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 "investigation of performance in integrated access and backhaul networks"):
  Abstract: Wireless backhaul allows densification of mobile networks without incurring additional fiber deployment cost. This, in turn, leads to high spatial reuse, which is a significant tool to meet increasing wireless demand in 5G networks. Integrated access and backhaul (IAB), where access and backhaul network share the same standard wireless technology (e.g. 5G new radio (NR) standard), allows interoperability among different IAB manufacturers and flexible operation between access and backhaul. This paper investigates joint resource allocation and relay selection in a multi-hop IAB network to maximize geometric mean of UE rates. Our study illustrates several advantages and features of IAB. First, IAB significantly improves UE rates compared to access only networks and can provide an important intermediate solution during incremental fiber deployment. Second, IAB networks with optimal mesh outperforms IAB networks with RSRP based spanning tree both in terms of rate and latency.

Includes members:
  Member "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic tdd interference analysis in macro cell and small cell deployments")
  Member "wireless backhaul node placement for small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "qos aware full duplex concurrent scheduling for millimeter wave wireless backhaul networks")

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.IT(Information Theory)