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 "rate splitting for multi antenna non orthogonal unicast and multicast transmission"):
  Abstract: In a superimposed unicast and multicast transmission system, one layer of Successive Interference Cancellation (SIC) is required at each receiver to remove the multicast stream before decoding the unicast stream. In this paper, we show that a linearly-precoded Rate-Splitting (RS) strategy at the transmitter can efficiently exploit this existing SIC receiver architecture. By splitting the unicast messages into common and private parts and encoding the common parts along with the multicast message into a super-common stream decoded by all users, the SIC is used for the dual purpose of separating the unicast and multicast streams as well as better managing the multi-user interference between the unicast streams. The precoders are designed with the objective of maximizing the Weighted Sum Rate (WSR) of the unicast messages subject to a Quality of Service (QoS) requirement of the multicast message and a sum power constraint. Numerical results show that RS outperforms existing Multi-User Linear-Precoding (MU-LP) and power-domain Non-Orthogonal Multiple Access (NOMA) in a wide range of user deployments (with a diversity of channel directions and channel strengths). Moreover, since one layer of SIC is required to separate the unicast and multicast streams, the performance gain of RS comes without any increase in the receiver complexity compared with MU-LP. Hence, in such non-orthogonal unicast and multicast transmissions, RS provides rate and QoS enhancements at no extra cost for the receivers.

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 "energy efficient joint unicast and multicast beamforming with multi antenna user terminals":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rate splitting for multi antenna non orthogonal unicast and multicast transmission spectral and energy efficiency analysis")
  Member "joint base station clustering and beamforming for non orthogonal multicast and unicast transmission with backhaul constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  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-4 (induced by source paper "rate splitting multiple access for multi antenna downlink communication systems spectral and energy efficiency tradeoff")
  Member "rate splitting for mimo wireless networks a promising phy layer strategy for lte evolution":
    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 "sum rate maximization for mu miso with partial csit using joint multicasting and broadcasting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")

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)