VLDB 2026 Research / reviewers in the wild / expert
Xiwen Jiang
dblp:167/9401
· DBLP profile ↗
7ranked-venue papers
4as first author
4since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 3 · 2 first-authorDatabases, data management, data science and information retrieval · 3 · 2 first-author · 3 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Fitter: post-mining user-preferred co-location patterns interactively
Xiwen Jiang, Lizhen Wang 0001, Peizhong Yang, Hongmei Chen 0003 |
Data Min. Knowl. Discov. | 1 |
| 2024 | RCPM_CFI: A regional core pattern mining method based on core feature influence
Lizhen Wang 0001, Xiwen Jiang, Peizhong Yang |
Inf. Sci. | 3 |
| 2023 | Multi-mobile Object Motion Coordination with Reinforcement Learning
Shanhua Yuan, Sheng Han 0001, Xiwen Jiang, Youfang Lin, Kai Lv 0002 |
ICONIP (8) | 3 |
| 2023 | A multi-view anomalous co-location detection framework considering both intra- and inter-feature couplingsabstractCo-location is one of the most fundamental spatial associations in spatial data. Previous anomalous co-location detections only aim to detect abnormal inter-feature co-locations on bivariate datasets, while the abnormal intra-feature co-locations are lost, which may have limits to applications. Thus, we propose a novel multi-view anomalous co-location detection framework (MACDF). Two kinds of relationships are captured by two proposed couplings, that is, intra-feature coupling and inter-feature coupling (intra-coupling and inter-coupling for short). Moreover, the neighboring concept in co-location relationships is redefined with a mixture-considered inter-coupling for point-like instances, inspired by the concept for polygonal instances, and a concreted algorithm, i.e. multi-view low-rank analysis with direction for anomalous co-location detection (MLAD-ACD), is designed to discover the anomalous co-locations, on not only bivariate datasets but also multivariate datasets. Experiments show the instantiated algorithm MLAD-ACD can detect anomalous co-locations effectively and efficiently on spatial datasets. Specifically, MLAD-ACD obtains at least a 71% higher AUC score than the state-of-the-art algorithms in an acceptable time. Xiwen Jiang, Lizhen Wang 0001, Hongmei Chen 0003, Vanha Tran |
MDM | 1 |
| 2018 | A Framework for Over-the-Air Reciprocity Calibration for TDD Massive MIMO SystemsabstractOne of the biggest challenges in operating massive multiple-input multiple-output systems is the acquisition of accurate channel state information at the transmitter. To take up this challenge, time division duplex is more favorable thanks to its channel reciprocity between downlink and uplink. However, while the propagation channel over the air is reciprocal, the radio-frequency front-ends in the transceivers are not. Therefore, calibration is required to compensate the RF hardware asymmetry. Although various over-the-air calibration methods exist to address the above problem, this paper offers a unified representation of these algorithms, providing a higher level view on the calibration problem, and introduces innovations on calibration methods. We present a novel family of calibration methods, based on antenna grouping, which improves accuracy and speeds up the calibration process compared to existing methods. We then provide the Cramér-Rao bound as the performance evaluation benchmark and compare maximum likelihood and least squares estimators. We also differentiate between the coherent and non-coherent accumulation of calibration measurements, and point out that enabling non-coherent accumulation allows the training to be spread in time, minimizing the impact to the data service. Overall, these results have special value in allowing the design of reciprocity calibration techniques that are both accurate and resource-effective. Xiwen Jiang, Alexis Decurninge, Kalyana Gopala, Florian Kaltenberger, Maxime Guillaud, Dirk T. M. Slock, Luc Deneire |
IEEE Trans. Wirel. Commun. | 1 |
| 2015 | MIMO-TDD reciprocity under hardware imbalances: Experimental resultsabstractFor time division duplexing (TDD) systems, the physical channel in the air is reciprocal for uplink (UL) and downlink (DL) within the channel coherence time. However when the transceivers' radio frequency (RF) hardware is taken into consideration, TDD channel reciprocity no longer holds because of the non-symmetric characteristics of RF transmit and receive chains. Relative calibration has been proposed to compensate this hardware impairment with a multiplicative matrix. In this paper we perform hardware measurements on this calibration matrix which gives a direct insight on the physical phenomenon of TDD transceivers. Especially, we inspect the assumption that this calibration matrix is diagonal, which is widely adopted in literature but has never been verified by experiments. This work can be regarded as an experimental base for TDD calibration or for theoretical analysis of non-perfect channel reciprocity of TDD systems. Xiwen Jiang, Mirsad Cirkic, Florian Kaltenberger, Erik G. Larsson, Luc Deneire, Raymond Knopp |
ICC | 1 |
| 2015 | An efficient FTN implementation of the OFDM/OQAM systemabstractIn this paper, we propose an implementation method for Orthogonal Frequency Division Multiplexing Offset Quadrature Amplitude Modulation (OFDM/OQAM) with Faster-Than-Nyquist (FTN) signaling. The proposed scheme can bring several advantages: 1) it approaches the theoretical rate gain of FTN signaling; 2) it can flexibly switch between Nyquist and FTN modes; 3) it does not cause complexity increase for the modem components while switching from Nyquist to FTN mode, and vice versa. In addition, we also present an iterative detector method which can support high constellation order transmission. With the simulations, we intend to show the FTN limits, up to a rate increase by a factor of 2, that the proposed transceiver can reach with various pulse shapes. Naila Lahbabi, Pierre Siohan, Xiwen Jiang |
ICC | 4 |