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 efficient resource allocation in machine to machine communications with multiple access and energy harvesting for iot"):
  Abstract: This paper studies energy efficient resource allocation for a machine-to-machine enabled cellular network with nonlinear energy harvesting, especially focusing on two different multiple access strategies, namely nonorthogonal multiple access (NOMA) and time division multiple access (TDMA). Our goal is to minimize the total energy consumption of the network via joint power control and time allocation while taking into account circuit power consumption. For both NOMA and TDMA strategies, we show that it is optimal for each machine type communication device (MTCD) to transmit with the minimum throughput, and the energy consumption of each MTCD is a convex function with respect to the allocated transmission time. Based on the derived optimal conditions for the transmission power of MTCDs, we transform the original optimization problem for NOMA to an equivalent problem which can be solved suboptimally via an iterative power control and time allocation algorithm. Through an appropriate variable transformation, we also transform the original optimization problem for TDMA to an equivalent tractable problem, which can be iteratively solved. Numerical results verify the theoretical findings and demonstrate that NOMA consumes less total energy than TDMA at low circuit power regime of MTCDs, while at high circuit power regime of MTCDs TDMA achieves better network energy efficiency than NOMA.

Includes members:
  Member "on user pairing in noma uplink":
    also connected through other hyperedges:
      (none)
  Member "distributed user association in energy harvesting small cell networks an exchange economy with uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed task management in cyber physical systems how to cooperate under uncertainty")
  Member "wireless energy harvesting in a cognitive relay network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "interplay between noma and other emerging technologies a survey")
  Member "power allocation and scheduling for swipt systems with non linear energy harvesting model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transmit precoding and receive power splitting for harvested power maximization in mimo swipt systems")
  Member "wireless powered communication opportunities and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "downlink power control in two tier cellular networks with energy harvesting small cells as stochastic games":
    also connected through other hyperedges:
      (none)
  Member "power and load coupling in cellular networks for energy optimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a note on decoding order in optimizing multi cell noma")
  Member "practical non linear energy harvesting model and resource allocation for swipt systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")

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)