human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "optimal user cell association for massive mimo wireless networks"):
  Abstract: The use of a very large number of antennas at each base station site (referred to as "Massive MIMO") is one of the most promising approaches to cope with the predicted wireless data traffic explosion. In combination with Time Division Duplex and with simple per-cell processing, it achieves large throughput per cell, low latency, and attractive power efficiency performance. Following the current wireless technology trend of moving to higher frequency bands and denser small cell deployments, a large number of antennas can be implemented within a small form factor even in small cell base stations. In a heterogeneous network formed by large (macro) and small cell BSs, a key system optimization problem consists of "load balancing", that is, associating users to BSs in order to avoid congested hot-spots and/or under-utilized infrastructure. In this paper, we consider the user-BS association problem for a massive MIMO heterogeneous network. We formulate the problem as a network utility maximization, and provide a centralized solution in terms of the fraction of transmission resources (time-frequency slots) over which each user is served by a given BS. Furthermore, we show that such a solution is physically realizable, i.e., there exists a sequence of integer scheduling configurations realizing (by time-sharing) the optimal fractions. While this solution is optimal, it requires centralized computation. Then, we also consider decentralized user-centric schemes, formulated as non-cooperative games where each user makes individual selfish association decisions based only on its local information. We identify a class of schemes such that their Nash equilibrium is very close to the global centralized optimum. Hence, these user-centric algorithms are attractive not only for their simplicity and fully decentralized implementation, but also because they operate near the system "social" optimum.

Includes members:
  Member "an overview of load balancing in hetnets old myths and open problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks")
  Member "distributed linear precoder optimization and base station selection for an uplink heterogeneous network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "load balancing user association in millimeter wave mimo networks")
  Member "optimizing client association in 60 ghz wireless access networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks")
  Member "scalable synchronization and reciprocity calibration for distributed multiuser mimo":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "amplitude and phase estimation for absolute calibration of massive mimo front ends")
  Member "joint spatial division and multiplexing for mm wave channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "statistical beamforming for fdd downlink massive mimo via spatial information extraction and beam selection")
  Member "downlink multi antenna heterogeneous cellular network with load balancing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sdn enabled mimo heterogeneous cooperative networks with flexible cell association")
  Member "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems")
  Member "user association for load balancing in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")

Question: Please tell me which class the source paper 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.NI(Networking and Internet Architecture)