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 "on the capacity regions of cloud radio access networks with limited orthogonal fronthaul"):
  Abstract: Uplink and downlink cloud radio access networks are modeled as two-hop K-user L-relay networks, whereby small base-stations act as relays for end-to-end communications and are connected to a central processor via orthogonal fronthaul links of finite capacities. Simplified versions of network compress-forward (or noisy network coding) and distributed decode-forward are presented to establish inner bounds on the capacity region for uplink and downlink communications, that match the respective cutset bounds to within a finite gap independent of the channel gains and signal to noise ratios. These approximate capacity regions are then compared with the capacity regions for networks with no capacity limit on the fronthaul. Although it takes infinite fronthaul link capacities to achieve these "fronthaul-unlimited" capacity regions exactly, these capacity regions can be approached approximately with finite-capacity fronthaul. The total fronthaul link capacities required to approach the fronthaul-unlimited sum-rates (for uplink and downlink) are characterized. Based on these results, the capacity scaling law in the large network size limit is established under certain uplink and downlink network models, both theoretically and via simulations.

Includes members:
  Member "integer forcing architectures for uplink cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "some properties of successive minima and their applications")
  Member "generalized compression strategy for the downlink cloud radio access network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hybrid data sharing and compression strategy for downlink cloud radio access network")
  Member "the capacity of the relay channel solution to cover s problem in the gaussian case":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the arbitrarily varying relay channel")
  Member "on the capacity of cloud radio access networks with oblivious relaying":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems")
  Member "lossy compression for compute and forward in limited backhaul uplink multicell processing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "storage space allocation strategy for digital data with message importance")
  Member "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "integer forcing architectures for uplink cloud radio access networks")
  Member "an uplink downlink duality for cloud radio access network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fog massive mimo a user centric seamless hot spot architecture")
  Member "on achievability for downlink cloud radio access networks with base station cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "hybrid precoder design for cache enabled millimeter wave radio access 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)