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: "energy efficiency maximization via joint sub carrier assignment and power control for ofdma full duplex networks"
  Abstract: In this paper, we develop an energy efficient resource allocation scheme for orthogonal frequency division multiple access (OFDMA) networks with in-band full-duplex (IBFD) communication between the base station and user equipments (UEs) considering a realistic self-interference (SI) model. Our primary aim is to maximize the system energy efficiency (EE) through a joint power control and sub-carrier assignment in both the downlink (DL) and uplink (UL), where the quality of service requirements of the UEs in DL and UL are guaranteed. The formulated problem is non-convex due to the non-linear fractional objective function and the non-convex feasible set which is generally intractable. In order to handle this difficulty, we first use fractional programming to transform the fractional objective function to the subtractive form. Then, by employing Dinkelbach method, we propose an iterative algorithm in which an inner problem is solved in each iteration. Applying majorization-minimization approximation, we make the inner problem convex. Also, by introducing a penalty function to handle integer sub-carrier assignment variables, we propose an iterative algorithm for addressing the inner problem. We show that our proposed algorithm converges to the locally optimal solution which is also demonstrated by our simulation results. In addition, simulation results show that by applying the IBFD capability in OFDMA networks with efficient SI cancellation techniques, our proposed resource allocation algorithm attains a 75% increase in the EE as compared to the half-duplex system.

Connected through hyperedge HE-1 (induced by source paper "performance trade off between uplink and downlink in full duplex communications"):
  with members:
    - "energy and spectral efficiency tradeoff in ofdma networks via antenna selection strategy"
    - "massive access for 5g and beyond"
    - "multi objective optimization for energy and spectral efficiency tradeoff in in band full duplex ibfd communication"
    - "multiple antenna technologies for beyond 5g"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "throughput analysis for full duplex wireless networks with imperfect self interference cancellation"
    - "multi objective optimization for robust power efficient and secure full duplex wireless communication systems"
    - "in band full duplex wireless challenges and opportunities"

Connected through hyperedge HE-2 (induced by source paper "energy and spectral efficiency tradeoff in ofdma networks via antenna selection strategy"):
  with members:
    - "joint user association and resource allocation in the uplink of heterogeneous networks"
    - "multi objective optimization for energy and spectral efficiency tradeoff in in band full duplex ibfd communication"
    - "downlink energy efficiency of power allocation and wireless backhaul bandwidth allocation in heterogeneous small cell networks"
    - "spectral and energy efficiency trade offs in cellular networks"
    - "an overview of sustainable green 5g networks"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "energy efficient heterogeneous cellular networks with spectrum underlay and overlay access"

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)