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: "performance indicator for mimo mmse receivers in the presence of channel estimation error"
  Abstract: We present the derivation of post-processing SNR for minimum mean-squared error (MMSE) receivers with imperfect channel estimates, and show that it is an accurate indicator of the error rate performance of MIMO systems in the presence of channel estimation error. Simulation results show the tightness of the analysis.

Connected through hyperedge HE-1 (induced by source paper "mimo underlay cognitive radio optimized power allocation effective number of transmit antennas and harvest transmit tradeoff"):
  with members:
    - "rf based energy harvesting in decode and forward relaying systems ergodic and outage capacities"
    - "jointly optimal spatial channel assignment and power allocation for mimo swipt systems"
    - "optimal power allocation and active interference mitigation for spatial multiplexed mimo cognitive systems"
    - "simultaneous spectrum sensing and data reception for cognitive spatial multiplexing distributed systems"
    - "full duplex mimo small cell networks with interference cancellation"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "energy efficiency in massive mimo based 5g networks opportunities and challenges"
    - "full duplex wireless powered relay with self energy recycling"

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.PF(Performance)