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: "on the transmission computation energy tradeoff in wireless and fixed networks"
  Abstract: In this paper, a framework for the analysis of the transmission-computation-energy tradeoff in wireless and fixed networks is introduced. The analysis of this tradeoff considers both the transmission energy as well as the energy consumed at the receiver to process the received signal. While previous work considers linear decoder complexity, which is only achieved by uncoded transmission, this paper claims that the average processing (or computation) energy per symbol depends exponentially on the information rate of the source message. The introduced framework is parametrized in a way that it reflects properties of fixed and wireless networks alike. #R##N#The analysis of this paper shows that exponential complexity and therefore stronger codes are preferable at low data rates while linear complexity and therefore uncoded transmission becomes preferable at high data rates. The more the computation energy is emphasized (such as in fixed networks), the less hops are optimal and the lower is the benefit of multi-hopping. On the other hand, the higher the information rate of the single-hop network, the higher the benefits of multi-hopping. Both conclusions are underlined by analytical results.

Connected through hyperedge HE-1 (induced by source paper "energy efficient beam coordination strategies with rate dependent processing power"):
  with members:
    - "comparison of polar decoders with existing low density parity check and turbo decoders"
    - "optimal policies for wireless networks with energy harvesting transmitters and receivers effects of decoding costs"
    - "energy efficient precoder design for mimo ofdm with rate dependent circuit power"
    - "pilot reuse for massive mimo transmission over spatially correlated rayleigh fading channels"
    - "energy efficient scheduling and power allocation in downlink ofdma networks with base station coordination"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
    - "on the optimum energy efficiency for flat fading channels with rate dependent circuit power"
    - "a coordinated approach to channel estimation in large scale multiple antenna systems"

Connected through hyperedge HE-2 (induced by source paper "optimal policies for wireless networks with energy harvesting transmitters and receivers effects of decoding costs"):
  with members:
    - "iterative dynamic water filling for fading multiple access channels with energy harvesting"
    - "convex separable problems with linear constraints in signal processing and communications"
    - "energy harvesting broadband communication systems with processing energy cost"
    - "energy cooperation in energy harvesting communications"
    - "throughput maximization for the gaussian relay channel with energy harvesting constraints"
    - "optimal scheduling and power allocation for two hop energy harvesting communication systems"
    - "throughput optimal policies for energy harvesting wireless transmitters with non ideal circuit power"
    - "training optimization for energy harvesting communication systems"

Connected through hyperedge HE-3 (induced by source paper "base station switching problem for green cellular networks with social spider algorithm"):
  with members:
    - "a social spider algorithm for global optimization"

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)