human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "multi rate sub nyquist spectrum sensing in cognitive radios"):
  Abstract: Wideband spectrum sensing is becoming increasingly important to cognitive radio (CR) systems for exploiting spectral opportunities. This paper introduces a novel multi-rate sub-Nyquist spectrum sensing (MS3) system that implements cooperative wideband spectrum sensing in a CR network. MS3 can detect the wideband spectrum using partial measurements without reconstructing the full frequency spectrum. Sub-Nyquist sampling rates are adopted in sampling channels for wrapping the frequency spectrum onto itself. This significantly reduces sensing requirements of CR. The effects of sub-Nyquist sampling are considered, and the performance of multi-channel sub-Nyquist samplings is analyzed. To improve its detection performance, sub-Nyquist sampling rates are chosen to be different such that the numbers of samples are consecutive prime numbers. Furthermore, when the received signals at CRs are faded or shadowed, the performance of MS3 is analytically evaluated. Numerical results show that the proposed system can significantly enhance the wideband spectrum sensing performance while requiring low computational and implementation complexities.

Includes members:
  Member "aggregate interference modeling in cognitive radio networks with power and contention control":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "interference modeling in cognitive radio networks a survey")
  Member "from theory to practice sub nyquist sampling of sparse wideband analog signals":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "image guided depth sampling and reconstruction")
  Member "enhanced compressive wideband frequency spectrum sensing for dynamic spectrum access":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sparse representation for wireless communications")
  Member "optimal multiband joint detection for spectrum sensing in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimization of the belief propagation algorithm for distributed detection by linear data fusion techniques")

Question: Please tell me which class the source paper 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)