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: "harmonized cellular and distributed massive mimo load balancing and scheduling"
  Abstract: Multi-tier networks with large-array base stations (BSs) that are able to operate in the "massive MIMO" regime are envisioned to play a key role in meeting the exploding wireless traffic demands. Operated over small cells with reciprocity-based training, massive MIMO promises large spectral efficiencies per unit area with low overheads. Also, near-optimal user-BS association and resource allocation are possible in cellular massive MIMO HetNets using simple admission control mechanisms and rudimentary BS schedulers, since scheduled user rates can be predicted a priori with massive MIMO. #R##N#Reciprocity-based training naturally enables coordinated multi-point transmission (CoMP), as each uplink pilot inherently trains antenna arrays at all nearby BSs. In this paper we consider a distributed-MIMO form of CoMP, which improves cell-edge performance without requiring channel state information exchanges among cooperating BSs. We present methods for harmonized operation of distributed and cellular massive MIMO in the downlink that optimize resource allocation at a coarser time scale across the network. We also present scheduling policies at the resource block level which target approaching the optimal allocations. Simulations reveal that the proposed methods can significantly outperform the network-optimized cellular-only massive MIMO operation (i.e., operation without CoMP), especially at the cell edge.

Connected through hyperedge HE-1 (induced by source paper "cell free massive mimo versus small cells"):
  with members:
    - "cell free massive mimo uniformly great service for everyone"
    - "deploying dense networks for maximal energy efficiency small cells meet massive mimo"
    - "a comparative study of downlink mimo cellular networks with co located and distributed base station antennas"
    - "large scale mimo versus network mimo for multicell interference mitigation"
    - "dealing with interference in distributed large scale mimo systems a statistical approach"
    - "energy efficient large scale distributed antenna system l das for multiple users"
    - "interference reduction in multi cell massive mimo systems i large scale fading precoding and decoding"
    - "downlink mimo hetnets modeling ordering results and performance analysis"

Connected through hyperedge HE-2 (induced by source paper "user association and interference management in massive mimo hetnets"):
  with members:
    - "performance analysis of massive mimo for cell boundary users"
    - "algorithms for enhanced inter cell interference coordination eicic in lte hetnets"
    - "an overview of load balancing in hetnets old myths and open problems"
    - "optimal user cell association for massive mimo wireless networks"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "evolution toward 5g multi tier cellular wireless networks an interference management perspective"
    - "hierarchical radio resource optimization for heterogeneous networks with enhanced inter cell interference coordination eicic"

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)