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: "distributed resource allocation for relay aided device to device communication under channel uncertainties a stable matching approach"
  Abstract: Wireless device-to-device (D2D) communication underlaying cellular network is a promising concept to improve user experience and resource utilization. Unlike traditional D2D communication where two mobile devices in the proximity establish a direct local link bypassing the base station, in this work we focus on relay-aided D2D communication. Relay-aided transmission could enhance the performance of D2D communication when D2D user equipments (UEs) are far apart from each other and/or the quality of D2D link is not good enough for direct communication. Considering the uncertainties in wireless links, we model and analyze the performance of a relay-aided D2D communication network, where the relay nodes serve both the cellular and D2D users. In particular, we formulate the radio resource allocation problem in a two-hop network to guarantee the data rate of the UEs while protecting other receiving nodes from interference. Utilizing time sharing strategy, we provide a centralized solution under bounded channel uncertainty. With a view to reducing the computational burden at relay nodes, we propose a distributed solution approach using stable matching to allocate radio resources in an efficient and computationally inexpensive way. Numerical results show that the performance of the proposed method is close to the centralized optimal solution and there is a distance margin beyond which relaying of D2D traffic improves network performance.

Connected through hyperedge HE-1 (induced by source paper "a dynamic and incentive policy for selecting d2d mobile relays"):
  with members:
    - "when distributed outperforms centralized scheduling in d2d enabled cellular networks"
    - "performance analysis of network assisted two hop d2d communications"

Connected through hyperedge HE-2 (induced by source paper "relay assisted device to device communication approaches and issues"):
  with members:
    - "distributed resource allocation for relay aided device to device communication a message passing approach"
    - "resource allocation under channel uncertainties for relay aided device to device communication underlaying lte a cellular networks"
    - "base station assisted device to device communications for high throughput wireless video networks"
    - "resource allocation for network integrated device to device communications using smart relays"
    - "to relay or not to relay learning device to device relaying strategies in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "robust fuzzy learning for partially overlapping channels allocation in uav communication networks"):
  with members:
    - "survey of important issues in uav communication networks"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "what will 5g be"
    - "quality of service provisioning in decentralized networks a satisfaction equilibrium approach"

Connected through hyperedge HE-4 (induced by source paper "intelligent wireless communications enabled by cognitive radio and machine learning"):
  with members:
    - "toward intelligent vehicular networks a machine learning framework"
    - "deep learning based channel estimation for beamspace mmwave massive mimo systems"
    - "channel agnostic end to end learning based communication systems with conditional gan"
    - "deep learning based csi feedback approach for time varying massive mimo channels"
    - "an introduction to deep learning for the physical layer"
    - "deep reinforcement learning for resource allocation in v2v communications"
    - "energy efficient user association and power allocation in millimeter wave based ultra dense networks with energy harvesting base stations"
    - "deep learning for wireless physical layer opportunities and challenges"

Connected through hyperedge HE-5 (induced by source paper "sub channel and power allocation for non orthogonal multiple access relay networks with amplify and forward protocol"):
  with members:
    - "pilot power allocation through user grouping in multi cell massive mimo systems"
    - "relay selection for cooperative noma"
    - "cell free massive mimo versus small cells"
    - "cooperative non orthogonal multiple access with simultaneous wireless information and power transfer"
    - "on the complexity of joint subcarrier and power allocation for multi user ofdma systems"

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)