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: "compressive coded random access for massive mtc traffic in 5g systems"
  Abstract: Massive MTC support is an important future market segment, but not yet efficiently supported in cellular systems. In this paper we follow-up on recent concepts combining advanced MAC protocols with Compressed Sensing (CS) based multiuser detection. Specifically, we introduce a concept for sparse joint activity, channel and data detection in the context of the Coded ALOHA (FDMA) protocol. We will argue that a simple sparse activity and data detection is not sufficient (as many papers do) because control resources are in the order of the data. In addition, we will improve on the performance of such protocols in terms of the reduction of resources required for the user activity, channel estimation and data detection. We will mathematically analyze the system accordingly and provide expressions for the capture probabilities of the underlying sparse multiuser detector. Finally, we will provide structured CS algorithms for the joint estimation scheme and evaluate its performance.

Connected through hyperedge HE-1 (induced by source paper "compressive random access with multiple resource blocks and fast retrial"):
  with members:
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "aloha random access that operates as a rateless code"
    - "rank awareness in joint sparse recovery"

Connected through hyperedge HE-2 (induced by source paper "towards massive connectivity support for scalable mmtc communications in 5g networks"):
  with members:
    - "a random access protocol for pilot allocation in crowded massive mimo systems"
    - "reliable and efficient access for alarm initiated and regular m2m traffic in ieee 802 11ah systems"
    - "massive machine type communication mmtc access with integrated authentication"
    - "reliable recovery of hierarchically sparse signals and application in machine type communications"
    - "pulse shaped ofdm for 5g systems"
    - "coded pilot access a random access solution for massive mimo systems"
    - "random access for massive mimo systems with intra cell pilot contamination"
    - "compressive random access using a common overloaded control channel"

Connected through hyperedge HE-3 (induced by source paper "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"):
  with members:
    - "sparse activity detection for massive connectivity"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "a random access protocol for pilot allocation in crowded massive mimo systems"
    - "device activity and embedded information bit detection using amp in massive mimo"
    - "random access in c ran for user activity detection with limited capacity fronthaul"
    - "capacity of gaussian many access channels"
    - "rrh based massive mimo with on the fly pilot contamination control"

Connected through hyperedge HE-4 (induced by source paper "secure massive iot using hierarchical fast blind deconvolution"):
  with members:
    - "regularized gradient descent a nonconvex recipe for fast joint blind deconvolution and demixing"
    - "blind demixing and deconvolution at near optimal rate"
    - "rapid robust and reliable blind deconvolution via nonconvex optimization"
    - "reliable recovery of hierarchically sparse signals and application in machine type communications"
    - "blind deconvolution meets blind demixing algorithms and performance bounds"
    - "compressive random access using a common overloaded control channel"
    - "sparse signal processing concepts for efficient 5g system design"
    - "simultaneously structured models with application to sparse and low rank matrices"

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)