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 "mimo mutli cell processing optimal precoding and power allocation"):
  Abstract: We investigate the optimal power allocation and optimal precoding for a cluster of two BSs which cooperate to jointly maximize the achievable rate for two users connecting to each BS in a MCP framework. This framework is modeled by a virtual network MIMO channel due to the framework of full cooperation. In particular, due to sharing the CSI and data between the two BSs over the backhaul link. We provide a generalized fixed point equation of the optimal precoder in the asymptotic regimes of the low- and high-snr. We introduce a new iterative approach that leads to a closed-form expression for the optimal precoding matrix in the high-snr regime which is known to be an NP-hard problem. Two MCP distributed algorithms have been introduced, a power allocation algorithm for the UL, and a precoding algorithm for the DL.

Includes members:
  Member "piggybacking codes for network coding the high low snr regime":
    also connected through other hyperedges:
      (none)
  Member "multiple access gaussian channels with arbitrary inputs optimal precoding and power allocation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "network coding connections between information theory and estimation theory")
  Member "multi cell processing with limited cooperation a novel framework to timely designs and reduced feedback with general inputs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multiuser i mmse")
  Member "fundamental limits of cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "on optimal precoding in linear vector gaussian channels with arbitrary input distribution":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "measurement matrix design for phase retrieval based on mutual information")
  Member "mutual information and minimum mean square error in gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")

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)