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 "what is the true value of dynamic tdd a mac layer perspective"):
  Abstract: Small cell networks (SCNs) are envisioned to embrace dynamic time division duplexing (TDD) in order to tailor downlink (DL)/uplink (UL) subframe resources to quick variations and burstiness of DL/UL traffic. The study of dynamic TDD is particularly important because it provides valuable insights on the full duplex transmission technology, which has been identified as one of the candidate technologies for the 5th-generation (5G) networks. Up to now, the existing works on dynamic TDD have shown that the UL of dynamic TDD suffers from severe performance degradation due to the strong DL-to-UL interference in the physical (PHY) layer. This conclusion raises a fundamental question: Despite such obvious technology disadvantage, what is the true value of dynamic TDD? In this paper, we answer this question from a media access control (MAC) layer viewpoint and present analytical results on the DL/UL time resource utilization (TRU) of synchronous dynamic TDD, which has been widely adopted in the existing 4th-generation (4G) systems. Our analytical results shed new light on the dynamic TDD in future synchronous 5G networks.

Includes members:
  Member "ultra dense networks is there a limit to spatial spectrum reuse":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a brief history on the theoretical analysis of dense small cell wireless networks")
  Member "study on the idle mode capability with los and nlos transmissions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cellular connectivity for uavs network modeling performance analysis and design guidelines")
  Member "throughput and coverage for a mixed full and half duplex small cell network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "backhaul aware uplink communications in full duplex dbs aided hetnets")
  Member "performance impact of idle mode capability on dense small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges")
  Member "performance impact of idle mode capability on dense small cell networks with los and nlos transmissions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "promises and caveats of uplink iot ultra dense networks")
  Member "performance impact of los and nlos transmissions in dense cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mobility in the sky performance and mobility analysis for cellular connected uavs")
  Member "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "game theory for multi access edge computing survey use cases and future trends")
  Member "d2d enhanced heterogeneous cellular networks with dynamic tdd":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")

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)