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 "an efficient precoder design for multiuser mimo cognitive radio networks with interference constraints"):
  Abstract: We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output (MIMO) broadcast channel, where the secondary system consisting of a secondary base station (BS) and a group of secondary users is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing (ZF) method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex–concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm.

Includes members:
  Member "collaborative relay beamforming for secrecy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "effective optimization criteria and relay selection algorithms for physical layer security in multiple antenna relay networks")
  Member "beamforming and rate allocation in miso cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "robust resource allocation for full duplex cognitive radio systems")
  Member "cooperative multi cell block diagonalization with per base station power constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cooperative downlink interference transmission and cancellation for cellular connected uav a divide and conquer approach")
  Member "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal precoder designs for sum utility maximization in swipt enabled multi user mimo cognitive radio networks")
  Member "on peak versus average interference power constraints for protecting primary users in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading")
  Member "weighted sum rate optimization for cognitive radio mimo broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cooperative prediction and sensing based spectrum sharing in cognitive radio networks")
  Member "capacity limits of cognitive radio with distributed and dynamic spectral activity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "mcleish distribution performance of digital communications over additive white mcleish noise awmn channels")

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)