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: "symbol level multiuser miso precoding for multi level adaptive modulation a multicast view"
  Abstract: Symbol-level precoding is a new paradigm for multiuser downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for MPSK modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. MQAM and APSK by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user SINR or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate.

Connected through hyperedge HE-1 (induced by source paper "energy efficient symbol level precoding in multiuser miso based on relaxed detection region"):
  with members:
    - "constructive interference through symbol level precoding for multi level modulation"
    - "constructive multiuser interference in symbol level precoding for the miso downlink channel"
    - "energy efficient symbol level precoding in multiuser miso channels"
    - "exploiting known interference as green signal power for downlink beamforming optimization"
    - "multicast multigroup precoding and user scheduling for frame based satellite communications"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"
    - "a multicast approach for constructive interference precoding in miso downlink channel"
    - "full frequency reuse multibeam satcoms frame based precoding and user scheduling"

Connected through hyperedge HE-2 (induced by source paper "directional modulation via symbol level precoding a way to enhance security"):
  with members:
    - "energy efficient symbol level precoding in multiuser miso based on relaxed detection region"
    - "secure m psk communication via directional modulation"
    - "joint power control in wiretap interference channels"
    - "secrecy analysis on network coding in bidirectional multibeam satellite communications"
    - "constructive interference through symbol level precoding for multi level modulation"
    - "constructive multiuser interference in symbol level precoding for the miso downlink channel"
    - "exploiting known interference as green signal power for downlink beamforming optimization"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"

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)