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 "a semiblind two way training method for discriminatory channel estimation in mimo systems"):
  Abstract: Discriminatory channel estimation (DCE) is a recently developed strategy to enlarge the performance difference between a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. Specifically, it makes use of properly designed training signals to degrade channel estimation at the UR, which in turn limits the UR's eavesdropping capability during data transmission. In this paper, we propose a new two-way training scheme for DCE through exploiting a whitening-rotation (WR) based semiblind method. To characterize the performance of DCE, a closed-form expression of the normalized mean squared error (NMSE) of the channel estimation is derived for both the LR and the UR. Furthermore, the developed analytical results on NMSE are utilized to perform optimal power allocation between the training signal and artificial noise (AN). The advantages of our proposed DCE scheme are twofold: Compared with the existing DCE scheme based on the linear minimum mean square error (LMMSE) channel estimator, the proposed scheme adopts a semiblind approach and achieves better DCE performance; and the proposed scheme is robust against active eavesdropping with the pilot contamination attack, whereas the existing scheme fails under such an attack.

Includes members:
  Member "on the secrecy outage capacity of physical layer security in large scale mimo relaying systems with imperfect csi":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "enabling security and high energy efficiency in the internet of things with massive mimo hybrid precoding")
  Member "two way training for discriminatory channel estimation in wireless mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the role of artificial noise in training and data transmission for secret communications")
  Member "on the design of artificial noise aided secure multi antenna transmission in slow fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "relay selection for two way relaying with amplify and forward protocols":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hybrid beamforming for reconfigurable intelligent surface based multi user communications achievable rates with limited discrete phase shifts")
  Member "robust beamforming for security in mimo wiretap channels with imperfect csi":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non orthogonal multiple access for 5g and beyond")
  Member "secure transmission with artificial noise over fading channels achievable rate and optimal power allocation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "secure massive mimo communication with low resolution dacs")

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)