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: "relay selection and performance analysis in multiple user networks"
  Abstract: This paper investigates the relay selection (RS) problem in networks with multiple users and multiple common amplify-and-forward (AF) relays. Considering the overall quality-of-service of the network, we first specify our definition of optimal RS for multiple-user relay networks. Then an optimal RS (ORS) algorithm is provided, which is a straightforward extension of an RS scheme in the literature that maximizes the minimum end-to-end receive signal-to-noise ratio (SNR) of all users. The complexity of the ORS is quadratic in both the number of users and the number of relays. Then a suboptimal RS (SRS) scheme is proposed, which has linear complexity in the number of relays and quadratic complexity in the number of users. Furthermore, diversity orders of both the ORS and the proposed SRS are theoretically derived and compared with those of a naive RS scheme and the single-user RS network. It is shown that the ORS achieves full diversity; while the diversity order of the SRS decreases with the the number of users. For two-user networks, the outage probabilities and array gains corresponding to the minimum SNR of the RS schemes are derived in closed forms. It is proved that the advantage of the SRS over the naive RS scheme increases as the number of relays in the network increases. Simulation results are provided to corroborate the analytical results.

Connected through hyperedge HE-1 (induced by source paper "interleaved training and training based transmission design for hybrid massive antenna downlink"):
  with members:
    - "millimeter wave beam alignment large deviations analysis and design insights"
    - "codebook based hybrid precoding for millimeter wave multiuser systems"
    - "performance scaling law for multi cell multi user massive mimo"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "beam searching and transmission scheduling in millimeter wave communications"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "turbo like beamforming based on tabu search algorithm for millimeter wave massive mimo systems"

Connected through hyperedge HE-2 (induced by source paper "energy efficient resource assignment and power allocation in heterogeneous cloud radio access networks"):
  with members:
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "ergodic capacity analysis of remote radio head associations in cloud radio access networks"
    - "adaptive multi objective optimization for energy efficient interference coordination in multi cell networks"
    - "robust and efficient distributed compression for cloud radio access networks"

Connected through hyperedge HE-3 (induced by source paper "distributed compute and forward based relaying strategies in multi user multi relay networks"):
  with members:
    - "compute and forward on a multiaccess relay channel coding and symmetric rate optimization"
    - "a simple cooperative diversity method based on network path selection"

Connected through hyperedge HE-4 (induced by source paper "distributed beamforming in wireless multiuser relay interference networks with quantized feedback"):
  with members:
    - "distributed scalar quantization for computing high resolution analysis and extensions"
    - "interference alignment with limited feedback"
    - "combining beamforming and space time coding using noisy quantized feedback"
    - "grassmannian beamforming for mimo amplify and forward relaying"
    - "network beamforming using relays with perfect channel information"
    - "power bandwidth tradeoff in dense multi antenna relay networks"
    - "a simple cooperative diversity method based on network path selection"
    - "mimo broadcast channels with finite rate feedback"

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)