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 "spatial coordination strategies in future ultra dense wireless networks"):
  Abstract: Ultra network densification is considered a major trend in the evolution of cellular networks, due to its ability to bring the network closer to the user side and reuse resources to the maximum extent. In this paper we explore spatial resources coordination as a key empowering technology for next generation (5G) ultra-dense networks. We propose an optimization framework for flexibly associating system users with a densely deployed network of access nodes, opting for the exploitation of densification and the control of overhead signaling. Combined with spatial precoding processing strategies, we design network resources management strategies reflecting various features, namely local vs global channel state information knowledge exploitation, centralized vs distributed implementation, and non-cooperative vs joint multi-node data processing. We apply these strategies to future UDN setups, and explore the impact of critical network parameters, that is, the densification levels of users and access nodes as well as the power budget constraints, to users performance. We demonstrate that spatial resources coordination is a key factor for capitalizing on the gains of ultra dense network deployments.

Includes members:
  Member "evolution toward 5g multi tier cellular wireless networks an interference management perspective":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on the security and the evolution of osmotic and catalytic computing for 5g networks")
  Member "spatial resources optimization in distributed mimo networks with limited data sharing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep reinforcement learning based mode selection and resource management for green fog radio access networks")
  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-3 (induced by source paper "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems")

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.IT(Information Theory)