Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

In-Band Full-Duplex MIMO Systems for Simultaneous Communications and Sensing: Challenges, Methods, and Future Perspectives

Besma Smida, George C. Alexandropoulos, Taneli Riihonen, Md Atiqul Islam

TL;DR

This article presents an FD-enabled framework for simultaneous communications and sensing using data signals and its goal is not to mitigate self interference, since it includes reflections of the downlink data transmissions from targets in the FD node's vicinity, but to optimize the system parameters for the intended dual functionality.

Abstract

In-band Full-Duplex (FD) Multiple-Input Multiple-Output (MIMO) systems offer a significant opportunity for Integrated Sensing and Communications (ISAC) due to their capability to realize simultaneous signal transmissions and receptions. This feature has been recently exploited to devise spectrum-efficient simultaneous information transmission and monostatic sensing operations, a line of research typically referred to as MIMO FD-ISAC. In this article, capitalizing on a recent FD MIMO architecture with reduced complexity analog cancellation, we present an FD-enabled framework for simultaneous communications and sensing using data signals. In contrast to communications applications, the framework's goal is not to mitigate self interference, since it includes reflections of the downlink data transmissions from targets in the FD node's vicinity, but to optimize the system parameters for the intended dual functionality. The unique characteristics and challenges of a generic MIMO FD-ISAC system are discussed along with a broad overview of state-of-the-art special cases, including numerical investigations. Several directions for future work on FD-enabled ISAC relevant to signal processing communities are also provided.

In-Band Full-Duplex MIMO Systems for Simultaneous Communications and Sensing: Challenges, Methods, and Future Perspectives

TL;DR

This article presents an FD-enabled framework for simultaneous communications and sensing using data signals and its goal is not to mitigate self interference, since it includes reflections of the downlink data transmissions from targets in the FD node's vicinity, but to optimize the system parameters for the intended dual functionality.

Abstract

In-band Full-Duplex (FD) Multiple-Input Multiple-Output (MIMO) systems offer a significant opportunity for Integrated Sensing and Communications (ISAC) due to their capability to realize simultaneous signal transmissions and receptions. This feature has been recently exploited to devise spectrum-efficient simultaneous information transmission and monostatic sensing operations, a line of research typically referred to as MIMO FD-ISAC. In this article, capitalizing on a recent FD MIMO architecture with reduced complexity analog cancellation, we present an FD-enabled framework for simultaneous communications and sensing using data signals. In contrast to communications applications, the framework's goal is not to mitigate self interference, since it includes reflections of the downlink data transmissions from targets in the FD node's vicinity, but to optimize the system parameters for the intended dual functionality. The unique characteristics and challenges of a generic MIMO FD-ISAC system are discussed along with a broad overview of state-of-the-art special cases, including numerical investigations. Several directions for future work on FD-enabled ISAC relevant to signal processing communities are also provided.
Paper Structure (17 sections, 3 equations, 5 figures, 1 table)

This paper contains 17 sections, 3 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. Motivation --- The moment is opportune for in-band full-duplex
  3. Scope --- Millimeter-wave massive MIMO FD-ISAC
  4. In-band Full-Duplex MIMO Fundamentals
  5. Characterization of the Self-Interference Signal
  6. From Self-Interference Cancellation to Self-Interference Management
  7. Propagation Domain --- Beamforming
  8. Analog Domain
  9. Digital Domain
  10. Unified design for Massive MIMO
  11. FD-Enabled Simultaneous Communications and Sensing
  12. Sensing Range Case Study
  13. Beamforming Design
  14. Waveform Design
  15. Numerical Results and discussion
  16. ...and 2 more sections

Figures (5)

  • Figure 1: The architectural components of an IBFD $N_{\rm R}\times N_{\rm T}$ MIMO node $b$ realizing simultaneous DL data transmission and monostatic sensing.
  • Figure 2: Sensing range of a $?\times?$ MIMO FD-ISAC system at $?$GHz with respect to the TX/RX beamforming gain for different SINR levels, $n_{p,k}=2.86$, $\sigma_{\rm{rcs,k}}=20$dBsm, and $\sigma_{s,k}=20$dB.
  • Figure 3: Sensing performance for $6$ automotive radar targets via the proposed $128\times128$ MIMO FD-ISAC system and optimization framework with $8$ TX and RF RF chains, each connected with a $16$-element ULA, and DL transmit power of $30$dBm.
  • Figure 4: Analog TX beamformer $\mathbf{V}_b^{\rm RF}$ and Analog RX combiner $\mathbf{W}_b^{\rm RF}$ for $6$ automotive radar targets via the proposed $128\times128$ MIMO FD-ISAC system and optimization framework with $8$ TX and RF RF chains, each connected with a $16$-element ULA, and DL transmit power of $30$dBm.
  • Figure 5: Achievable DL rate performance versus the transmit power $P$ in dBm for the MIMO FD-ISAC system and optimization framework in Fig. \ref{['fig: sim_1']} considering different numbers $K$ of targets in the environment.