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 "study of relay selection for physical layer security in buffer aided relay networks based on the secrecy rate criterion"):
  Abstract: In this paper, we investigate an opportunistic relay and jammer scheme along with relay selection algorithms based on the secrecy rate criterion in multiple-input multiple-output buffer-aided down link relay networks, which consist of one source, a number of relay nodes, legitimate users and eavesdroppers, with the constraints of physical layer security. The opportunistic relay and jammer scheme is employed to improve the transmission rate and different relay selection policies are performed to achieve better secrecy rate with the consideration of eavesdroppers. Among all the investigated relay selection policies, a relay selection policy which is developed to maximize the secrecy rate based on exhaustive searches outperforms other relay selection policies in terms of secrecy rate. Based on the secrecy rate criterion, we develop a relay selection algorithm without knowledge of the channels of the eavesdroppers. We also devise a greedy search algorithm based on the secrecy rate criterion to reduce the computational complexity of the exhaustive search technique. Simulations show the superiority of the secrecy rate criterion over competing approaches.

Includes members:
  Member "multi branch tomlinson harashima precoding design for mu mimo systems theory and algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "study of compressed randomized utv decompositions for low rank matrix approximations in data science")
  Member "principles of physical layer security in multiuser wireless networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "angle aware user cooperation for secure massive mimo in rician fading channel")
  Member "buffer aided relaying with adaptive link selection fixed and mixed rate transmission":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance of energy buffer aided incremental relaying in cooperative networks")
  Member "multiuser diversity for secrecy communications using opportunistic jammer selection secure dof and jammer scaling law":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "effective optimization criteria and relay selection algorithms for physical layer security in multiple antenna relay networks")

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)