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 "enhancing massive mimo a new approach for uplink training based on heterogeneous coherence time"):
  Abstract: Massive multiple-input multiple-output (MIMO) is one of the key technologies in future generation networks. Owing to their considerable spectral and energy efficiency gains, massive MIMO systems provide the needed performance to cope with the ever increasing wireless capacity demand. Nevertheless, the number of scheduled users stays limited in massive MIMO both in time division duplexing (TDD) and frequency division duplexing (FDD) systems. This is due to the limited coherence time, in TDD systems, and to limited feedback capacity, in FDD mode. In current systems, the time slot duration in TDD mode is the same for all users. This is a suboptimal approach since users are subject to heterogeneous Doppler spreads and, consequently, different coherence times. In this paper, we investigate a massive MIMO system operating in TDD mode in which, the frequency of uplink training differs among users based on their actual channel coherence times. We argue that optimizing uplink training by exploiting this diversity can lead to considerable spectral efficiency gain. We then provide a user scheduling algorithm that exploits a coherence interval based grouping in order to maximize the achievable weighted sum rate.

Includes members:
  Member "sum rate and power scaling of massive mimo systems with channel aging":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "addressing the curse of mobility in massive mimo with prony based angular delay domain channel predictions")
  Member "effects of channel aging in massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nuts and bolts of a realistic stochastic geometric analysis of mmwave hetnets hardware impairments and channel aging")

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)