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 efficiency of rate splitting multiple access and performance benefits over sdma and noma"):
  Abstract: Rate-Splitting Multiple Access (RSMA) is a general and powerful multiple access framework for downlink multiantenna systems, and contains Space-Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA) as special cases. RSMA relies on linearly precoded rate-splitting with Successive Interference Cancellation (SIC) to decode part of the interference and treat the remaining part of the interference as noise. Recently, RSMA has been shown to outperform both SDMA and NOMA rate-wise in a wide range of network loads (underloaded and overloaded regimes) and user deployments (with a diversity of channel directions, channel strengths and qualities of channel state information at the transmitter). Moreover, RSMA was shown to provide spectral efficiency and QoS enhancements over NOMA at a lower computational complexity for the transmit scheduler and the receivers. In this paper, we build upon those results and investigate the energy efficiency of RSMA compared to SDMA and NOMA. Considering a multiple-input single-output broadcast channel, we show that RSMA is more energy-efficient than SDMA and NOMA in a wide range of user deployments (with a diversity of channel directions and channel strengths). We conclude that RSMA is more spectrally and energy-efficient than SDMA and NOMA.

Includes members:
  Member "rate splitting multiple access for downlink communication systems bridging generalizing and outperforming sdma and noma":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rate splitting multiple access for multi antenna downlink communication systems spectral and energy efficiency tradeoff")
  Member "on the total energy efficiency of cell free massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "energy efficiency in mimo underlay and overlay device to device communications and cognitive radio systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rate splitting to mitigate residual transceiver hardware impairments in massive mimo systems")
  Member "energy efficient beam coordination strategies with rate dependent processing power":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")
  Member "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "rate splitting multiple access for multi antenna downlink communication systems spectral and energy efficiency tradeoff")
  Member "a survey of energy efficient techniques for 5g networks and challenges ahead":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "improving energy efficiency through multimode transmission in the downlink mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "rate splitting for multi antenna non orthogonal unicast and multicast transmission spectral and energy efficiency analysis")

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)