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: "hardware impairments aware transceiver design for bidirectional full duplex mimo ofdm systems"
  Abstract: In this paper we address the linear precoding and decoding design problem for a bidirectional orthogonal frequencydivision multiplexing (OFDM) communication system, between two multiple-input multiple-output (MIMO) full-duplex (FD) nodes. The effects of hardware distortion as well as the channel state information error are taken into account. In the first step, we transform the available time-domain characterization of the hardware distortions for FD MIMO transceivers to the frequency domain, via a linear Fourier transformation. As a result, the explicit impact of hardware inaccuracies on the residual selfinterference (RSI) and inter-carrier leakage (ICL) is formulated in relation to the intended transmit/received signals. Afterwards, linear precoding and decoding designs are proposed to enhance the system performance following the minimum-mean-squarederror (MMSE) and sum rate maximization strategies, assuming the availability of perfect or erroneous CSI. The proposed designs are based on the application of alternating optimization over the system parameters, leading to a necessary convergence. Numerical results indicate that the application of a distortionaware design is essential for a system with a high hardware distortion, or for a system with a low thermal noise variance.

Connected through hyperedge HE-1 (induced by source paper "rate splitting for massive mimo multi carrier system using full duplex decode and forward relay with hardware impairments"):
  with members:
    - "rate splitting robustness in multi pair massive mimo relay systems"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "massive mimo enabled full duplex cellular networks"
    - "hardware impairments aware transceiver for full duplex massive mimo relaying"
    - "rate analysis of two receiver miso broadcast channel with finite rate feedback a rate splitting approach"
    - "passive self interference suppression for full duplex infrastructure nodes"
    - "in band full duplex wireless challenges and opportunities"
    - "experiment driven characterization of full duplex wireless systems"

Connected through hyperedge HE-2 (induced by source paper "environment aware minimum cost wireless backhaul network planning with full duplex links"):
  with members:
    - "hardware impairments aware transceiver design for full duplex amplify and forward mimo relaying"
    - "sum rate analysis and optimization of self backhauling based full duplex radio access system"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "a survey of energy efficient techniques for 5g networks and challenges ahead"
    - "hardware impairments aware transceiver for full duplex massive mimo relaying"
    - "full duplex mimo small cell networks performance analysis"
    - "small cell in band wireless backhaul in massive mimo systems a cooperation of next generation techniques"
    - "5g wireless backhaul networks challenges and research advances"

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)