Browsing by Author "Ting, Pangan"

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Bayes-Optimal Joint Channel-and-Data Estimation for Massive MIMO With Low-Precision ADCs
(2016-05-15)
Wen, Chao-Kai
;
Wang, Chang-Jen
;
Jin, Shi
;
Wong, Kai-Kit
;
Ting, Pangan
This paper considers a multiple-input multipleoutput (MIMO) receiver with very low-precision analog-to-digital convertors (ADCs) with the goal of developing massive MIMO antenna systems that require minimal cost and power. Previous studies demonstrated that the training duration should be relatively long to obtain acceptable channel state information. To address this requirement, we adopt a joint channel-and-data (JCD) estimation method based on Bayes-optimal inference. This method yields minimal mean square errors with respect to the channels and payload data. We develop a Bayes-optimal JCD estimator using a recent technique based on approximate message passing. We then present an analytical framework to study the theoretical performance of the estimator in the large-system limit. Simulation results confirm our analytical results, which allow the efficient evaluation of the performance of quantized massive MIMO systems and provide insights into effective system design.
Quasi-Maximum Likelihood Initial Downlink Synchronization for IEEE 802.16m
(2011)
Wang, Po-Sen
;
Lu, Kai-Wei
;
Lin, David W.
;
Ting, Pangan
;
電子工程學系及電子研究所
We consider initial downlink synchronization for the emerging IEEE 802.16m standard. Such synchronization involves estimation of the carrier frequency offset, signal timing, and the index of "Primary Advanced Preamble" (PA-Preamble) over a multipath channel. We first give a brief overview of some relevant signal properties in IEEE 802.16m. These properties are rather different from other recent standards to the point of needing a new synchronization algorithm. We develop a synchronization method based on the maximum likelihood (ML) principle. It turns out that the multipath channel response is also estimated along the way. The resulting method is considered quasi-ML because some approximations are used to simplify computation. Simulation results are presented to illustrate its performance.