human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "robust and efficient distributed compression for cloud radio access networks"
  Abstract: This work studies distributed compression for the uplink of a cloud radio access network where multiple multi-antenna base stations (BSs) are connected to a central unit, also referred to as cloud decoder, via capacity-constrained backhaul links. Since the signals received at different BSs are correlated, distributed source coding strategies are potentially beneficial, and can be implemented via sequential source coding with side information. For the problem of compression with side information, available compression strategies based on the criteria of maximizing the achievable rate or minimizing the mean square error are reviewed first. It is observed that, in either case, each BS requires information about a specific covariance matrix in order to realize the advantage of distributed source coding. Since this covariance matrix depends on the channel realizations corresponding to other BSs, a robust compression method is proposed for a practical scenario in which the information about the covariance available at each BS is imperfect. The problem is formulated using a deterministic worst-case approach, and an algorithm is proposed that achieves a stationary point for the problem. Then, BS selection is addressed with the aim of reducing the number of active BSs, thus enhancing the energy efficiency of the network. An optimization problem is formulated in which compression and BS selection are performed jointly by introducing a sparsity-inducing term into the objective function. An iterative algorithm is proposed that is shown to converge to a locally optimal point. From numerical results, it is observed that the proposed robust compression scheme compensates for a large fraction of the performance loss induced by the imperfect statistical information. Moreover, the proposed BS selection algorithm is seen to perform close to the more complex exhaustive search solution.

Connected through hyperedge HE-1 (induced by source paper "integer forcing architectures for uplink cloud radio access networks"):
  with members:
    - "achievability performance bounds for integer forcing source coding"
    - "green heterogeneous cloud radio access networks potential techniques performance trade offs and challenges"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "outage behavior of integer forcing with random unitary pre processing"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "optimized backhaul compression for uplink cloud radio access network"

Connected through hyperedge HE-2 (induced by source paper "making cell free massive mimo competitive with mmse processing and centralized implementation"):
  with members:
    - "ubiquitous cell free massive mimo communications"
    - "large scale fading decoding in cellular massive mimo systems with spatially correlated channels"
    - "few bit csi acquisition for centralized cell free massive mimo with spatial correlation"
    - "can massive mimo support uplink intensive applications"
    - "on the performance of backhaul constrained cell free massive mimo with linear receivers"
    - "massive mimo has unlimited capacity"
    - "performance of cell free massive mimo systems with mmse and lsfd receivers"
    - "on the total energy efficiency of cell free massive mimo"

Connected through hyperedge HE-3 (induced by source paper "robust baseband compression against congestion in packet based fronthaul networks using multiple description coding"):
  with members:
    - "hybrid data sharing and compression strategy for downlink cloud radio access network"
    - "reliable and low latency fronthaul for tactile internet applications"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "joint precoding and multivariate backhaul compression for the downlink of cloud radio access networks"
    - "minimum expected distortion in gaussian source coding with fading side information"

Connected through hyperedge HE-4 (induced by source paper "non orthogonal multiplexing of ultra reliable and broadband services in fog radio architectures"):
  with members:
    - "joint power and time allocation for noma mec offloading"
    - "coexistence of urllc and embb services in the c ran uplink an information theoretic study"
    - "mixed delay constraints in wyner s soft handoff network"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "cognitive non orthogonal multiple access with cooperative relaying a new wireless frontier for 5g spectrum sharing"
    - "non orthogonal embb urllc radio access for cloud radio access networks with analog fronthauling"
    - "joint scheduling of urllc and embb traffic in 5g wireless networks"
    - "fronthaul compression and precoding design for c rans over ergodic fading channels"

Connected through hyperedge HE-5 (induced by source paper "joint optimization of fronthaul compression and bandwidth allocation in uplink h cran with large system analysis"):
  with members:
    - "message passing in c ran joint user activity and signal detection"
    - "downlink energy efficiency of power allocation and wireless backhaul bandwidth allocation in heterogeneous small cell networks"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "contract based interference coordination in heterogeneous cloud radio access networks"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "energy efficient design of mimo heterogeneous networks with wireless backhaul"

Connected through hyperedge HE-6 (induced by source paper "throughput maximization in cloud radio access networks using network coding"):
  with members:
    - "rate aware instantly decodable network codes"
    - "coordinated scheduling for the downlink of cloud radio access networks"
    - "what will 5g be"
    - "group sparse beamforming for green cloud ran"
    - "joint precoding and multivariate backhaul compression for the downlink of cloud radio access networks"
    - "completion delay minimization for instantly decodable network codes"

Connected through hyperedge HE-7 (induced by source paper "a supervised learning detector for multihop distributed reception systems"):
  with members:
    - "one bit sphere decoding for uplink massive mimo systems with one bit adcs"
    - "compute and forward strategies for cooperative distributed antenna systems"
    - "wireless network information flow a deterministic approach"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-8 (induced by source paper "multi tenant c ran with spectrum pooling downlink optimization under privacy constraints"):
  with members:
    - "optimization of massive full dimensional mimo for positioning and communication"
    - "inter operator base station coordination in spectrum shared millimeter wave cellular networks"
    - "cross layer design for downlink multihop cloud radio access networks with network coding"
    - "joint base station clustering and beamforming for non orthogonal multicast and unicast transmission with backhaul constraints"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "multivariate fronthaul quantization for downlink c ran"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "robust group sparse beamforming for multicast green cloud ran with imperfect csi"

Question: Please tell me which class the center node 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)