Framework for a Perceptive Mobile Network Using Joint Communication and Radar Sensing

Abstract

In this paper, we develop a framework for a novel perceptive mobile/cellular network that integrates radar sensing function into the mobile communication network. We propose a unified system platform that enables downlink and uplink sensing, sharing the same transmitted signals with communications. We aim to tackle the fundamental sensing parameter estimation problem in perceptive mobile networks, by addressing two key challenges associated with sophisticated mobile signals and rich multipath in mobile networks. To extract sensing parameters from orthogonal frequency division multiple access (OFDMA) and spatial division multiple access (SDMA) communication signals, we propose two approaches to formulate it to problems that can be solved by compressive sensing techniques. Most sensing algorithms have limits on the number of multipath signals for their inputs. To reduce the multipath signals, as well as removing unwanted clutter signals, we propose a background subtraction method based on simple recursive computation, and provide a closed-form expression for performance characterization. The effectiveness of these methods is validated in simulations.

Simultaneous Model and Parameter Estimation for Joint Communication and Positioning

“…To exploit the benefits of compressive sensing to recover the physical path parameters, the authors of [57] state the problem formulation again in the frequency domain. The authors of [57] assess a joint communication and radar sensing framework based on using compressive sensing to determine the physical path parameters. The authors combine the approach with special signal processing techniques.…”

“…The authors refer to these techniques as signal-stripping and clutter-reduction. With the signal stripping approach, the authors of [57], and [58] yield a problem formulation that circumvents additional communication data based errors. Such techniques aim at targeting a high physical path parameter estimation accuracy.…”

“…Let us assume that the pilot design is optimal. Approaches like successive interference-cancellation as assessed in [59] or signal stripping [57], [58] aim at removing the undesired signal parts from the received signal. They improve the channel estimation performance compared to the trainingbased estimation by removing the systematic error.…”

A Survey on Joint Communication-Radar Systems

“…This system exploits some properties of IEEE 802.11ad preamble to implement the radar functions. In [3], a system-level framework for perceptive mobile networks is presented, which aims to integrate radar sensing functions into the entire network. Systemlevel architecture, along with signal processing algorithms are presented to implement these additional sensing functions on a unified platform.…”

“…Therefore, there are a number of applications that stand to benefit from the integration of radar and communication functions. Hence, spectrum sharing between radar and communication systems has attracted significant interest in recent years [1]- [3].…”