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: "a cross layer perspective on energy harvesting aided green communications over fading channels"
  Abstract: We consider the power allocation of the physical layer and the buffer delay of the upper application layer in energy harvesting green networks. The total power required for reliable transmission includes the transmission power and the circuit power. The harvested power (which is stored in a battery) and the grid power constitute the power resource. The uncertainty of data generated from the upper layer, the intermittence of the harvested energy, and the variation of the fading channel are taken into account and described as independent Markov processes. In each transmission, the transmitter decides the transmission rate as well as the allocated power from the battery, and the rest of the required power will be supplied by the power grid. The objective is to find an allocation sequence of transmission rate and battery power to minimize the long-term average buffer delay under the average grid power constraint. A stochastic optimization problem is formulated accordingly to find such transmission rate and battery power sequence. Furthermore, the optimization problem is reformulated as a constrained MDP problem whose policy is a two-dimensional vector with the transmission rate and the power allocation of the battery as its elements. We prove that the optimal policy of the constrained MDP can be obtained by solving the unconstrained MDP. Then we focus on the analysis of the unconstrained average-cost MDP. The structural properties of the average optimal policy are derived. Moreover, we discuss the relations between elements of the two-dimensional policy. Next, based on the theoretical analysis, the algorithm to find the constrained optimal policy is presented for the finite state space scenario. In addition, heuristic policies with low-complexity are given for the general state space. Finally, simulations are performed under these policies to demonstrate the effectiveness.

Connected through hyperedge HE-1 (induced by source paper "energy efficient resource allocation for time varying ofdma relay systems with hybrid energy supplies"):
  with members:
    - "cross layer scheduling for ofdma based cognitive radio systems with delay and security constraints"
    - "power allocation for conventional and buffer aided link adaptive relaying systems with energy harvesting nodes"
    - "energy efficient resource allocation in ofdma systems with hybrid energy harvesting base station"
    - "maximizing energy efficiency in multi relay ofdma cellular networks"
    - "decentralized delay optimal control for interference networks with limited renewable energy storage"
    - "jointly optimal channel and power assignment for dual hop multi channel multi user relaying"
    - "adaptive power management for wireless base stations in a smart grid environment"
    - "wsr maximized resource allocation in multiple df relays aided ofdma downlink transmission"

Connected through hyperedge HE-2 (induced by source paper "self sustainability of energy harvesting systems concept analysis and design"):
  with members:
    - "performance analysis of ambient rf energy harvesting with repulsive point process modeling"
    - "energy harvesting wireless communications a review of recent advances"
    - "rf powered cognitive radio networks technical challenges and limitations"
    - "renewable powered cellular networks energy field modeling and network coverage"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "on green energy powered cognitive radio networks"

Connected through hyperedge HE-3 (induced by source paper "spectrum sharing in energy harvesting cognitive radio networks a cross layer perspective"):
  with members:
    - "delay optimal data transmission in renewable energy aided cognitive radio networks"
    - "hierarchic power allocation for spectrum sharing in ofdm based cognitive radio networks"

Connected through hyperedge HE-4 (induced by source paper "delay optimal data transmission in renewable energy aided cognitive radio networks"):
  with members:
    - "on green energy powered cognitive radio networks"

Connected through hyperedge HE-5 (induced by source paper "joint energy and spectrum cooperation for cellular communication systems"):
  with members:
    - "energy cooperation in energy harvesting communications"
    - "energy cooperation in cellular networks with renewable powered base stations"
    - "green cellular networks a survey some research issues and challenges"
    - "optimal energy allocation for wireless communications with energy harvesting constraints"

Connected through hyperedge HE-6 (induced by source paper "data driven stochastic models and policies for energy harvesting sensor communications"):
  with members:
    - "transmission with energy harvesting nodes in fading wireless channels optimal policies"

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)