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: "downlink coordinated joint transmission for mutual information accumulation"
  Abstract: In this letter, we propose a new coordinated multipoint (CoMP) technique based on mutual information (MI) accumulation using rateless codes. Using a stochastic geometry model for the cellular downlink, we quantify the performance enhancements in coverage probability and rate due to MI accumulation. By simulation and analysis, we show that MI accumulation using rateless codes leads to remarkable improvements in coverage and rate for general users and specific cell edge users.

Connected through hyperedge HE-1 (induced by source paper "adaptive transmission in cellular networks do physical layer rateless codes supersede power control"):
  with members:
    - "rate statistics in cellular downlink phy rateless vs adaptive modulation and coding"
    - "system level modeling and optimization of the energy efficiency in cellular networks a stochastic geometry framework"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "the meta distribution of the sir for cellular networks with power control"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "enhanced cellular coverage and throughput using rateless codes"
    - "user point processes in cellular networks"
    - "rate splitting for mimo wireless networks a promising phy layer strategy for lte evolution"

Connected through hyperedge HE-2 (induced by source paper "outage correlation in finite and clustered wireless networks"):
  with members:
    - "effect of user mobility on the performance of device to device networks with distributed caching"
    - "interference functionals in poisson networks"
    - "modeling and performance analysis of clustered device to device networks"
    - "correlations of interference and link successes in heterogeneous cellular networks"
    - "managing interference correlation through random medium access"
    - "effect of spatial interference correlation on the performance of maximum ratio combining"
    - "a direct approach to computing spatially averaged outage probability"
    - "diversity polynomials for the analysis of temporal correlations in wireless networks"

Connected through hyperedge HE-3 (induced by source paper "unified analytical volume distribution of poisson delaunay simplex and its application to coordinated multi point transmission"):
  with members:
    - "optimal dynamic point selection for power minimization in multiuser downlink comp"
    - "random cell association and void probability in poisson distributed cellular networks"
    - "deploying dense networks for maximal energy efficiency small cells meet massive mimo"
    - "optimal cell load and throughput in green small cell networks with generalized cell association"
    - "spectral efficiency scaling laws in dense random wireless networks with multiple receive antennas"
    - "what will 5g be"
    - "worst case user analysis in poisson voronoi cells"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-4 (induced by source paper "the meta distribution of the sir for cellular networks with power control"):
  with members:
    - "ergodic spectral efficiency in mimo cellular networks"
    - "a primer on cellular network analysis using stochastic geometry"
    - "user point processes in cellular networks"
    - "d2d enhanced heterogeneous cellular networks with dynamic tdd"
    - "the meta distribution of the sir in poisson bipolar and cellular networks"
    - "deploying dense networks for maximal energy efficiency small cells meet massive mimo"
    - "stochastic geometry modeling of cellular networks analysis simulation and experimental validation"
    - "analyzing uplink sinr and rate in massive mimo systems using stochastic geometry"

Connected through hyperedge HE-5 (induced by source paper "enhanced cellular coverage and throughput using rateless codes"):
  with members:
    - "fountain codes with nonuniform selection distributions through feedback"
    - "user point processes in cellular networks"
    - "asymptotics and approximation of the sir distribution in general cellular networks"
    - "the meta distribution of the sir in poisson bipolar and cellular networks"
    - "the mean interference to signal ratio and its key role in cellular and amorphous networks"
    - "what will 5g be"
    - "a stochastic geometry analysis of inter cell interference coordination and intra cell diversity"
    - "a physical layer rateless code for wireless channels"

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)