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 "friendly jamming in a mimo wiretap interference network a nonconvex game approach"):
  Abstract: We consider joint optimization of artificial noise (AN) and information signals in a MIMO wiretap interference network, wherein the transmission of each link may be overheard by several MIMO-capable eavesdroppers. Each information signal is accompanied with AN, generated by the same user to confuse nearby eavesdroppers. Using a noncooperative game, a distributed optimization mechanism is proposed to maximize the secrecy rate of each link. The decision variables here are the covariance matrices for the information signals and ANs. However, the nonconvexity of each link’s optimization problem (i.e., best response) makes conventional convex games inapplicable, even to find whether a Nash equilibrium (NE) exists. To tackle this issue, we analyze the proposed game using a relaxed equilibrium concept, called  quasi-NE  (QNE). Under a constraint qualification condition for each player’s problem, the set of QNEs includes the NE of the proposed game. We also derive the conditions for the existence and uniqueness of the resulting QNE. It turns out that the uniqueness conditions are too restrictive, and do not always hold in typical network scenarios. Thus, the proposed game often has multiple QNEs, and convergence to a QNE is not always guaranteed. To overcome these issues, we modify the utility functions of the players by adding several specific terms to each utility function. The modified game converges to a QNE even when multiple QNEs exist. Furthermore, players have the ability to select a desired QNE that optimizes a given social objective (e.g., sum rate or secrecy sum rate). Depending on the chosen objective, the amount of signaling overhead as well as the performance of resulting QNE can be controlled. Simulations show that not only can we guarantee the convergence to a QNE, but also due to the QNE selection mechanism, we can achieve a significant improvement in terms of secrecy sum rate and power efficiency, especially in dense networks.

Includes members:
  Member "joint power control in wiretap interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "physical layer security for rf satellite channels in the finite length regime")
  Member "physical layer security for massive mimo an overview on passive eavesdropping and active attacks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "real and complex monotone communication games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on cyber risk management of blockchain networks a game theoretic approach")
  Member "joint sensing and power allocation in nonconvex cognitive radio games nash equilibria and distributed algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed channel assignment in cognitive radio networks stable matching and walrasian equilibrium")
  Member "on secrecy rate of the generalized artificial noise assisted secure beamforming for wiretap channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "secure transmission with multiple antennas ii the mimome wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi antenna jamming in covert communication")
  Member "on the secure degrees of freedom in the k user gaussian interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint power control in wiretap interference channels")

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)