Browsing by Author "Lin, Jhe-Yi"

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Distributed Beamforming with Improper Gaussian Signaling for MIMO Interference Broadcast Channels
(2017-01-01)
Lin, Jhe-Yi
;
Chang, Ronald Y.
;
Lee, Chia-Han
;
Tsao, Hen-Wai
;
電機工程學系
For rate optimization in interference limited network, improper Gaussian signaling has shown its capability to outperform the conventional proper Gaussian signaling. In this work, we study a weighted sum rate maximization problem with improper Gaussian signaling for the multiple-input multiple-output interference broadcast channel (MIMO-IBC). To solve this nonconvex and NP-hard problem, we propose an effective two-stage algorithm. In the first stage, a weighted mean square error (MSE) minimization algorithm is adopted to compute the transmit covariance matrices, and in the second stage, an alternating direction method of multipliers (ADMM)-based distributed multi-agent algorithm is proposed to obtain the globally optimal pseudo-covariance matrices in a parallel and scalable fashion. Finally, simulation results are presented to demonstrate the superior performance of our algorithm under different signal-to-noise ratio (SNR) and various network scenarios.
Investigation of non-unique relationship between soil electrical conductivity and water content due to drying-wetting rate using TDR
(2019-03-26)
Chung, Chih-Chung
;
Lin, Chih-Ping
;
Yang, Shi-Hui
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Lin, Jhe-Yi
;
Lin, Chun-Hung
The characterization of the relationship between volumetric soil water content (theta) and bulk electrical conductivity (EC) (or electrical resistivity) is of high interest in fields of engineering, fundamental petrophysical, hydrological model parameterization, and quantitative hydrogeophysical interpretations. Based on the relationship, for instance, the broad-area image using electrical resistivity tomography (ERT) can be transformed into theta tomograms as initial/boundary conditions of the slope stability analysis. However, the relationship is affected by the hysteresis, leading the inconsistency in drying-wetting circles. Therefore, this study focused on the factor of soil drying-wetting rate using the proposed time domain reflectometry (TDR) method and related sensors for such characterization. A modified pressure plate apparatus enhanced by TDR was first employed with a relatively low rate in which EC and theta were measured simultaneously, without evident non-unique relationship. A TDR penetrometer was then designed for acquiring the temporal variations of theta and EC in the field. On the basis of certain assumptions, observations showed an apparent dependency of the slope of the theta-EC rating curve on rates, but no hysteresis pattern. Finally, a laboratory controlled fast wetting drying cell was used to increase the response time, proving that both the hysteresis and slopes of the theta-EC rating curves were obviously affected by the soil drying-wetting rate, as a significant finding to the related topics.
Multi-Agent Distributed Beamforming With Improper Gaussian Signaling for MIMO Interference Broadcast Channels
(2019-01-01)
Lin, Jhe-Yi
;
Chang, Ronald Y.
;
Lee, Chia-Han
;
Tsao, Hen-Wai
;
Su, Hsuan-Jung
For rate optimization in interference limited networks, improper Gaussian signaling has shown its ability to outperform conventional proper Gaussian signaling. In this paper, we study a weighted sum-rate maximization problem with improper Gaussian signaling for the multiple-input multiple-output interference broadcast channel. To solve this nonconvex and NP-hard problem, we propose an effective separate covariance and pseudo-covariance matrices optimization algorithm. In the covariance optimization, a weighted minimum mean square error algorithm is adopted, and in the pseudo-covariance optimization, an alternating optimization (AO) algorithm is proposed, which guarantees convergence to a stationary solution and ensures a sum-rate improvement over proper Gaussian signaling. An alternating direction method of multipliers-based multi-agent distributed algorithm is proposed to solve an AO subproblem with the globally optimal solution in a parallel and scalable fashion. The proposed scheme exhibits favorable convergence, optimality, and complexity properties for future large-scale networks. The simulation results demonstrate the superior sum-rate performance of the proposed algorithm as compared with the existing schemes with proper as well as improper Gaussian signaling under various network configurations.