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 "sphere decoder with box optimization for ftn non orthogonal fdm system"):
  Abstract: In 1975, the pioneering work of J. E. Mazo showed the potential faster-than-Nyquist (FTN) gain of single-carrier binary signal. If the inter-symbol interference is eliminated by an optimal detector, the FTN single-carrier binary signal can transmit 24.7% more bits than the Nyquist signal without any loss of bit error rate performance, which is known as the Mazo limit. In this paper, we apply sphere decoder (SD) with box optimization (BO) to reduce inter-carrier interference (ICI) in FTN non-orthogonal frequency division multiplexing (FTN-NOFDM) system. Compared with the conventional SD, SD with BO can achieve the same performance to reduce ICI, but its average number of expanded nodes in search process is significantly decreased especially for high-order modulation format, which can reduce the complexity of the receiver. When the bandwidth compression factor $\alpha$ is set to 0.802, the transmission rate of QPSK-modulated FTN-NOFDM is 24.7% faster than the Nyquist rate, and it has almost the same performance as orthogonal frequency division multiplexing (OFDM), which agrees well with the Mazo limit. The QPSK-modulated FTN-NOFDM with $\alpha$ equal to 0.5 (the spectral efficiency is 4 bit/s/Hz) outperforms 16QAM-modulated OFDM by about 1.5 dB. The 16QAM-modulated FTN-NOFDM with $\alpha$ equal to 0.67 and 0.5 (the spectral efficiency is 6 bit/s/Hz and 8 bit/s/Hz, respectively) outperforms 64QAM-modulated and 256QAM-modulated OFDM by about 1.5 dB and 2 dB, respectively. Therefore, FTN-NOFDM will be a promising modulation scheme for the future bandwidth-limited wireless communications.

Includes members:
  Member "capacity limit for faster than nyquist non orthogonal frequency division multiplexing signaling":
    also connected through other hyperedges:
      (none)
  Member "reduced complexity optimal detection of binary faster than nyquist signaling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "low complexity detection of m ary psk faster than nyquist signaling")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")

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)