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 "uplink downlink rate balancing and throughput scaling in fdd massive mimo systems"):
  Abstract: In this work we extend the concept of uplink-downlink rate balancing to frequency division duplex (FDD) massive MIMO systems. In uplink-downlink balancing, we use part of the uplink capacity for CSI feedback in order to increase the downlink capacity. We consider a base station with large number antennas serving many single antenna users. We first show that any unused capacity in the uplink can be traded off for higher throughput in the downlink in a system that uses either dirty paper (DP) coding or zero-forcing (ZF) precoding. We then also study the scaling of the system throughput with the number of antennas in cases of Beamforming (BF) Precoding, ZF Precoding, and DP coding. We show that the downlink throughput is proportional to the logarithm of the number of antennas. While, this logarithmic scaling is lower than the linear scaling of the rate in the uplink, it can still bring significant throughput gains. For example, we demonstrate through analysis and simulation that increasing the number of antennas from 4 to 128 will increase the throughput by more than a factor of 5. We also show that a logarithmic scaling of downlink throughput as a function of the number of receive antennas can be achieved even when the number of transmit antennas only increases logarithmically with the number of receive antennas.

Includes members:
  Member "uplink downlink rate balancing in cooperating cellular networks":
    also connected through other hyperedges:
      (none)
  Member "a lower bound on the data rate of dirty paper coding in general noise and interference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "uplink downlink rate balancing in cooperating cellular networks")
  Member "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")
  Member "noncoherent trellis coded quantization a practical limited feedback technique for massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "high dimensional stochastic gradient quantization for communication efficient edge learning")
  Member "designing multi user mimo for energy efficiency when is massive mimo the answer":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal policies of advanced sleep modes for energy efficient 5g networks")
  Member "massive mimo systems signal processing challenges and research trends":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "massive mimo and waveform design for 5th generation wireless communication systems")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")

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)