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: "multiband spectrum access great promises for future cognitive radio networks"
  Abstract: Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises toward implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band-based networks.

Connected through hyperedge HE-1 (induced by source paper "a survey of multi objective optimization in wireless sensor networks metrics algorithms and open problems"):
  with members:
    - "distributed energy spectral efficiency optimization for partial full interference alignment in multi user multi relay multi cell mimo systems"
    - "energy efficient ofdma networks maintaining statistical qos guarantees for delay sensitive traffic"
    - "wireless sensor network virtualization a survey"
    - "markov decision processes with applications in wireless sensor networks a survey"
    - "accuracy of homology based coverage hole detection for wireless sensor networks on sphere"
    - "end to end reliability aware scheduling for wireless sensor networks"
    - "spectral and energy spectral efficiency optimization of joint transmit and receive beamforming based multi relay mimo ofdma cellular networks"
    - "achieving maximum energy efficiency in multi relay ofdma cellular networks a fractional programming approach"

Connected through hyperedge HE-2 (induced by source paper "reconfigurable wireless networks"):
  with members:
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "enhanced pilot based spectrum sensing algorithm"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "software defined networking state of the art and research challenges"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "multi user mimo scheduling in the fourth generation cellular uplink"
    - "optimal multiband joint detection for spectrum sensing in cognitive radio networks"
    - "femtocell networks a survey"

Connected through hyperedge HE-3 (induced by source paper "multiband spectrum sensing challenges and limitations"):
  with members:
    - "enhanced pilot based spectrum sensing algorithm"
    - "wideband spectrum sensing for cognitive radio networks a survey"
    - "beyond nyquist efficient sampling of sparse bandlimited signals"
    - "optimal multiband joint detection for spectrum sensing in cognitive radio networks"

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)