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: "optimal downlink transmission for cell free swipt massive mimo systems with active eavesdropping"
  Abstract: This paper considers secure simultaneous wireless information and power transfer (SWIPT) in cell-free massive multiple-input multiple-output (MIMO) systems. The system consists of a large number of randomly (Poisson-distributed) located access points (APs) serving multiple information users (IUs) and an information-untrusted dual-antenna active energy harvester (EH). The active EH uses one antenna to legitimately harvest energy and the other antenna to eavesdrop information. The APs are networked by a centralized infinite backhaul which allows the APs to synchronize and cooperate via a central processing unit (CPU). Closed-form expressions for the average harvested energy (AHE) and a tight lower bound on the ergodic secrecy rate (ESR) are derived. The obtained lower bound on the ESR takes into account the IUs' knowledge attained by downlink effective precoded-channel training. Since the transmit power constraint is per AP, the ESR is nonlinear in terms of the transmit power elements of the APs and that imposes new challenges in formulating a convex power control problem for the downlink transmission. To deal with these nonlinearities, a new method of balancing the transmit power among the APs via relaxed semidefinite programming (SDP) which is proved to be rank-one globally optimal is derived. A fair comparison between the proposed cell-free and the colocated massive MIMO systems shows that the cell-free MIMO outperforms the colocated MIMO over the interval in which the AHE constraint is low and vice versa. Also, the cell-free MIMO is found to be more immune to the increase in the active eavesdropping power than the colocated MIMO.

Connected through hyperedge HE-1 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo"):
  with members:
    - "max min fair wireless powered cell free massive mimo for uncorrelated rician fading channels"
    - "scalability aspects of cell free massive mimo"
    - "scalable cell free massive mimo systems"
    - "massive mimo with spatially correlated rician fading channels"
    - "performance of cell free massive mimo with rician fading and phase shifts"
    - "multiple antenna technologies for beyond 5g"
    - "making cell free massive mimo competitive with mmse processing and centralized implementation"
    - "massive mimo has unlimited capacity"

Connected through hyperedge HE-2 (induced by source paper "max min fair wireless powered cell free massive mimo for uncorrelated rician fading channels"):
  with members:
    - "scalability aspects of cell free massive mimo"
    - "massive mimo with spatially correlated rician fading channels"
    - "performance of cell free massive mimo with rician fading and phase shifts"
    - "multiple antenna technologies for beyond 5g"
    - "making cell free massive mimo competitive with mmse processing and centralized implementation"
    - "optimization of power transfer efficiency and energy efficiency for wireless powered systems with massive mimo"
    - "green cell less design for rf wireless power transfer networks"
    - "performance of cell free massive mimo systems with mmse and lsfd receivers"

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)