Hybrid Semantic/Bit Communication Based Networking Problem Optimization

TL;DR

This paper comprehensively develops a knowledge matching-aware two-stage tandem packet queuing model and theoretically derive the average packet loss ratio and queuing latency, and proposes an optimal resource management strategy by employing a Lagrange primal-dual method and devising a preference list-based heuristic algorithm.

Abstract

This paper jointly investigates user association (UA), mode selection (MS), and bandwidth allocation (BA) problems in a novel and practical next-generation cellular network where two modes of semantic communication (SemCom) and conventional bit communication (BitCom) coexist, namely hybrid semantic/bit communication network (HSB-Net). Concretely, we first identify a unified performance metric of message throughput for both SemCom and BitCom links. Next, we comprehensively develop a knowledge matching-aware two-stage tandem packet queuing model and theoretically derive the average packet loss ratio and queuing latency. Combined with several practical constraints, we then formulate a joint optimization problem for UA, MS, and BA to maximize the overall message throughput of HSB-Net. Afterward, we propose an optimal resource management strategy by employing a Lagrange primal-dual method and devising a preference list-based heuristic algorithm. Finally, numerical results validate the performance superiority of our proposed strategy compared with different benchmarks.

Figures (5)

• Figure 1: The two-stage tandem queue model at each SemCom-enabled MU.
• Figure 2: Overall message throughput (kmsg/s) versus different numbers of BSs.
• Figure 3: Overall message throughput versus different numbers of MUs.
• Figure 4: Overall message throughput versus varying $\bar{\tau}$ over all $200$ MUs.
• Figure 5: The CDF of the message rate $M_{ij}$ obtained by the associated link.