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: "cross layer optimization of wireless links under reliability and energy constraints"
  Abstract: The vision of connecting billions of battery operated devices to be used for diverse emerging applications calls for a wireless communication system that can support stringent reliability and latency requirements. Both reliability and energy efficiency are critical for many of these applications that involve communication with short packets which undermine the coding gain achievable from large packets. In this paper, we study a cross-layer approach to optimize the performance of low-power wireless links. At first, we derive a simple and accurate packet error rate (PER) expression for uncoded schemes in block fading channels based on a new proposition that shows that the waterfall threshold in the PER upper bound in Nakagami-m fading channels is tightly approximated by the m-th moment of an asymptotic distribution of PER in AWGN channel. The proposed PER approximation establishes an explicit connection between the physical and link layers parameters, and the packet error rate. We exploit this connection for cross-layer design and optimization of communication links. To this end, we propose a semi-analytic framework to jointly optimize signal-to-noise ratio (SNR) and modulation order at physical layer, and the packet length and number of retransmissions at link layer with respect to distance under the prescribed delay and reliability constraints.

Connected through hyperedge HE-1 (induced by source paper "energy reliability aware link optimization for battery powered iot devices with non ideal power amplifiers"):
  with members:
    - "energy efficiency maximization of full duplex two way relay with non ideal power amplifiers and non negligible circuit power"
    - "packet error rate analysis of uncoded schemes in block fading channels using extreme value theory"

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)