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: "weighted sum rate maximization for downlink ofdma with subcarrier pair based opportunistic df relaying"
  Abstract: This paper addresses a weighted sum rate (WSR) maximization problem for downlink OFDMA aided by a decode-and-forward (DF) relay under a total power constraint. A novel subcarrier-pair based opportunistic DF relaying protocol is proposed. Specifically, user message bits are transmitted in two time slots. A subcarrier in the first slot can be paired with a subcarrier in the second slot for the DF relay-aided transmission to a user. In particular, the source and the relay can transmit simultaneously to implement beamforming at the subcarrier in the second slot. Each unpaired subcarrier in either the first or second slot is used for the source's direct transmission to a user. A benchmark protocol, same as the proposed one except that the transmit beamforming is not used for the relay-aided transmission, is also considered. For each protocol, a polynomial-complexity algorithm is developed to find at least an approximately optimum resource allocation (RA), by using continuous relaxation, the dual method, and Hungarian algorithm. Instrumental to the algorithm design is an elegant definition of optimization variables, motivated by the idea of regarding the unpaired subcarriers as virtual subcarrier pairs in the direct transmission mode. The effectiveness of the RA algorithm and the impact of relay position and total power on the protocols' performance are illustrated by numerical experiments. It is shown that for each protocol, it is more likely to pair subcarriers for relay-aided transmission when the total power is low and the relay lies in the middle between the source and user region. The proposed protocol always leads to a maximum WSR equal to or greater than that for the benchmark one, and the performance gain of using the proposed one is significant especially when the relay is in close proximity to the source and the total power is low. Theoretical analysis is presented to interpret these observations.

Connected through hyperedge HE-1 (induced by source paper "novel subcarrier pair based opportunistic df protocol for cooperative downlink ofdma"):
  with members:
    - "power minimization for ofdm transmission with subcarrier pair based opportunistic df relaying"
    - "wsr maximized resource allocation in multiple df relays aided ofdma downlink transmission"
    - "joint subcarrier pairing and power allocation for ofdm transmission with decode and forward relaying"
    - "sum rate maximized resource allocation in multiple df relays aided ofdm transmission"

Connected through hyperedge HE-2 (induced by source paper "on the optimum energy efficiency for flat fading channels with rate dependent circuit power"):
  with members:
    - "power minimization for ofdm transmission with subcarrier pair based opportunistic df relaying"
    - "framework for link level energy efficiency optimization with informed transmitter"
    - "sum rate maximized resource allocation in multiple df relays aided ofdm transmission"

Connected through hyperedge HE-3 (induced by source paper "power minimization for ofdm transmission with subcarrier pair based opportunistic df relaying"):
  with members:
    - "wsr maximized resource allocation in multiple df relays aided ofdma downlink transmission"
    - "sum rate maximized resource allocation in multiple df relays aided ofdm transmission"

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.SY(Systems and Control)