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 "aid an energy efficient decoding scheme for ldpc codes in wireless body area sensor networks"):
  Abstract: One of the major challenges in Wireless Body Area Networks (WBANs) is to prolong the lifetime of network. Traditional research work focuses on minimizing transmit power, however, in the case of short range communication the consumption power in decoding is significantly larger than transmit power. This paper investigates the minimization of total power consumption by reducing the decoding power consumption. For achieving a desired Bit Error Rate (BER), we introduce some fundamental results on the basis of iterative message-passing algorithms for Low Density Parity Check Code (LDPC). To reduce energy dissipation in decoder, LDPC based coded communications between sensors are considered. Moreover, we evaluate the performance of LDPC at different code rates and introduce Adaptive Iterative Decoding (AID) by exploiting threshold on the number of iterations for a certain BER. In iterative LDPC decoding, the total energy consumption of network is reduced by 20 to 25 percent.

Includes members:
  Member "energy efficient mac protocols in wireless body area sensor networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "e horm an energy efficient hole removing mechanism in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "divide and rule scheme for energy efficient routing in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "density controlled divide and rule scheme for energy efficient routing in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "performance study of localization techniques in wireless body area sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "adaptive reliable medium access control protocol for wireless body area networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "modeling and evaluating enhancements in expanding ring search algorithm for wireless reactive protocols":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an energy efficient decoding scheme for wireless body area sensor networks")
  Member "energy efficiency and reliability in wireless biomedical implant systems":
    also connected through other hyperedges:
      (none)

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.NI(Networking and Internet Architecture)