5G-Based User-Centric Sensing at <i>C</i>-Band

Yang, Xiaodong; Fan, Dou; Ren, Aifeng; Zhao, Nan; Alam, Muhammad Mahtab

doi:10.1109/tii.2019.2891738

Cited by 57 publications

(35 citation statements)

References 22 publications

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“…Adaptive Beamforming is a widely used technique in wireless communication [1], acoustic sensors array [2], medical imaging [3] and other fields to improve signal quality. It can also be used in the latest tactile internet application when multiple sensors are deployed [4]. The fundamental task of adaptive beamforming is to combine the output from an array of spatially separated sensors in a way to minimize a predefined cost function adaptively so that a particular performance criteria could be satisfied.…”

Section: Introductionmentioning

confidence: 99%

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

Dai

Abbasi

2021

IEEE Sensors J.

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A fast algorithm to generate the Blocking Matrix for Generalized Sidelobe Canceller (GSC) beamforming is proposed in this paper. The proposed algorithm uses a Simplified Zero Placement Algorithm (SZPA) to directly generate the column vectors of the Blocking Matrix using the polynomial method. The constrained signal incoming angles are converted to spatial frequency and designated as zero locations in the Z domain. Independent vectors that span the whole left null space of the constraint matrix is then built using a simple shift operation. The algorithm also supports the derivative constraints used for robust beamforming. Compared to the conventional methods based on Singular Value Decomposition (SVD), the SZPA algorithm can generate Blocking Matrix more than 9 times faster for scenarios with 15 constraints and will be even more advantageous for more constraints. The Blocking Matrix generated by the SZPA and SVD methods is then implemented in the same GSC architecture for performance evaluation. The numerical simulation confirms that the same overall optimum state performance and learning speed can be achieved. By reducing the calculation time of blocking matrix from 1.541ms of SVD method to 0.168ms, the proposed SZPA algorithm is fast and insensitive to the number of constraints as the required calculation time incremental for each additional constraint with SZPA is only around 1/16 of SVD method. This makes it suitable for scenarios like train to infrastructure communication in High Speed Rail (HSR) where there are multiple constraints and frequent constraints update is required.

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Section: Introductionmentioning

confidence: 99%

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

Dai

Abbasi

2021

IEEE Sensors J.

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“…Compared to the TDD protocol, FDD protocol can provide better CSI estimation performance in terms of transmission delay, communication range, and mobility support [5]- [10]. The challenge of CSI estimation for FDD protocol is serious pilot overhead [11]. That is because the number of training pilots required for channel estimation increases rapidly with the number of BS antennas.…”

Section: Introductionmentioning

confidence: 99%

Decoupling Channel Estimation for FDD Massive MIMO Systems Utilizing Joint Sparsity

et al. 2020

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Effective channel estimation for massive multiple-input-multiple-output (MIMO) systems based on frequency division duplex (FDD) protocol is a crucial problem. To reduce pilot overhead, we consider the joint sparsity of the multi-path channel in delay-angle domain. Based on the joint sparsity, we propose a decoupling pilot design scheme. In the proposed scheme, the pilot design is decoupled into two parts. In the first part, a global optimal selection greedy iterative algorithm (GOS-GIA) is proposed to obtain the near-optimal pilot subcarrier pattern. In the second part, a random Rademacher distribution pilot matrix is used as the angle-domain pilot matrix. Accordingly, a two-stage channel estimation strategy is also provided and analyzed. The first stage of the strategy is concerned with retrieving the positions of non-zero dominant taps in the delay domain. The second stage focuses on estimating the channel coefficients at these taps. Algorithm complexity analysis shows that the GOS-GIA can reduce the computational complexity at least one order of magnitude, and the proposed channel estimation strategy reduces the computational complexity by more than two orders of magnitude. Simulation results verify that the proposed pilot design scheme achieves better performance with lower pilot overhead. INDEX TERMS Angle domain, channel estimation, compressive sensing, delay domain, massive multiple-input-multiple-output, pilot design, sparsity.

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“…A nonintrusive breathing monitoring system that benefits from the C-band sensing technique is proposed in [17]. e respiratory motions of diabetic patients are monitored by this technique in order to identify diabetic ketoacidosis in indoor areas, which can be accessed from outside through the connectivity of tactile internet.…”

Section: Introductionmentioning

confidence: 99%

A Clustering-Based Approach for Improving the Accuracy of UWB Sensor-Based Indoor Positioning System

Arsan

Hameez

2019

Mobile Information Systems

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There are several methods which can be used to locate an object or people in an indoor location. Ultra-wideband (UWB) is a specifically promising indoor positioning technology because of its high accuracy, resistance to interference, and better penetration. This study aims to improve the accuracy of the UWB sensor-based indoor positioning system. To achieve that, the proposed system is trained by using the K-means algorithm with an additional average silhouette method. This helps us to define the optimal number of clusters to be used by the K-means algorithm based on the value of the silhouette coefficient. Fuzzy c-means and mean shift algorithms are added for comparison purposes. This paper also introduces the impact of the Kalman filter while using the measured UWB test points as an input for the Kalman filter in order to obtain a better estimation of the position. As a result, the average localization error is reduced by 43.26% (from 16.3442 cm to 9.2745 cm) when combining the K-means algorithm with the Kalman filter in which the Kalman-filtered UWB-measured test points are used as an input for the proposed system.

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5G-Based User-Centric Sensing at C-Band

Cited by 57 publications

References 22 publications

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

A Fast Blocking Matrix Generating Algorithm for Generalized Sidelobe Canceller Beamformer in High Speed Rail Like Scenario

Decoupling Channel Estimation for FDD Massive MIMO Systems Utilizing Joint Sparsity

A Clustering-Based Approach for Improving the Accuracy of UWB Sensor-Based Indoor Positioning System

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