random access with massive mimo"):
  with members:
    - "a dimension reduction based joint activity detection and channel estimation algorithm for massive access"
    - "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver"
    - "massive mimo unsourced random access"
    - "joint active user detection and channel estimation in massive access systems exploiting reed muller sequences"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "online estimation and adaptation for random access with successive interference cancellation"):
  with members:
    - "maximum sum rate of slotted aloha with successive interference cancellation"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "random access protocols for massive mimo"
    - "aloha random access that operates as a rateless code"
    - "graph based random access for the collision channel without feedback capacity bound"

Connected through hyperedge HE-3 (induced by source paper "random noma with cross slot successive interference cancellation packet recovery"):
  with members:
    - "maximum sum rate of slotted aloha with successive interference cancellation"
    - "noma based random access with multichannel aloha"
    - "irregular repetition slotted aloha over the rayleigh block fading channel with capture"
    - "maximum sum rate of slotted aloha with capture"
    - "aloha random access that operates as a rateless code"

Connected through hyperedge HE-4 (induced by source paper "polar slotted aloha over slot erasure channels"):
  with members:
    - "faulty successive cancellation decoding of polar codes for the binary erasure channel"
    - "error floor analysis of coded slotted aloha over packet erasure channels"
    - "llr based successive cancellation list decoding of polar codes"
    - "coded random access applying codes on graphs to design random access protocols"
    - "list decoding of polar codes"

Connected through hyperedge HE-5 (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-6 (induced by source paper "massive access for future wireless communication systems"):
  with members:
    - "fundamental limits of many user mac with finite payloads and fading"
    - "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver"
    - "on the fundamental limits of mimo massive access communication"
    - "a joint graph based coding scheme for the unsourced random access gaussian channel"
    - "polar coding and random spreading for unsourced multiple access"
    - "energy efficient coded random access for the wireless uplink"
    - "sparcs for unsourced random access"
    - "random access channel coding in the finite blocklength regime"

Connected through hyperedge HE-7 (induced by source paper "fixed symbol aided random access scheme for machine to machine communications"):
  with members:
    - "deep learning methods for improved decoding of linear codes"
    - "sparse message passing based preamble estimation for crowded m2m communications"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "irregular repetition slotted aloha over the rayleigh block fading channel with capture"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"

Connected through hyperedge HE-8 (induced by source paper "dnn aided block sparse bayesian learning for user activity detection and channel estimation in grant free non orthogonal random access"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "fixed symbol aided random access scheme for machine to machine communications"
    - "deep learning methods for improved decoding of linear codes"
    - "asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "iterative channel estimation using lse and sparse message passing for mmwave mimo systems"

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)