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: "impact of received signal on self interference channel estimation and achievable rates in in band full duplex transceivers"
  Abstract: In this paper we analyze the effect of the calibration period, or lack of, on self-interference channel estimation in the digital domain of in-band full-duplex radio transceivers. In particular, we consider a scenario where the channel estimation must be performed without a separate calibration period, which means that the received signal of interest will act as an additional noise source from the estimation perspective. We will explicitly analyze its effect, and quantify the increase in the parameter estimation variance, or sample size, if similar accuracy for the channel estimate is to be achieved as with a separate calibration period. In addition, we will analyze how the calibration period, or its absence, affects the overall achievable rates. Full waveform simulations are then used to determine the validity of the obtained results, as well as provide numerical results regarding the achievable rates. It is shown that, even though a substantial increase in the parameter sample size is required if there is no calibration period, the achievable rates are still comparable for the two scenarios.

Connected through hyperedge HE-1 (induced by source paper "on the feasibility of full duplex large scale mimo cellular systems"):
  with members:
    - "full duplex cloud radio access network stochastic design and analysis"
    - "multi cell massive mimo beamforming in assuring qos for large numbers of users"
    - "compact full duplex mimo radios in d2d underlaid cellular networks from system design to prototype results"
    - "massive mimo ten myths and one critical question"
    - "performance analysis of massive mimo for cell boundary users"
    - "prototyping real time full duplex radios"
    - "compressed channel feedback for correlated massive mimo systems"
    - "performance analysis of self interference cancellation methods in full duplex large scale mimo systems"

Connected through hyperedge HE-2 (induced by source paper "multi tap digital canceller for full duplex applications"):
  with members:
    - "all digital self interference cancellation technique for full duplex systems"
    - "reference receiver based digital self interference cancellation in mimo full duplex transceivers"
    - "passive self interference suppression for full duplex infrastructure nodes"
    - "full duplex mobile device pushing the limits"
    - "experiment driven characterization of full duplex wireless systems"

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)