Beamspace Multidimensional ESPRIT Approaches for Simultaneous Localization and Communications

Abstract

Modern wireless communication systems operating at high carrier frequencies are characterized by a high dimensionality of the underlying parameter space (including channel gains, angles, delays, and possibly Doppler shifts). Estimating these parameters is valuable for communication purposes, but also for localization and sensing, making channel estimation a critical component in any joint communication and localization or sensing application. The high dimensionality make it difficult to use search-based methods such as maximum likelihood. Search-free methods such as ESPRIT provide an attractive alternative, but require a complex decomposition step in both the tensor and matrix version of ESPRIT. To mitigate this, we propose, develop, and analyze a reduced complexity beamspace ESPRIT method. Complexity is reduced both by beampace processing as well as low-complex implementation of the singular value decomposition. A novel perturbation analysis provides important insights for both channel estimation and localization performance. The proposed method is compared to the tensor ESPRIT method, in terms of channel estimation, communication, localization, and sensing performance, further validating the perturbation analysis.

Doppler-Enabled Single-Antenna Localization and Mapping Without Synchronization

“…As a consequence, the matrix A S is of rank 2L+2 (which is not full rank due to the unknown clock offset), indicating the localization and mapping can not be performed without UE mobility. 4 This proposition is clearly congruent with the observations from Section II-C. Moreover, the scenario with v → 0 is equivalent to the setup in [15], [17], where the localization problem was solved by assuming perfect knowledge of the clock bias B [15] or a reconfigurable intelligent surface [17].…”

“…, t B,l , and t U,l are the direction vector at the BS and UE, respectively. The channel parameters contain the geometry information of each path, which is assumed to be obtained by the channel parameter estimation methods (e.g., MD-ESPRIT [4]). The lower bound of the measurement parameter vector γ can be obtained using CRB, which will be detailed in Section III-A.…”

Doppler-Enabled Single-Antenna Localization and Mapping Without Synchronization

“…where α and ξ are unknown vectors to be estimated, d 0 = p 0 − p B is the distance between the BS and UE, d l = d l,1 + d l,2 = p l − p B + p l − p 0 is the actual signal propagation distance of the lth path, c is the speed of light (in [m/s]), B is the clock offset in [m], t B,l , and t U,l are the direction vector at the BS and UE, respectively. The channel parameters contain the geometry information of each path, which is assumed to be obtained by the channel parameter estimation methods (e.g., MD-ESPRIT [4]). The lower bound of the measurement parameter vector γ can be obtained using CRB, which will be detailed in Section III-A.…”

“…Location and map information can assist communication in the the millimeter wave/Terahertz (mmWave/THz) band 5G/6G systems, as well as a variety of location-based applications such as autonomous driving [1], tactile robots [2], etc. Due to the geometrical channel property of high frequency radio signals [3], the localization and mapping tasks can be done by exploiting the channel parameters (e.g., angles and delay) of each path from the estimated channel matrix [4]. With the help of one or more reference points (e.g., base station (BS) or reconfigurable intelligent surface (RIS)), the position and orientation of the user equipment (UE), as well as the position of the incidence point (IP), can be estimated [5].…”

Experimental Validation of Single Base Station 5G mm Wave Positioning: Initial Findings

“…3) Uncertainties and Impact for Positioning: In contrast to the BS, the complex element response and beam response at the UE is fully characterized. Hence, both w UE,g,k and a R (θ i k ) are known, opening up possibilities for super-resolution processing [19]- [21]. While collecting the measurements, the main challenge is to maintain the synchronization between the BS and UE.…”