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 performance with imperfect channel reciprocity and channel estimation error"):
  Abstract: Channel reciprocity in time-division duplexing (TDD) massive multiple-input multiple-output (MIMO) systems can be exploited to reduce the overhead required for the acquisition of channel state information (CSI). However, perfect reciprocity is unrealistic in practical systems due to random radio-frequency (RF) circuit mismatches in uplink and downlink channels. This can result in a significant degradation in the performance of linear precoding schemes, which are sensitive to the accuracy of the CSI. In this paper, we model and analyse the impact of RF mismatches on the performance of linear precoding in a TDD multi-user massive MIMO system, by taking the channel estimation error into considerations. We use the truncated Gaussian distribution to model the RF mismatch, and derive closed-form expressions of the output signal-to-interference-plus-noise ratio for maximum ratio transmission and zero forcing precoders. We further investigate the asymptotic performance of the derived expressions, to provide valuable insights into the practical system designs, including useful guidelines for the selection of the effective precoding schemes. Simulation results are presented to demonstrate the validity and accuracy of the proposed analytical results.

Includes members:
  Member "performance analysis of massive mimo for cell boundary users":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a retrodirective wireless power transfer scheme for ambient backscatter systems")
  Member "a novel antenna selection scheme for spatially correlated massive mimo uplinks with imperfect channel estimation":
    also connected through other hyperedges:
      (none)
  Member "mmwave massive mimo based wireless backhaul for the 5g ultra dense network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ultra low latency ull networks the ieee tsn and ietf detnet standards and related 5g ull research")
  Member "uplink performance of time reversal mrc in massive mimo systems subject to phase noise":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "achieving phase coherency and gain stability in active antenna arrays for sub 6 ghz fdd and tdd fd mimo challenges and solutions")
  Member "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the pilot contamination attack in multi cell multiuser massive mimo networks")
  Member "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")
  Member "scalable synchronization and reciprocity calibration for distributed multiuser mimo":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "amplitude and phase estimation for absolute calibration of massive mimo front ends")

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)