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 "robust beamforming with pilot reuse scheduling in a heterogeneous cloud radio access network"):
  Abstract: This paper considers a downlink ultra-dense heterogeneous cloud radio access network (H-CRAN) which guarantees seamless coverage and can provide high date rates. In order to reduce channel state information (CSI) feedback overhead, incomplete inter-cluster CSI is considered, i.e., each remote radio head (RRH) or macro base station (MBS) only measures the CSI from user equipments (UEs) in its serving cluster. To reduce pilot consumption, pilot reuse among UEs is assumed, resulting in imperfect intra-cluster CSI. A two-stage optimization problem is then formulated. In the first stage, a pilot scheduling algorithm is proposed to minimize the sum mean square error (MSE) of all channel estimates. Specifically, the minimum number of required pilots along with a feasible pilot allocation solution are first determined by applying the Dsatur algorithm, and adjustments based on the defined level of pilot contamination are then carried out for further improvement. Based on the pilot allocation result obtained in the first stage, the second stage aims to maximize the sum spectral efficiency (SE) of the network by optimizing the beam-vectors. Due to incomplete inter-cluster CSI and imperfect intra-cluster CSI, an explicit expression of each UE's achievable rate is unavailable. Hence, a lower bound on the achievable rate is derived based on Jensen's inequality, and an alternative robust transmission design (RTD) algorithm along with its distributed realization are then proposed to maximize the derived tight lower bound. Simulation results show that compared with existing algorithms, the system performance can be greatly improved by the proposed algorithms in terms of both sum MSE and sum SE.

Includes members:
  Member "joint precoding and rrh selection for user centric green mimo c ran":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hybrid precoder design for cache enabled millimeter wave radio access networks")
  Member "joint user selection and energy minimization for ultra dense multi channel c ran with incomplete csi":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "boosting fronthaul capacity global optimization of power sharing for centralized radio access network")
  Member "energy efficient resource allocation optimization for multimedia heterogeneous cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep reinforcement learning based mode selection and resource management for green fog radio access networks")
  Member "robust pilot decontamination based on joint angle and power domain discrimination":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "performance of multi cell massive mimo systems with interference decoding")
  Member "energy efficient joint congestion control and resource optimization in heterogeneous cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "secure millimeter wave cloud radio access networks relying on microwave multicast fronthaul")
  Member "energy efficiency of downlink transmission strategies for cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sparse optimization for green edge ai inference")
  Member "contract based interference coordination in heterogeneous cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep reinforcement learning based mode selection and resource management for green fog radio access networks")
  Member "coordinated shared spectrum precoding with distributed csit":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a practical spectrum sharing scheme for cognitive radio networks design and experiments")

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)