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: "analog spatial cancellation for tackling the near far problem in wirelessly powered communications"
  Abstract: The implementation of wireless power transfer in wireless communication systems allow them to support communications with low-power passive nodes such as sensors and wearable computing devices, known as wirelessly powered communications (WPC). In next-generation heterogeneous networks where dense (or ultra-dense) smallcell base stations (BSs) are deployed, simultaneous wireless information and power transfer (SWIPT) is feasible over short ranges. One challenge for designing a WPC system is the severe near-far problem where a user attempts to decode an information-transfer (IT) signal (with the typical power of −50 to −90 dBm) in the presence of extremely strong SWIPT signals (with the typical power of several to hundreds of mW). Jointly quantizing the mixed signal causes the IT signal to be completely corrupted by quantization noise and thus the SWIPT signal has to be suppressed in the analog domain. This motivates the design of a framework in this paper for analog spatial cancellation in a multi-antenna WPC system comprising a (macro-cell) IT BS performing IT to a user in the presence of interfering (small-cell) SWIPT BSs, all of which are equipped with multi-antennas. Due to their extreme difference in transmission ranges, the IT and SWIPT are assumed to be over rich scattering and free-space channels, respectively. In the framework, an analog circuit at the user, which consists of simple phase shifters and adders, is adapted to cancel the SWIPT signals by multiplying it with a matrix having unit-modulus elements and full rank, called the cancellation matrix, where the full rank retains the spatial-multiplexing gain of the IT channel. The unit-modulus constraints render the conventional zero-forcing method unsuitable. Therefore, the paper presents a novel systematic approach for constructing cancellation matrices. For the case of single SWIPT BS, the matries are obtained as truncated Fourier or Hadamard matrices after compensating for propagation phase shifts over the SWIPT channel. For the more challenging case of multiple SWIPT BSs, it is proposed that each row of the cancellation matrix can be constructed as a Kronecker product of component vectors, each of which is designed to null the signal from a corresponding SWIPT BS similarly as in the preceding case. Considering all possible mappings between component vectors and SWIPT signals generates a mother set of candidate row vectors, from which a desired independent sub-set can be found to form the cancellation matrix.

Connected through hyperedge HE-1 (induced by source paper "hybrid beamforming via the kronecker decomposition for the millimeter wave massive mimo systems"):
  with members:
    - "modeling and analyzing millimeter wave cellular systems"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "compressed sensing based multi user millimeter wave systems how many measurements are needed"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "what will 5g be"

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)