Compressed Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave Systems

Abstract

This work addresses the problem of intelligent reflecting surface (IRS) assisted target sensing in a non-line-ofsight (NLOS) scenario, where an IRS is employed to facilitate the radar/access point (AP) to sense the targets when the lineof-sight (LOS) path between the AP and the target is blocked by obstacles. To sense the targets, the AP transmits a train of uniformly-spaced orthogonal frequency division multiplexing (OFDM) pulses, and then perceives the targets based on the echoes from the AP-IRS-targets-IRS-AP channel. To resolve an inherent scaling ambiguity associated with IRS-assisted NLOS sensing, we propose a two-phase sensing scheme by exploiting the diversity in the illumination pattern of the IRS across two different phases. Specifically, the received echo signals from the two phases are formulated as third-order tensors. Then a canonical polyadic (CP) decomposition-based method is developed to estimate each target's parameters including the direction of arrival (DOA), Doppler shift and time delay. Our analysis reveals that the proposed method achieves reliable NLOS sensing using a modest quantity of pulse/subcarrier resources. Simulation results are provided to show the effectiveness of the proposed method under the challenging scenario where the degrees-of-freedom provided by the AP-IRS channel are not enough for resolving the scaling ambiguity.

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

“…In [99], the authors develop a joint channel estimation and beamforming design for RIS-assisted MISO systems in the millimeter-wave frequency band. In order to reduce the training overhead, the inherent sparsity of millimeterwave channels is exploited.…”

Prospective Multiple Antenna Technologies for Beyond 5G

“…Besides, there are some initial attempts in the literature for addressing the channel estimation problem in IRS-assisted systems. For example, in [171], compressive sensing-based channel estimation was studied for IRS-assisted mmWave systems. In [172], a practical transmission protocol was proposed to execute channel estimation and reflection optimization successively.…”

mmWave Doubly-Massive-MIMO Communications Enhanced With an Intelligent Reflecting Surface: Asymptotic Analysis

“…Typically, the fully-digital precoding/combining architecture for a mmWave massive MIMO system is more expensive. However, (30) implies that instead of the fully-digital architecture, a cost-efficient analog precoding/combining architecture can be applied in the underlying IRS-assisted mmWave massive MIMO system. In practice, the use of hybrid precoding/combining (beamforming) instead of pure analog precoding/combining (beamforming) can lead to further improvement of the system performance [2], [3].…”

“…To date, there are a few works that investigate IRS-aided mmWave MIMO systems for both single-user and multi-user scenarios, and with one or multiple IRSs. These works were concerned with rate optimization [20]- [22], joint active and passive beamforming design [23], [24], joint power allocation and beamforming design [25], hybrid beamforming design [26]- [29], channel estimation [30], [31], user association [32], and secure transmission [33].…”