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 "massive mimo for internet of things iot connectivity"):
  Abstract: Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design.

Includes members:
  Member "massive mimo unsourced random access":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "phase transition analysis for covariance based massive random access with massive mimo")
  Member "ultrareliable and low latency communication techniques for tactile internet services":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust urllc packet scheduling of ofdm systems")
  Member "non stationarities in extra large scale massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep learning based fdd non stationary massive mimo downlink channel reconstruction")
  Member "ubiquitous cell free massive mimo communications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis of uav communications in cell free massive mimo systems")
  Member "sparcs for unsourced random access":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "massive unsourced random access based on uncoupled compressive sensing another blessing of massive mimo")
  Member "management of network slicing in 5g radio access networks functional framework and information models":
    also connected through other hyperedges:
      (none)
  Member "grant free massive mtc enabled massive mimo a compressive sensing approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "faster activity and data detection in massive random access a multi armed bandit approach")
  Member "massive mimo for ultra reliable communications with constellations for dual coherent noncoherent detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "wireless access in ultra reliable low latency communication urllc")

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)