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 "convex separable problems with linear constraints in signal processing and communications"):
  Abstract: In this work, we focus on separable convex optimization problems with box constraints and a set of triangular linear constraints. The solution is given in closed-form as a function of some Lagrange multipliers that can be computed through an iterative procedure in a finite number of steps. Graphical interpretations are given casting valuable insights into the proposed algorithm and allowing to retain some of the intuition spelled out by the water-filling policy. It turns out that it is not only general enough to compute the solution to different instances of the problem at hand but also remarkably simple in the way it operates. We also show how some power allocation problems in signal processing and communications can be solved with the proposed algorithm.

Includes members:
  Member "on the precoder design of a wireless energy harvesting node in linear vector gaussian channels with arbitrary input distribution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on mimo transmission with discrete input signals technical challenges advances and future trends")
  Member "duality and optimization for generalized multi hop mimo amplify and forward relay networks with linear constraints":
    also connected through other hyperedges:
      (none)
  Member "power allocation in two hop amplify and forward mimo relay systems with qos requirements":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficiency optimization in relay assisted mimo systems with perfect and statistical csi")
  Member "a tutorial on the optimization of amplify and forward mimo relay systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficiency fairness for multi pair wireless powered relaying systems")
  Member "transmission with energy harvesting nodes in fading wireless channels optimal policies":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "closed form analysis of non linear age of information in status updates with an energy harvesting transmitter")
  Member "separable convex optimization problems with linear ascending constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "convex separable problems with linear and box constraints")

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)