Browsing by Author "Wang, Po-Sen"

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Maximum-Likelihood Blind Synchronization for GFDM Systems
(2016-06)
Wang, Po-Sen
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Lin, David W.
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Generalized frequency-division multiplexing (GFDM) inherits the cyclic-prefixed (CP) block signaling structure from orthogonal frequency-division multiplexing (OFDM). The feasibility of CP-based maximum-likelihood (ML) blind synchronization for GFDM systems, however, has not been assessed in the literature. We find that such synchronization is complicated by the covariance structure of the signal which, due to nonorthogonal pulse shaping, possesses a time-varying signal power and some weak self-induced interference. Neglecting the latter and approximating the former by the average power enable us to obtain an approximate-ML solution based on a recent result on OFDM synchronization in wide-sense stationary uncorrelated scattering (WSSUS) channels. Simulations show that the resulting method for GFDM yields comparable performance, under commonly considered pulse-shaping filters, to its kin for OFDM.
On Maximum-Likelihood Blind Synchronization Over WSSUS Channels for OFDM Systems
(2015-10-01)
Wang, Po-Sen
;
Lin, David W.
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交大名義發表
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電子工程學系及電子研究所
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National Chiao Tung University
Various blind synchronization methods built on the maximum likelihood (ML) principle have been proposed, where the addressed scenarios include additive white Gaussian noise (AWGN), single-path fading, and multipath fading channels. We consider ML blind synchronization over wide-sense stationary uncorrelated scattering (WSSUS) channels. Different from existing studies, we exploit a more complete signal correlation function and find the carrier frequency offset estimate to be the solution of a quartic equation, rather than the phase angle of a complex number. As the truly ML synchronizer (dubbed MLE) is very complicated, we also derive a reduced-complexity alternative (dubbed RCE). It is found that the RCE yields indistinguishable performance from the MLE, at a somewhat lower complexity than an existing rival. We also present an in-depth theoretical analysis and comparison of the performance of various methods. Simulations show that the proposed methods yield rather robust performance in modeling errors of the fading rate and the channel power-delay profile (PDP).
On the Configuration-Dependent Singularity of GFDM Pulse-Shaping Filter Banks
(2016-10)
Lin, David W.
;
Wang, Po-Sen
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電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
It is known that, under some configurations, the generalized frequency-division multiplexing (GFDM) pulse-shaper matrix is singular. Moreover, a GFDM pulse-shaper matrix may have unequal magnitude gains in different vector-space dimensions. This letter presents a Fourier-transform-based decomposition of the GFDM pulse-shaper matrix from which the above GFDM properties, as well as some other ones, can be readily appreciated. An upper bound on the nullity of the pulse-shaper matrix is obtained. We also show that, for some commonly conceivable designs, the nullity of the pulse-shaper matrix, if singular, is one. In the latter case, we also specify the corresponding null space. From this, GFDM signals can be designed, so that they do not fall in the null space.
Quasi-Maximum Likelihood Initial Downlink Synchronization for IEEE 802.16m
(2011)
Wang, Po-Sen
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Lu, Kai-Wei
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Lin, David W.
;
Ting, Pangan
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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.