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: "massive mimo unsourced random access"
  Abstract: We consider an extension of the massive unsourced random access originally proposed by Polyanskiy to the case where the receiver has a very large number of antennas (a massive MIMO base station) and no channel state information is given to the receiver (fully non-coherent detection). Our coding approach borrows the concatenated coding idea from Amalladinne et. al., combined with a novel non-Bayesian `activity detection' algorithm for massive MIMO random access channels, that outperforms currently proposed Bayesian vector AMP (VAMP) schemes currently proposed for activity detection, and does not suffer from the numerical instabilities and requirement for accurate a priori statistics as VAMP. We show that the required transmit $E_b/N_0$ for reliable communication can be made arbitrarily small as the number of receiver antennas M grows sufficiently large.

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"
    - "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"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"

Connected through hyperedge HE-2 (induced by source paper "massive unsourced random access based on uncoupled compressive sensing another blessing of massive mimo"):
  with members:
    - "a joint graph based coding scheme for the unsourced random access gaussian channel"
    - "polar coding and random spreading for unsourced multiple access"
    - "generalized approximate message passing for massive mimo mmwave channel estimation with laplacian prior"
    - "an enhanced decoding algorithm for coded compressed sensing"
    - "sparcs for unsourced random access"
    - "improved scaling law for activity detection in massive mimo systems"
    - "a coupled compressive sensing scheme for unsourced multiple access"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"

Connected through hyperedge HE-3 (induced by source paper "massive mimo for internet of things iot connectivity"):
  with members:
    - "ultrareliable and low latency communication techniques for tactile internet services"
    - "non stationarities in extra large scale massive mimo"
    - "ubiquitous cell free massive mimo communications"
    - "sparcs for unsourced random access"
    - "management of network slicing in 5g radio access networks functional framework and information models"
    - "grant free massive mtc enabled massive mimo a compressive sensing approach"
    - "massive mimo for ultra reliable communications with constellations for dual coherent noncoherent detection"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"

Connected through hyperedge HE-4 (induced by source paper "sparcs for unsourced random access"):
  with members:
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "sparse signal processing for grant free massive iot connectivity"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "on or many access channels"
    - "device activity and embedded information bit detection using amp in massive mimo"
    - "state evolution for approximate message passing with non separable functions"
    - "mutual information and optimality of approximate message passing in random linear estimation"

Connected through hyperedge HE-5 (induced by source paper "energy efficient coded random access for the wireless uplink"):
  with members:
    - "fundamental limits of many user mac with finite payloads and fading"
    - "a joint graph based coding scheme for the unsourced random access gaussian channel"
    - "massive random access with common alarm messages"
    - "improved scaling law for activity detection in massive mimo systems"
    - "sparse activity detection for massive connectivity"
    - "sparse signal processing for grant free massive iot connectivity"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "achievability bounds for t fold irregular repetition slotted aloha scheme in the gaussian mac"

Connected through hyperedge HE-6 (induced by source paper "on the fundamental limits of mimo massive access communication"):
  with members:
    - "fundamental limits of many user mac with finite payloads and fading"
    - "improved scaling law for activity detection in massive mimo systems"
    - "sparse activity detection for massive connectivity"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "a new scaling law for activity detection in massive mimo systems"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "fundamental limits of low density spreading noma with fading"
    - "capacity of gaussian many access channels"

Connected through hyperedge HE-7 (induced by source paper "an enhanced decoding algorithm for coded compressed sensing"):
  with members:
    - "sparse regression codes"
    - "a joint graph based coding scheme for the unsourced random access gaussian channel"
    - "sparcs for unsourced random access"
    - "a coupled compressive sensing scheme for unsourced multiple access"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "the dynamics of message passing on dense graphs with applications to compressed sensing"

Connected through hyperedge HE-8 (induced by source paper "on the restricted isometry property of centered self khatri rao products"):
  with members:
    - "improved scaling law for activity detection in massive mimo systems"
    - "on the restricted isometry of the columnwise khatri rao product"
    - "multiple measurement vectors problem a decoupling property and its applications"
    - "sparse representation of a polytope and recovery of sparse signals and low rank matrices"

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)