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 "energy reliability aware link optimization for battery powered iot devices with non ideal power amplifiers"):
  Abstract: In this paper, we study cross-layer optimization of low-power wireless links for reliability-aware applications while considering both the constraints and the non-ideal characteristics of the hardware in Internet-of-things (IoT) devices. Specifically, we define an energy consumption (EC) model that captures the energy cost---of transceiver circuitry, power amplifier, packet error statistics, packet overhead, etc.---in delivering a useful data bit. We derive the EC models for an ideal and two realistic non-linear power amplifier models. To incorporate packet error statistics, we develop a simple, in the form of elementary functions, and accurate closed-form packet error rate (PER) approximation in Rayleigh block-fading. Using the EC models, we derive energy-optimal yet reliability and hardware compliant conditions for limiting unconstrained optimal signal-to-noise ratio (SNR), and payload size. Together with these conditions, we develop a semi-analytic algorithm for resource-constrained IoT devices to jointly optimize parameters on physical (modulation size, SNR) and MAC (payload size and the number of retransmissions) layers in relation to link distance. Our results show that despite reliability constraints, the common notion---higher $M$-ary QAM modulations are energy optimal for short-range communication---prevails, and can provide up to 180% lifetime extension as compared to often employed OQPSK modulation in IoT devices. However, the reliability constraints reduce both their range and the energy efficiency, while non-ideal traditional PA reduces the range further by 50%, and diminishes the energy gains unless a better PA is employed.

Includes members:
  Member "energy efficiency maximization of full duplex two way relay with non ideal power amplifiers and non negligible circuit power":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficiency fairness for multi pair wireless powered relaying systems")
  Member "packet error rate analysis of uncoded schemes in block fading channels using extreme value theory":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "renewal theoretic packet collision modeling under long tailed heterogeneous traffic")
  Member "cross layer optimization of wireless links under reliability and energy constraints":
    also connected through other hyperedges:
      (none)

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)