Abstract
Future communication networks will be intelligence-embedded on reconfigurable architectures, thus effectively realizing automation of network self-optimization. Central to this architectural approach is handling a comprehensive set of key performance indicators associated with service-specific requirements, such as resource efficiency and operation cost. For heterogeneous networks, node cooperation, which brings computation-intensive intelligence toward cell edges, is important. This article presents a node-cooperative universal framework with a unified class of linear assignment optimizations facilitating massive connectivity and cost-saving user association. Dual self-optimizing targets are classified into two-phase tasks of inter-cell and intra-cell levels. Network nodes share common internal computing structures that can be incorporated in both tasks, and simple message-exchange mechanisms integrate them to achieve orchestration dedicated to specific target configurations. Numerical evaluations analyze impacts of cooperation-based computations, demonstrating cost reduction and efficiency over realistic environments. Within this operational context, we discuss potentials and challenges of network management along with clues to their plausible solutions.
Original language | British English |
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Pages (from-to) | 50-57 |
Number of pages | 8 |
Journal | IEEE Communications Magazine |
Volume | 62 |
Issue number | 6 |
DOIs | |
State | Published - 1 Jun 2024 |