Joint Cell Association and Spectrum Allocation in Semantic Communication Networks
Le Xia, Yao Sun, Muhammad Ali Imran · 2024
Semantic communication (SemCom) has recently been considered a promising remedy to ensure high resource utilization and transmission reliability for next-generation wireless networks. Nevertheless, the unique demand for background knowledge matching makes it challenging to achieve efficient resource management for multiple users in SemCom-enabled networks (SC-Nets). To this end, this chapter explores SemCom from a networking perspective, where two fundamental issues of cell association (CA) and spectrum allocation (SA) are systematically addressed in the SC-Net. First, considering varying knowledge matching conditions between wireless users and base stations, we identify two general SC-Net scenarios, namely perfect knowledge matching-based SC-Net and imperfect knowledge matching-based SC-Net. Afterward, for each SC-Net scenario, we identify its distinctive semantic channel model from the semantic information theory perspective, and then a concept of bit-rate-to-message-rate transformation is developed alongside a new semantic-level metric, namely system throughput in message (STM), to measure the overall network performance. In this way, we formulate a joint STM-maximization problem of CA and SA for each SC-Net scenario, followed by a corresponding optimal solution proposed. Numerical results in both cases validate significant superiority and reliability of our solutions in the STM performance compared to benchmarks.