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: "wireless backhaul node placement for small cell networks"
  Abstract: Small cells have been proposed as a vehicle for wireless networks to keep up with surging demand. Small cells come with a significant challenge of providing backhaul to transport data to(from) a gateway node in the core network. Fiber based backhaul offers the high rates needed to meet this requirement, but is costly and time-consuming to deploy, when not readily available. Wireless backhaul is an attractive option for small cells as it provides a less expensive and easy-to-deploy alternative to fiber. However, there are multitude of bands and features (e.g. LOS/NLOS, spatial multiplexing etc.) associated with wireless backhaul that need to be used intelligently for small cells. Candidate bands include: sub-6 GHz band that is useful in non-line-of-sight (NLOS) scenarios, microwave band (6-42 GHz) that is useful in point-to-point line-of-sight (LOS) scenarios, and millimeter wave bands (e.g. 60, 70 and 80 GHz) that are recently being commercially used in LOS scenarios. In many deployment topologies, it is advantageous to use aggregator nodes, located at the roof tops of tall buildings near small cells. These nodes can provide high data rate to multiple small cells in NLOS paths, sustain the same data rate to gateway nodes using LOS paths and take advantage of all available bands. This work performs the joint cost optimal aggregator node placement, power allocation, channel scheduling and routing to optimize the wireless backhaul network. We formulate mixed integer nonlinear programs (MINLP) to capture the different interference and multiplexing patterns at sub-6 GHz and microwave band. We solve the MINLP through linear relaxation and branch-and-bound algorithm and apply our algorithm in an example wireless backhaul network of downtown Manhattan.

Connected through hyperedge HE-1 (induced by source paper "qos aware full duplex concurrent scheduling for millimeter wave wireless backhaul networks"):
  with members:
    - "full duplex amplify and forward relaying power and location optimization"
    - "full duplex millimeter wave communication"
    - "hierarchical codebook design for beamforming training in millimeter wave communication"
    - "exploiting device to device communications in joint scheduling of access and backhaul for mmwave small cells"
    - "a survey of millimeter wave mmwave communications for 5g opportunities and challenges"
    - "in band full duplex wireless challenges and opportunities"
    - "coding the beams improving beamforming training in mmwave communication system"

Connected through hyperedge HE-2 (induced by source paper "investigation of performance in integrated access and backhaul networks"):
  with members:
    - "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks"

Connected through hyperedge HE-3 (induced by source paper "exploiting device to device communications to enhance spatial reuse for popular content downloading in directional mmwave small cells"):
  with members:
    - "exploiting multi hop relaying to overcome blockage in directional mmwave small cells"
    - "exploiting device to device communications in joint scheduling of access and backhaul for mmwave small cells"
    - "iterative joint beamforming training with constant amplitude phased arrays in millimeter wave communications"
    - "modeling analysis and optimization of multicast device to device transmissions"
    - "coding the beams improving beamforming training in mmwave communication system"
    - "femtocell networks a survey"

Connected through hyperedge HE-4 (induced by source paper "deployment of 5g networking infrastructure with machine type communication considerations"):
  with members:
    - "tractable model for rate in self backhauled millimeter wave cellular networks"
    - "what will 5g be"

Connected through hyperedge HE-5 (induced by source paper "energy efficient scheduling for mmwave backhauling of small cells in heterogeneous cellular networks"):
  with members:
    - "iterative eigenvalue decomposition and multipath grouping tx rx joint beamformings for millimeter wave communications"
    - "5g wireless backhaul networks challenges and research advances"
    - "coding the beams improving beamforming training in mmwave communication system"

Connected through hyperedge HE-6 (induced by source paper "exploiting device to device communications in joint scheduling of access and backhaul for mmwave small cells"):
  with members:
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "coding the beams improving beamforming training in mmwave communication system"
    - "femtocell networks a survey"

Connected through hyperedge HE-7 (induced by source paper "joint deployment of small cells and wireless backhaul links in next generation networks"):
  with members:
    - "tractable model for rate in self backhauled millimeter wave cellular networks"
    - "what will 5g be"

Connected through hyperedge HE-8 (induced by source paper "system power minimization to access non contiguous spectrum in cognitive radio networks"):
  with members:
    - "optimal resource allocation and relay selection in bandwidth exchange based cooperative forwarding"
    - "towards a communication theoretic understanding of system level power consumption"

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)