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 "sphere decoding complexity exponent for decoding full rate codes over the quasi static mimo channel"):
  Abstract: In the setting of quasi-static multiple-input multiple-output (MIMO) channels, we consider the high signal-to-noise ratio (SNR) asymptotic complexity required by the sphere decoding (SD) algorithm for decoding a large class of full rate linear space-time codes. With SD complexity having random fluctuations induced by the random channel, noise and codeword realizations, the introduced SD complexity exponent manages to concisely describe the computational reserves required by the SD algorithm to achieve arbitrarily close to optimal decoding performance. Bounds and exact expressions for the SD complexity exponent are obtained for the decoding of large families of codes with arbitrary performance characteristics. For the particular example of decoding the recently introduced threaded cyclic division algebra (CDA) based codes -- the only currently known explicit designs that are uniformly optimal with respect to the diversity multiplexing tradeoff (DMT) -- the SD complexity exponent is shown to take a particularly concise form as a non-monotonic function of the multiplexing gain. To date, the SD complexity exponent also describes the minimum known complexity of any decoder that can provably achieve a gap to maximum likelihood (ML) performance which vanishes in the high SNR limit.

Includes members:
  Member "efficient soft input soft output tree detection via an improved path metric":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fifty years of mimo detection the road to large scale mimos")
  Member "lattice sequential decoder for coded mimo channel performance and complexity analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "time out lattice sequential decoding for the mimo arq channel")
  Member "decoding by sampling a randomized lattice algorithm for bounded distance decoding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on low complexity lattice reduction algorithms for large scale mimo detection the blessing of sequential reduction")
  Member "faster recursions in sphere decoding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning to detect")
  Member "lattice sequential decoding for last coded mimo channels achievable rate dmt and complexity analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the average complexity of sphere decoding in lattice space time coded mimo channel")
  Member "mimo detection for high order qam based on a gaussian tree approximation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi user detection based on expectation propagation for the non coherent simo multiple access channel")
  Member "dmt optimality of lr aided linear decoders for a general class of channels lattice designs and system models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deterministic sampling decoding where sphere decoding meets lattice gaussian distribution")
  Member "soft input soft output single tree search sphere decoding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "signal processing for high throughput satellites challenges in new interference limited scenarios")

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)