Localization and Throughput Trade-Off in a Multi-User Multi-Carrier mm-Wave System

Koirala, Remun; Denis, Benoît; Uguen, Bernard; Dardari, Davide; Wymeersch, Henk

doi:10.1109/access.2019.2953777

Cited by 11 publications

(13 citation statements)

References 28 publications

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“…Communication and localization are conventionally seen as competing for the same precious time-frequency resources, where reference signals used for localization take away resources used for communication. In that sense, one must trade off communication rate with localization accuracy [1], [2]. At the same time, it has been appreciated that location information is useful for communication [3].…”

Section: Introductionmentioning

confidence: 99%

Beamspace Multidimensional ESPRIT Approaches for Simultaneous Localization and Communications

Jiang¹,

Wen²,

Ge³

et al. 2021

Preprint

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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.

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Section: Introductionmentioning

confidence: 99%

Beamspace Multidimensional ESPRIT Approaches for Simultaneous Localization and Communications

Jiang¹,

Wen²,

Ge³

et al. 2021

Preprint

Self Cite

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“…Furthermore, the localization in mmwave communications has been considered in several papers, such as [28][29][30][31][32][33][34]. In detail, in [28], a three-step localization scheme was introduced, which includes the coarse channel estimation using the distributed compressed sensing simultaneous orthogonal matching pursuit (DCS-SOMP) algorithm, and the fine estimation using the space-alternating generalized expectationmaximization (SAGE) algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…In [29], the fisher information matrix (FIM) and the position error bound (PEB) for a uniform rectangular array (URA) were derived. In [34], the FIM and the Cramer-Rao lower bound (CRLB) were derived for the multi-user multi-carrier systems, where a localization throughput trade-off was also derived. In [31], a joint received signal strength and angle of arrival (RSS-AOA) algorithm based on beamspace transformation was introduced to reduce the complexity of angle estimation.…”

Section: Introductionmentioning

confidence: 99%

Millimeter-Wave Based Localization Using a Two-Stage Channel Estimation Relying on Few-Bit ADCs

El‐Hajjar

Yang

2021

IEEE Open J. Commun. Soc.

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Benefiting from the high resolution in beamspace, millimeter wave (mmwave) communication has been regarded as a high-accuracy localization solution, where the location information is embedded in the channel via angle and time delay, for example. In this paper, to locate a user equipment (UE) and scatterers, we present the localization model in mmwave communications as a compressed sensing assisted channel estimation problem, which is solved using a proposed two-stage channel estimation based localization scheme. During the first stage, a sparse Bayesian learning (SBL) algorithm is operated to attain a coarse estimation. Then during the second stage, a multi-stage grid refinement assisted fine estimation is achieved by a distributed compressed sensing simultaneous orthogonal matching pursuit (DCS-SOMP) algorithm. Moreover, in our approach, the few-bit analog to digital converters (ADCs) are utilized by the receiver of UE so as to attain a good trade-off among performance, complexity and energy-efficiency. Finally, the performance of channel estimation and positioning is comprehensively investigated and compared. It can be shown that our proposed two-stage approach is capable of achieving centimeterlevel accuracy with the required number of quantization bits of ADCs less than four.

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“…From this perspective, G. Destino, et al [42]- [44], performed some important works by dividing a fixed communication duration into two separate time slots for localization and effective data transmission, respectively, and inquiring into the trade-off between the positioning quality and EADR. R. Koirala, et al [45], also studied the trade-off from the perspective of the time allocation, and formulated optimization problems to optimize the localization and EADR performances. G. Ghatak, et al [46], derived the CRLB for the estimation of the distance between a mobile user and its serving BS, and investigated the trade-off by allocating the total transmit power for the positioning and effective data transmission.…”

Section: Introductionmentioning

confidence: 99%

Joint beamforming for intelligent reflecting surface aided wireless communication using statistical CSI

Dang

Zhang

2020

China Commun.

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Intelligent reflecting surface (IRS) is a novel burgeoning concept, which possesses advantages in enhancing wireless communication and user localization, while maintaining low hardware cost and energy consumption. Herein, we establish an IRS-aided mmWave-MIMO based joint localization and communication system (IMM-JLCS), and probe into its performance evaluation and optimization design.Specifically, first, we provide the signal, channel and estimation error models, and contrive the working process of the IMM-JLCS in detail. Then, by configuring appropriate IRS phase shifts, we derive the closed-form expressions of the Cramér-Rao Lower Bound (CRLB) of the position/orientation estimation errors and the effective achievable data rate (EADR), with respect to the time allocation ratio of the beam alignment and localization stage (BALS). Subsequently, we investigate the trade-off between the two performance metrics, for which we propose a joint optimization algorithm. Finally, we carry out simulations and comparisons to view the trade-off and validate the effectiveness of the proposed algorithm, in the presence of distinct levels of estimation uncertainty and user mobility. Our results demonstrate that the proposed algorithm can find the joint optimal solution for the position/orientation estimation accuracy and EADR, with its optimization performance being robust to slight localization or channel estimation errors and user mobility.

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Localization and Throughput Trade-Off in a Multi-User Multi-Carrier mm-Wave System

Cited by 11 publications

References 28 publications

Beamspace Multidimensional ESPRIT Approaches for Simultaneous Localization and Communications

Beamspace Multidimensional ESPRIT Approaches for Simultaneous Localization and Communications

Millimeter-Wave Based Localization Using a Two-Stage Channel Estimation Relying on Few-Bit ADCs

Joint beamforming for intelligent reflecting surface aided wireless communication using statistical CSI

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