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Multi-Static ISAC based on Network-Assisted Full-Duplex Cell-Free Networks: Performance Analysis and Duplex Mode Optimization

Fan Zeng, Ruoyun Liu, Xiaoyu Sun, Jingxuan Yu, Jiamin Li, Pengchen Zhu, Dongming Wang, Xiaohu You

TL;DR

This paper proposes a design for multi-static ISAC based on network-assisted full-duplex (NAFD) cell-free networks that can well solve the above problems and achieves performance comparable to that of the Pareto optimal solutions with low complexity.

Abstract

Multi-static integrated sensing and communication (ISAC) technology, which can achieve a wider coverage range and avoid self-interference, is an important trend for the future development of ISAC. Existing multi-static ISAC designs are unable to support the asymmetric uplink (UL)/downlink (DL) communication requirements in the scenario while simultaneously achieving optimal sensing performance. This paper proposes a design for multi-static ISAC based on network-assisted full-duplex (NAFD) cell-free networks can well solve the above problems. Under this design, closed-form expressions for the individual comunication rate and localization error rate are derived under imperfect channel state information, which are respectively utilized to assess the communication and sensing performances. Then, we propose a deep Q-network-based accesss point (AP) duplex mode optimization algorithm to obtain the trade-off between communication and sensing from the UL and DL perspectives of the APs. Simulation results demonstrate that the NAFD-based ISAC system proposed in this paper can achieve significantly better communication performance than other ISAC systems while ensuring minimal impact on sensing performance. Then, we validate the accuracy of the derived closed-form expressions. Furthermore, the proposed optimization algorithm achieves performance comparable to that of the exhaustion method with low complexity.

Multi-Static ISAC based on Network-Assisted Full-Duplex Cell-Free Networks: Performance Analysis and Duplex Mode Optimization

TL;DR

This paper proposes a design for multi-static ISAC based on network-assisted full-duplex (NAFD) cell-free networks that can well solve the above problems and achieves performance comparable to that of the Pareto optimal solutions with low complexity.

Abstract

Multi-static integrated sensing and communication (ISAC) technology, which can achieve a wider coverage range and avoid self-interference, is an important trend for the future development of ISAC. Existing multi-static ISAC designs are unable to support the asymmetric uplink (UL)/downlink (DL) communication requirements in the scenario while simultaneously achieving optimal sensing performance. This paper proposes a design for multi-static ISAC based on network-assisted full-duplex (NAFD) cell-free networks can well solve the above problems. Under this design, closed-form expressions for the individual comunication rate and localization error rate are derived under imperfect channel state information, which are respectively utilized to assess the communication and sensing performances. Then, we propose a deep Q-network-based accesss point (AP) duplex mode optimization algorithm to obtain the trade-off between communication and sensing from the UL and DL perspectives of the APs. Simulation results demonstrate that the NAFD-based ISAC system proposed in this paper can achieve significantly better communication performance than other ISAC systems while ensuring minimal impact on sensing performance. Then, we validate the accuracy of the derived closed-form expressions. Furthermore, the proposed optimization algorithm achieves performance comparable to that of the exhaustion method with low complexity.
Paper Structure (29 sections, 6 theorems, 58 equations, 9 figures, 1 algorithm)

This paper contains 29 sections, 6 theorems, 58 equations, 9 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. system model
  3. Channel modeling
  4. Channel estimation
  5. Autocorrelation Matrix/Coefficient
  6. Uplink Pilot Training
  7. Downlink Pilot Training
  8. Communication Signal Model
  9. Downlink Signal Model
  10. Uplink Signal Model
  11. Sensing Signal Model
  12. Closed-form Expression Derivation
  13. Downlink Communication Rate
  14. Uplink Communication Rate
  15. Sensing Localization Estimation Rate
  16. ...and 14 more sections

Key Result

Theorem 1

The autocorrelation matrix/coefficient of all channels present in the NAFD-based system can be expressed as where $\bm{\zeta}_{a,b}=\bigl({{{\bar{\rm d}_{a,b}^{ -2{\alpha}}}} + \sigma _{a,b}^2}\bigr)\bigl( {{\bar{\mathbf q}}_{a,b}\bar{\mathbf q}_{a,b}^{\rm H} + \chi _{a,b}^2 {\mathbf {I}_N}} \bigr)$, $\gamma_{a,b}={{{\bar{\rm d}_{a,b}^{ -2{\alpha}}}} + \sigma _{a,b}^2}$, $a$ and $b$ represent the

Figures (9)

  • Figure 1: The schematic of the NAFD-based ISAC system
  • Figure 2: Changes of system communication and sensing performance in different scenarios ($M=10$, $K=10$). (a) Changes in system communication performance. (b) Changes in system sensing performance.
  • Figure 3: Diagram of the DQN algorithm
  • Figure 4: Comparison of sensing performance between single-station independent sensing and multi-static cooperative sensing . (a) Sensing performance of single-station independent sensing. (b) Sensing performance of multi-static cooperative sensing.
  • Figure 5: Comparison of system performance with the number of antennas. (a) Comparison of system communication and rate variation with antenna number. (b) Comparison of system LER with antenna number.
  • ...and 4 more figures

Theorems & Definitions (10)

  • Theorem 1
  • Proof 1
  • Theorem 2
  • Proof 2
  • Theorem 3
  • Proof 3
  • Theorem 4
  • Proof 4
  • Lemma 1
  • Lemma 2