Browsing by Author "Wang, Hai-wei"

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Design and DSP software implementation of mobile WiMAX baseband transceiver functions
(2007)
Wang, Hai-wei
;
Lin, David W.
;
Hungi, Kun-Chien
;
Lee, Youn-Tai
;
電子工程學系及電子研究所
This paper considers the orthogonal frequency-division multiple access (OFDMA) physical layer of the IEEE 802.16e standard. We discuss the design of some key baseband signal processing functions, including synchronization, channel estimation, and forward-error-correction (FEC) decoding. Further, we describe a fully software implementation of these functions employing Texas Instruments' digital signal processors (DSPs).
Detection of Cooperative OFDM Signals in Time-Varying Channels with Partial Whitening of Intercarrier Interference
(2013-01-01)
Wang, Hai-wei
;
Lin, David W.
;
Sang, Tzu-Hsien
;
電機工程學系
;
Department of Electrical and Computer Engineering
Cooperative communication can yield spatial diversity gains, but its performance can also suffer severely from the multiple carrier frequency offsets (MCFOs) induced by high-speed relative motion, in addition to Doppler spread. In orthogonal frequency-division multiplexing (OFDM) systems, such performance degradation arises as a result of intercarrier interference (ICI). We have shown previously that, in conventional non-cooperative communication, certain ICI components (called residual ICI) display high normalized autocorrelation and a partial whitening of the residual ICI can significantly benefit OFDM signal detection. In this work, we show that similar whitening can also be employed in cooperative communication to address the MCFO issue mentioned above. As an illustration, we simulate a distributed spatial-frequency block coding (SFBC) OFDM system subject to highly disparate MCFOs, where in the receiver we perform partial whitening of the residual ICI followed by maximum-likelihood sequence estimation (MLSE). The results show that the proposed method can comfortably accommodate a maximum MCFO span well exceeding one subcarrier spacing.
OFDM Signal Detection in Doubly Selective Channels with Blockwise Whitening of Residual Intercarrier Interference and Noise
(2012-05-01)
Wang, Hai-wei
;
Lin, David W.
;
Sang, Tzu-Hsien
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
Orthogonal frequency-division multiplexing (OFDM) is a popular broadband wireless transmission technique, but its performance can suffer severely from the intercarrier interference (ICI) induced by fast channel variation arising from high-speed motion. Existing ICI countermeasures usually address a few dominant ICI terms only and treat the residual similar to white noise. We show that the residual ICI has high normalized autocorrelation and that this normalized autocorrelation is insensitive to the multipath channel profile as well as a variety of other system and channel conditions. Consequently, the residual ICI plus noise can be whitened in a nearly channel-independent manner, leading to significantly improved detection performance. Simulation results confirm the theoretical analysis. In particular, they show that the proposed technique can significantly lower the ICI-induced error floor in maximum-likelihood sequence estimation (MLSE) designed to address a few dominant ICI terms.
OFDM Signal Detection in Doubly Selective Channels with Whitening of Residual Intercarrier Interference and Noise
(2010)
Wang, Hai-wei
;
Lin, David W.
;
Sang, Tzu-Hsien
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
Orthogonal frequency-division multiplexing (OFDM) transmission in time-varying channels suffers from intercarrier interference (ICI). Existing ICI countermeasures usually address a few dominant ICI terms only and treat the residual as similar to white noise. We show that the residual ICI has high normalized autocorrelation and that this normalized autocorrelation is insensitive to the maximum Doppler frequency and the multipath channel profile, among other things. The residual ICI can thus be whitened in a largely channel-independent manner, leading to significantly improved detection performance. Simulation results confirm the theoretical analysis. In particular, they show that the proposed technique can lower the ICI-induced error floor by several orders of magnitude in maximum-likelihood sequence estimation (MLSE) designed to address a few dominant ICI terms.