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Wireless Resource Optimization in Hybrid Semantic/Bit Communication Networks

Le Xia, Yao Sun, Dusit Niyato, Lan Zhang, Muhammad Ali Imran

TL;DR

This paper jointly investigates user association, mode selection, and bandwidth allocation problems in a hybrid semantic/bit communication network (HSB-Net), and proposes an optimal resource management strategy by utilizing a Lagrange primal-dual transformation method and a preference list-based heuristic algorithm with polynomial-time complexity.

Abstract

Recently, semantic communication (SemCom) has shown great potential in significant resource savings and efficient information exchanges, thus naturally introducing a novel and practical cellular network paradigm where two modes of SemCom and conventional bit communication (BitCom) coexist. Nevertheless, the involved wireless resource management becomes rather complicated and challenging, given the unique background knowledge matching and time-consuming semantic coding requirements in SemCom. To this end, this paper jointly investigates user association (UA), mode selection (MS), and bandwidth allocation (BA) problems in a 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 specially develop a knowledge matching-aware two-stage tandem packet queuing model and theoretically derive the average packet loss ratio and queuing latency. Combined with 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 utilizing a Lagrange primal-dual transformation method and a preference list-based heuristic algorithm with polynomial-time complexity. Numerical results not only demonstrate the accuracy of our analytical queuing model, but also validate the performance superiority of our proposed strategy compared with different benchmarks.

Wireless Resource Optimization in Hybrid Semantic/Bit Communication Networks

TL;DR

This paper jointly investigates user association, mode selection, and bandwidth allocation problems in a hybrid semantic/bit communication network (HSB-Net), and proposes an optimal resource management strategy by utilizing a Lagrange primal-dual transformation method and a preference list-based heuristic algorithm with polynomial-time complexity.

Abstract

Recently, semantic communication (SemCom) has shown great potential in significant resource savings and efficient information exchanges, thus naturally introducing a novel and practical cellular network paradigm where two modes of SemCom and conventional bit communication (BitCom) coexist. Nevertheless, the involved wireless resource management becomes rather complicated and challenging, given the unique background knowledge matching and time-consuming semantic coding requirements in SemCom. To this end, this paper jointly investigates user association (UA), mode selection (MS), and bandwidth allocation (BA) problems in a 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 specially develop a knowledge matching-aware two-stage tandem packet queuing model and theoretically derive the average packet loss ratio and queuing latency. Combined with 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 utilizing a Lagrange primal-dual transformation method and a preference list-based heuristic algorithm with polynomial-time complexity. Numerical results not only demonstrate the accuracy of our analytical queuing model, but also validate the performance superiority of our proposed strategy compared with different benchmarks.
Paper Structure (18 sections, 2 theorems, 39 equations, 10 figures, 1 table)

This paper contains 18 sections, 2 theorems, 39 equations, 10 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model
  3. HSB-Net Scenario
  4. Network Performance Metric
  5. Queuing Model
  6. Queuing Analysis and Problem Formulation
  7. Queuing Analysis for SCQ and PTQ
  8. Problem Formulation
  9. Proposed Resource Management for HSB-Nets
  10. Strategy Determination for UA and MS
  11. Optimal Solution for BA with Complexity Analysis
  12. Algorithm Analysis
  13. Numerical Results and Discussions
  14. Queuing Model Validation
  15. Performance of the Proposed Solution
  16. ...and 3 more sections

Key Result

Proposition 1

For each $Q_{ij}(t)$ of PTQ, it must have a solvable and unique steady-state probability vector, denoted as $\bm{\alpha}_{ij}=\left[\alpha_{ij}^{0},\alpha_{ij}^{1},\cdots,\alpha_{ij}^{F}\right]^{T}$, where $\alpha_{ij}^k$ represents the steady-state probability of $Q_{ij}\left(t\right)=k$ when $t$ t

Figures (10)

  • Figure 1: The HSB-Net scenario involving UA, MS, and BA in one time block.
  • Figure 2: The two-stage tandem queue model at each SemCom-enabled MU.
  • Figure 3: The Proposed Resource Allocation in HSB-Net
  • Figure 4: Simulated and analytical results w.r.t. average queuing latency $\delta_{i}^{S_1}$ at SCQ for varying packet arrival rates and average knowledge-matching degrees.
  • Figure 5: Simulated and analytical results w.r.t. average queuing latency $\delta_{ij}^{S_2}$ at PTQ for varying packet buffer sizes and allocated bandwidth resources.
  • ...and 5 more figures

Theorems & Definitions (3)

  • Definition 1
  • Proposition 1
  • Proposition 2