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: "jointly optimal channel pairing and power allocation for multichannel multihop relaying"
  Abstract: We study the problem of channel pairing and power allocation in a multichannel multihop relay network to enhance the end-to-end data rate. Both amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are considered. Given fixed power allocation to the channels, we show that channel pairing over multiple hops can be decomposed into independent pairing problems at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal, where each relay pairs its incoming and outgoing channels by their SNR order. For the joint optimization of channel pairing and power allocation under both total and individual power constraints, we show that the problem can be decoupled into two subproblems solved separately. This separation principle is established by observing the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution. It significantly reduces the computational complexity in finding the jointly optimal solution. It follows that the channel pairing problem in joint optimization can be again decomposed into independent pairing problems at each relay based on sorted channel gains. The solution for optimizing power allocation for DF relaying is also provided, as well as an asymptotically optimal solution for AF relaying. Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives. It is also observed that more gain is obtained from optimal channel pairing than optimal power allocation through judiciously exploiting the variation among multiple channels. Impact of the variation of channel gain, the number of channels, and the number of hops on the performance gain is also studied through numerical examples.

Connected through hyperedge HE-1 (induced by source paper "wireless information and energy transfer for two hop non regenerative mimo ofdm relay networks"):
  with members:
    - "distributed power splitting for swipt in relay interference channels using game theory"
    - "power allocation strategies in energy harvesting wireless cooperative networks"
    - "joint transmit beamforming and receive power splitting for miso swipt systems"
    - "interactive joint transfer of energy and information"
    - "throughput maximization for the gaussian relay channel with energy harvesting constraints"
    - "wireless information and power transfer in multiuser ofdm systems"
    - "wireless information and power transfer energy efficiency optimization in ofdma systems"
    - "relaying protocols for wireless energy harvesting and information processing"

Connected through hyperedge HE-2 (induced by source paper "wireless information and energy transfer for decode and forward relying mimo ofdm networks"):
  with members:
    - "wireless information and power transfer in multiuser ofdm systems"
    - "wireless information and power transfer architecture design and rate energy tradeoff"
    - "mimo broadcasting for simultaneous wireless information and power transfer"

Connected through hyperedge HE-3 (induced by source paper "jointly optimal channel and power assignment for dual hop multi channel multi user relaying"):
  with members:
    - "joint subcarrier pairing and power allocation for ofdm transmission with decode and forward relaying"
    - "optimization framework and graph based approach for relay assisted bidirectional ofdma cellular networks"
    - "distributive subband allocation power and rate control for relay assisted ofdma cellular system with imperfect system state knowledge"

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)