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: "a greedy algorithm of data dependent user selection for fast fading gaussian vector broadcast channels"
  Abstract: User selection (US) with Zero-forcing beamforming is considered in fast fading Gaussian vector broadcast channels with perfect channel state information (CSI) at the transmitter. A novel criterion for US is proposed, which depends on both CSI and the data symbols, while conventional criteria only depend on CSI. Since the optimization of US based on the proposed criterion is infeasible, a greedy algorithm of data-dependent US is proposed to perform the optimization approximately. An overhead issue arises in fast fading channels: On every update of US, the transmitter might inform each user whether he/she has been selected, using a certain fraction of resources. This overhead results in a significant rate loss for fast fading channels. In order to circumvent this overhead issue, iterative detection and decoding schemes are proposed on the basis of belief propagation. The proposed iterative schemes require no information about whether each user has been selected. The proposed US scheme is compared to a data-independent US scheme. The complexity of the two schemes is comparable to each other for fast fading channels. Numerical simulations show that the proposed scheme can outperform the data-independent scheme for fast fading channels in terms of energy efficiency, bit error rate, and achievable sum rate.

Connected through hyperedge HE-1 (induced by source paper "large system analysis of joint user selection and vector precoding for multiuser mimo downlink"):
  with members:
    - "large system analysis of joint channel and data estimation for mimo ds cdma systems"
    - "sum rates rate allocation and user scheduling for multi user mimo vector perturbation precoding"
    - "tight bounds on the capacity of binary input random cdma systems"
    - "asymptotic analysis of general multiuser detectors in mimo ds cdma channels"
    - "vector precoding for wireless mimo systems and its replica analysis"
    - "analysis of cdma systems that are characterized by eigenvalue spectrum"
    - "randomly spread cdma asymptotics via statistical physics"

Connected through hyperedge HE-2 (induced by source paper "large system analysis of joint user selection and vector precoding with zero forcing transmit beamforming for mimo broadcast channels"):
  with members:
    - "large system analysis of joint user selection and vector precoding for multiuser mimo downlink"
    - "vector precoding for wireless mimo systems and its replica analysis"

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)