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: "harvesting the self interference in heterogeneous full duplex networks for joint rate energy optimization"
  Abstract: Wireless nodes in future communication systems are expected to overcome three barriers when compared to their transitional counterparts, namely to support significantly higher data rates, have long-lasting energy supplies and remain fully operational in interference-limited heterogeneous networks. This could be achieved by providing three promising features, which are radio frequency (RF) energy harvesting, improper Gaussian signaling and operating in full-duplex communication mode, i.e., transmit and receive at the same time within the same frequency band. In this paper, we consider these aspects jointly in a multiantenna heterogeneous two-tier-network. Thus, the users in the femto-cell are sharing the scarce resources with the cellular users in the macro-cell and have to cope with the interference from the macro-cell base station as well as the transmitter noise and residual self-interference (RSI) due to imperfect fullduplex operation. Interestingly enough, while these impairments are detrimental from the achievable rate perspective, they are beneficial from the energy harvesting aspect as they carry RF energy. In this paper, we consider this natural trade-off jointly and propose appropriate optimization problems for beamforming and optimal resource allocation. Various receiver structures are employed for both information detection (ID) and energy harvesting (EH) capabilities. The paper aims at characterizing the tradeoff between the achievable rates and harvested energies. Rate and energy maximization problems are thoroughly investigated. Finally, the numerical illustrations demonstrate the impact of the energy harvesting on the achievable rate performance.

Connected through hyperedge HE-1 (induced by source paper "on the efficiency of widely linear precoding and symbol extension in cellular uplink"):
  with members:
    - "approximate capacity region of the mac ic mac"
    - "improper signaling and symbol extensions how far can we go with gaussian p2p codebooks in the interfering mac with tin"
    - "enabling the multi user generalized degrees of freedom in the gaussian cellular channel"
    - "transmit optimization with improper gaussian signaling for interference channels"
    - "interference alignment and neutralization in a cognitive 3 user mac interference channel degrees of freedom"

Connected through hyperedge HE-2 (induced by source paper "optimal power splitting for simultaneous information detection and energy harvesting"):
  with members:
    - "heterogeneous multi tier networks improper signaling for joint rate energy optimization"
    - "joint transceiver design algorithms for multiuser miso relay systems with energy harvesting"
    - "feedback enhances simultaneous wireless information and energy transmission in multiple access channels"
    - "noncoherent relaying in energy harvesting communication systems"
    - "simultaneous wireless information and power transfer in modern communication systems"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "joint transmit beamforming and receive power splitting for miso swipt systems"
    - "simultaneous information and power transfer for broadband wireless systems"

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)