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 "compute and forward protocol design based on improved sphere decoding"):
  Abstract: We consider the problem of finding the optimal coefficient vector that maximizes the computation rate at a relay in the computer-and-forward scheme. Based on the idea of sphere decoding, we propose a low-complexity method that gives the maximum rate. First, we derive an efficient algorithm to compute the Cholesky factorization by using the structure of the matrix, to transfer the problem to a shortest vector problem (SVP). This algorithm gives the closed-form expression of the Cholesky factor $\R$ with only $\bigO(n^2)$ flops. Based on this $\R$, we propose some conditions that can be checked by $\bigO(n)$ flops, under which the optimal coefficient vector can be obtained immediately without using any search algorithm. Second, by taking into account some resultant useful properties of the optimal coefficient vector, we modify the Schnorr-Euchner search algorithm to solve the SVP. Although the general SVP is suspected to be NP-hard, by studying the properties of $\R$, we show that the average cost of our new algorithm is estimated by $\bigO(n^{2.5})$ for i.i.d. Gaussian channel entries. Numerical simulations show that our proposed branch-and-bound method is much more efficient than the existing one that gives the optimal solution. Besides, compared with the suboptimal methods, our method offers the best performance at a cost lower than that of the LLL method and similar to that of the quadratic programming relaxation method.

Includes members:
  Member "effects of the lll reduction on the success probability of the babai point and on the complexity of sphere decoding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "closed form word error rate analysis for successive interference cancellation decoders")
  Member "compute and forward harnessing interference through structured codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "private information retrieval over gaussian mac")

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)