| Author: | Wang, Qipeng |
| Title: | Exploiting intelligent reflecting surfaces as passive anchors for ubiquitous sensing in 6G cellular networks |
| Advisors: | Liu, Liang (EEE) Lau, C. M. Francis (EEE) |
| Degree: | Ph.D. |
| Year: | 2025 |
| Subject: | Signal processing Wireless communication systems Remote Sensing Wireless localization Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Electrical and Electronic Engineering |
| Pages: | xvii, 144 pages : color illustrations |
| Language: | English |
| Abstract: | Integrated sensing and communication (ISAC) is envisioned to be one of the key use cases in the future sixth-generation (6G) cellular networks, where base stations (BSs) are expected to provide ubiquitous communication services as well as ubiquitous sensing services simultaneously. Because sensing relies on the line-of-sight (LOS) paths between targets and BSs, it requires a dense deployment of the BSs in cellular networks to achieve the goal of ubiquitous sensing. However, it is not a cost-efficient solution to densely deploy BSs in practice. Motivated by the advance in the intelligent reflecting surface (IRS) technology for 6G communication, this thesis examines the feasibility of deploying low-cost IRSs as passive anchors to extend the sensing coverage of the BSs. Specifically, because IRSs are typically deployed at known and fixed locations, the ranges and angle-of-arrivals (AOAs) from the targets to the IRSs are useful to localize these targets. However, since the passive IRSs do not have the capability to process the incident signals, the above range information and AOA information have to be estimated by the BS based on its signals received over the target-IRS-BS paths, which is challenging. In this thesis, we make a comprehensive investigation on the powerful signal processing techniques that can enable the BS to extract the range and AOA information from the targets to the IRSs, and localize the targets based on such information. First, we study the range-based localization strategy in an IRS-assisted ISAC system that consists of the active anchors, i.e., BSs, and the passive anchors, i.e., IRSs. Under this framework, the BSs emit the orthogonal frequency division multiplexing (OFDM) communication signals in the downlink for localizing the passive targets based on their echoes reflected via/not via the IRSs. The main challenges include the infeasibility of directly estimating the distance between a passive IRS and a target, as well as the uncertainty of which IRS serves as the anchor to the target. We show that the distance between a target and its associated IRS can be indirectly estimated based on the length of the BS-target-BS path and the BS-target-IRS-BS path. Moreover, we propose an efficient data association method to match each target to its associated IRS. Then, we investigate the AOA-based localization strategy in an IRS-assisted ISAC system, where the LOS paths between the active anchor, i.e., the BS, and the active targets are blocked. Here, the IRS serves as a passive anchor to maintain LOS paths to both BS and targets. We are interested in estimating the AOAs of the incident signals from the active targets to the IRS, but based on the signals received by the BS. However, the challenge is that the signals received across different antennas of the BS only contain AOA information of its incident signals via the LOS path from the IRS to the BS, which is not helpful for localizing the users. To solve this issue, we design innovative temporal-domain multi-dimensional signals by controlling the user message and IRS reflection patterns. These signals allow us to estimate the AOA from targets to the IRS using the classic multiple signal classification (MUSIC) algorithm. Last, we consider the localization strategy that exploits both range and AOA information in an IRS-assisted ISAC system, with mixed near-field targets and far-field targets. In this setup, a single-antenna user transmits OFDM signals, and a multi-antenna BS receives the echoes. In particular, we focus on a challenging scenario where the LOS paths between the targets and the BS are blocked such that it is impossible to estimate the range information and the AOA information of the targets to the BS as in the conventional bi-static radar system. We propose to leverage the IRS as a passive anchor to tackle the above challenge. However, two challenges arise from the above localization system. First, it is unclear whether a target is in the near-field or far-field region of the IRS, leading to uncertainty about which channel model to use. Choosing the wrong model can result in significant localization errors. Second, estimating range and AOA information between passive IRSs and targets is inherently difficult. To tackle these issues, we develop an innovative virtual channel model and an efficient signal processing method that enables the BS to 1) identify whether targets are in the near-field or far-field regions of the IRS, and 2) estimate the distance and AOA information relative to the IRS for localization. |
| Rights: | All rights reserved |
| Access: | open access |
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