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: "on interference alignment with imperfect csi characterizations of outage probability ergodic rate and ser"
  Abstract: In this paper, the autors give a unified performance analysis of interference alignment (IA) over multiple-input–multiple-output (MIMO) interference channels. Rather than the asymptotic characterization, i.e., degree of freedom (DOF) at high signal-to-noise ratio (SNR), the authors focus on the other practical performance metrics, namely, outage probability, ergodic rate, and symbol error rate (SER). In particular, the authors consider imperfect IA because the transmitters usually have only imperfect channel state information (CSI) in a practical scenario. By characterizing the impact of imperfect CSI, the authors derive the exact closed-form expressions of outage probability, ergodic rate, and SER in terms of CSI accuracy, transmit SNR, channel condition, number of antennas, and the number of data streams of each communication pair. Furthermore, the authors obtain some important guidelines for performance optimization of IA under imperfect CSI by minimizing the performance loss over IA with perfect CSI. Finally, the authors theoretical claims are validated by simulation results.

Connected through hyperedge HE-1 (induced by source paper "interference alignment and soft space reuse based cooperative transmission for multi cell massive mimo networks"):
  with members:
    - "structured compressive sensing based spatio temporal joint channel estimation for fdd massive mimo"
    - "two stage beamformer design for massive mimo downlink by trace quotient formulation"
    - "two stage subspace constrained precoding in massive mimo cellular systems"
    - "training sequence design for feedback assisted hybrid beamforming in massive mimo systems"
    - "two tier precoding for fdd multi cell massive mimo time varying interference networks"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "five disruptive technology directions for 5g"
    - "scaling up mimo opportunities and challenges with very large arrays"

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)