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: "exploiting channel memory for joint estimation and scheduling in downlink networks"
  Abstract: We address the problem of opportunistic multiuser scheduling in downlink networks with Markov-modeled outage channels. We consider the scenario in which the scheduler does not have full knowledge of the channel state information, but instead estimates the channel state information by exploiting the memory inherent in the Markov channels along with ARQ-styled feedback from the scheduled users. Opportunistic scheduling is optimized in two stages: (1) Channel estimation and rate adaptation to maximize the expected immediate rate of the scheduled user; (2) User scheduling, based on the optimized immediate rate, to maximize the overall long term sum-throughput of the downlink. The scheduling problem is a partially observable Markov decision process with the classic 'exploitation vs exploration' trade-off that is difficult to quantify. We therefore study the problem in the framework of Restless Multi-armed Bandit Processes (RMBP) and perform a Whittle's indexability analysis. Whittle's indexability is traditionally known to be hard to establish and the index policy derived based on Whittle's indexability is known to have optimality properties in various settings. We show that the problem of downlink scheduling under imperfect channel state information is Whittle indexable and derive the Whittle's index policy in closed form. Via extensive numerical experiments, we show that the index policy has near-optimal performance. #R##N#Our work reveals that, under incomplete channel state information, exploiting channel memory for opportunistic scheduling can result in significant performance gains and that almost all of these gains can be realized using an easy-to-implement index policy.

Connected through hyperedge HE-1 (induced by source paper "low complexity optimal scheduling over time correlated fading channels with arq feedback"):
  with members:
    - "green communication via power optimized harq protocols"
    - "exploiting hybrid channel information for downlink multi user mimo scheduling"
    - "multiuser scheduling in a markov modeled downlink using randomly delayed arq feedback"
    - "asymptotically optimal downlink scheduling over markovian fading channels"
    - "joint scheduling and resource allocation in the ofdma downlink utility maximization under imperfect channel state information"
    - "scheduling with rate adaptation under incomplete knowledge of channel estimator statistics"
    - "optimality of myopic sensing in multi channel opportunistic access"

Connected through hyperedge HE-2 (induced by source paper "on the whittle index for restless multi armed hidden markov bandits"):
  with members:
    - "whittle index policy for crawling ephemeral content"
    - "congestion control of tcp flows in internet routers by means of index policy"
    - "on optimality of myopic sensing policy with imperfect sensing in multi channel opportunistic access"
    - "asymptotically optimal downlink scheduling over markovian fading channels"
    - "on myopic sensing for multi channel opportunistic access structure optimality and performance"
    - "joint design and separation principle for opportunistic spectrum access in the presence of sensing errors"

Connected through hyperedge HE-3 (induced by source paper "optimal recommendation to users that react online learning for a class of pomdps"):
  with members:
    - "on the whittle index for restless multi armed hidden markov bandits"
    - "whittle index policy for crawling ephemeral content"
    - "leveraging side observations in stochastic bandits"
    - "analysis of thompson sampling for the multi armed bandit problem"
    - "a contextual bandit approach to personalized news article recommendation"

Connected through hyperedge HE-4 (induced by source paper "power aware wireless file downloading a lyapunov indexing approach to a constrained restless bandit problem"):
  with members:
    - "power aware wireless file downloading a constrained restless bandit approach"
    - "throughput optimal opportunistic scheduling in the presence of flow level dynamics"
    - "optimality of myopic sensing in multi channel opportunistic access"

Connected through hyperedge HE-5 (induced by source paper "scheduling in time correlated wireless networks with imperfect csi and stringent constraint"):
  with members:
    - "exploiting hybrid channel information for downlink multi user mimo scheduling"
    - "multiuser scheduling in a markov modeled downlink using randomly delayed arq feedback"
    - "asymptotically optimal downlink scheduling over markovian fading channels"
    - "joint scheduling and resource allocation in the ofdma downlink utility maximization under imperfect channel state information"
    - "scheduling with rate adaptation under incomplete knowledge of channel estimator statistics"

Connected through hyperedge HE-6 (induced by source paper "power aware wireless file downloading a constrained restless bandit approach"):
  with members:
    - "throughput optimal opportunistic scheduling in the presence of flow level dynamics"
    - "optimality of myopic sensing in multi channel opportunistic access"

Connected through hyperedge HE-7 (induced by source paper "long term profit maximizing incentive for crowd sensing in mobile social networks"):
  with members:
    - "asymptotically optimal downlink scheduling over markovian fading channels"
    - "reputation based incentive protocols in crowdsourcing applications"
    - "perseus randomized point based value iteration for pomdps"
    - "a game theoretic framework for incentives in p2p systems"

Connected through hyperedge HE-8 (induced by source paper "joint opportunistic scheduling and selective channel feedback"):
  with members:
    - "smart scheduling and feedback allocation over non stationary wireless channels"
    - "performance and convergence of multi user online learning"
    - "scheduling with rate adaptation under incomplete knowledge of channel estimator statistics"
    - "rethinking information theory for mobile ad hoc networks"

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.NI(Networking and Internet Architecture)