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 "gpi based secrecy rate maximization beamforming scheme for wireless transmission with an aided directional modulation"):
  Abstract: In a directional modulation network, a general power iterative (GPI) based beamforming scheme is proposed to maximize the secrecy rate (SR), where there are two optimization variables required to be optimized. The first one is the useful precoding vector of transmitting confidential messages to the desired user while the second one is the artificial noise (AN) projection matrix of forcing more AN to eavesdroppers. In such a secure network, the paramount problem is how to design or optimize the two optimization variables by different criteria. To maximize the SR (Max-SR), an alternatively iterative structure (AIS) is established between the AN projection matrix and the precoding vector for confidential messages. To choose a good initial value of iteration process of GPI, the proposed Max-SR method can readily double its convergence speed compared to the random choice of initial value. With only four iterations, it may rapidly converge to its rate ceil. From simulation results, it follows that the SR performance of the proposed AIS of GPI-based Max-SR is much better than those of conventional leakage-based and null-space projection methods in the medium and large signal-to-noise ratio (SNR) regions, and its achievable SR performance gain gradually increases as SNR increases.

Includes members:
  Member "robust secure transmission of using main lobe integration based leakage beamforming in directional modulation mu mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient alternating iterative secure structure of maximizing secrecy rate for directional modulation networks")
  Member "symbol level and multicast precoding for multiuser multiantenna downlink a survey classification and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secure precise wireless transmission with random subcarrier selection based directional modulation transmit antenna array")
  Member "secure precise wireless transmission with random subcarrier selection based directional modulation transmit antenna array":
    also connected through other hyperedges:
      (none)
  Member "artificial noise aided secure transmission in wiretap channels with transmitter side correlation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "covert transmission with a self sustained relay")
  Member "directional modulation via symbol level precoding a way to enhance security":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "rethinking secure precoding via interference exploitation a smart eavesdropper perspective")
  Member "secrecy transmit beamforming for heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "secrecy outage and diversity analysis of multiple cooperative source destination pairs")
  Member "relay selection improves the security reliability trade off in cognitive radio systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading")

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)