human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "joint opportunistic scheduling and selective channel feedback"):
  Abstract: It is well known that Max-Weight type scheduling algorithms are throughput optimal since they achieve the maximum throughput while maintaining the network stability. However, the majority of existing works employing Max-Weight algorithm require the complete channel state information (CSI) at the scheduler without taking into account the associated overhead. In this work, we design a Scheduling and Selective Feedback algorithm (SSF) taking into account the overhead due to acquisition of CSI. SSF algorithm collects CSI from only those users with sufficiently good channel quality so that it always schedules the user with the highest queue backlog and channel rate product at every slot. We characterize the achievable rate region of SSF algorithm by showing that SSF supports 1 + ϵ fraction of the rate region when CSI from all users are collected. We also show that the value of ϵ depends on the expected number of users which do not send back their CSI to the base station. For homogenous and heterogeneous channel conditions, we determine the minimum number of users that must be present in the network so that the rate region is expanded, i.e., ϵ > 0. We also demonstrate numerically in a realistic simulation setting that this rate region can be achieved by collecting CSI from only less than 50% of all users in a CDMA based cellular network utilizing high data rate (HDR) protocol.

Includes members:
  Member "smart scheduling and feedback allocation over non stationary wireless channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "federated learning under channel uncertainty joint client scheduling and resource allocation")
  Member "performance and convergence of multi user online learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "periodic bandits and wireless network selection")
  Member "scheduling with rate adaptation under incomplete knowledge of channel estimator statistics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low complexity optimal scheduling over time correlated fading channels with arq feedback")
  Member "exploiting channel memory for joint estimation and scheduling in downlink networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "low complexity optimal scheduling over time correlated fading channels with arq feedback")
  Member "rethinking information theory for mobile ad hoc networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "end to end simulation of integrated access and backhaul at mmwaves")

Question: Please tell me which class the source paper 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)