Performance of OSTBC Diversity for QAM over Correlated Fading Channels

[[abstract]]We consider arbitrary rectangular QAM signaling in orthogonal space-time block code (OSTBC) diversity systems over correlated fading channels with Gaussian channel gains. We first decorrelate the physical branches into uncorrelated virtual branches to obtain a general moment generating function (MGF), from which closed-form symbol error probability (SEP) is then obtained for OSTBC with generalized complex orthogonal design (GCOD) and it is discovered that different information symbols may yield different SEP's.[[conferencetype]]國際[[conferencedate]]20061127~20061130[[booktype]]紙本[[conferencelocation]]Guilin, Chin

Performance of OFDM QAM over Frequency-Selective Fading Channels

[[abstract]]We present exact symbol error rate (SER) performance analysis for M-QAM OFDM systems over Ricean and Rayleigh fading is analyzed. Both slow and fast quasi-static fading as well as frequency-selective and -nonselective channels are considered.[[conferencetype]]國際[[conferencedate]]20070702~20070704[[booktype]]紙本[[booktype]]電子版[[conferencelocation]]Singapor

Symbol Error Probability for Rectangular M-QAM OFDM Transmission over Rayleigh Fading Channels

[[abstract]]By using what we call the pre-averaging method, an exact closed form expression for the symbol error probability (SEP) is derived for arbitrary rectangular M-QAM signaling in OFDM systems over frequencyselective Rayleigh fading channels. In addition, the channel capacity for the QAM OFDM transmission over Rayleigh fading environment is obtained.[[sponsorship]]IEEE Computer Society Technical Committee on Distributed Processing (TCDP); Tamkung University[[notice]]補正完畢[[conferencetype]]國內[[conferencetkucampus]]淡水校園[[conferencedate]]20050328~20050330[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]臺北縣, 臺

Performance of a non-orthogonal STBC over correlative fading channels

[[abstract]]It has been recently shown that, for non-orthogonal space-time block code (STBC), the multiple-input multiple-output (MIMO) maximum-likelihood (ML) metric can also be decoupled into single-input single-output (SISO) ML metrics for decoding simplification just as for orthogonal STBC. In this work, we utilized the decoupled metrics of a non-orthogonal STBC to derive the symbol error rate (SER) in correlative fading channels and show that, when the non-orthogonal code is generated by converting an orthogonal code using proper precoding, the conversion will improve the SER performance when the MIMO channels are correlated.[[conferencetype]]國際[[conferencedate]]20080604~20080606[[booktype]]紙本[[conferencelocation]]Hoi an, Vietna

Frequency tracking by method of least squares combined with channel estimation for OFDM over mobile wireless channels

[[abstract]]To track frequency offset and time-varying channel in orthogonal frequency division multiplexing (OFDM) systems over mobile wireless channels, a common technique is, based on one OFDM training block sample, to apply the maximum-likelihood (ML) algorithm to perform joint frequency tracking and channel estimation employing some adaptive iteration processes. The major drawback of such joint estimation techniques is the local extrema problem arising from the highly nonlinear nature of the log-likelihood function. This makes the joint estimation process very difficult and complicated, and many a time the results are not very satisfactory if the algorithm is not well designed. In this study, rather than using the ML algorithm, we shall apply the method of least squares (LS) for frequency tracking utilizing repeated OFDM training blocks. As will be seen, by using such an LS approach, the frequency offset estimation requires no channel knowledge. The channel state can be estimated separately after the LS frequency offset correction. This not only circumvents the local extrema complication, but also obviates the need for the lengthy adaptive iteration process of joint estimation thus greatly simplifies the entire estimation process. Most importantly, our technique can achieve excellent estimation performance as compared to the usual ML algorithms.[[incitationindex]]SCI[[booktype]]紙

Iterative joint frequency offset and channel estimation for OFDM systems using first and second order approximation algorithms

[[abstract]]To implement an algorithm for joint estimation of carrier frequency offset (CFO) and channel impulse response (CIR) in orthogonal frequency division multiplexing (OFDM) systems, the maximum-likelihood criterion is commonly adopted. A major difficulty arises from the highly nonlinear nature of the log-likelihood function which renders local extrema or multiple solutions for the CFO and CIR estimators. Use of an approximation method coupled with an adaptive iteration algorithm has been a popular approach to ease problem solving. The approximation used in those existing methods is usually of the first order level. Here, in addition to a new first order approximation method, we also propose a second order approximation method. Further, for the part of the adaptive iteration algorithm, we adopt a new technique which will enable performance improvement. Our first order approximation method is found to outperform the existing ones in terms of estimation accuracies, tracking range, computation complexity, and convergence speed. As expected, our second order approximation method provides an even further improvement at the expense of higher computation complication.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子版[[countrycodes]]DE

Effective approximate algorithms for joint frequency offset and channel estimation for OFDM systems

[[conferencetype]]國際[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Guilin, Chin

Finite High Order Approximation Algorithm for Joint Frequency Tracking and Channel Estimation in OFDM Systems

[[abstract]]For maximum-likelihood (ML) estimation to jointly track carrier frequency offset (CFO) and channel impulse response (CIR) in orthogonal frequency division multiplexing (OFDM) systems, we present a finite high order approximation method utilizing the MATLAB ‘roots' command on the log-likelihood function derived from the OFDM received signal, coupled with an adaptive iteration algorithm. The tracking performance of this high order approximation algorithm is found to be excellent, and as expected, the algorithm outperforms the other existing first order approximation algorithms.[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Generalized minimum symbol error Rate for linear equalization

[[abstract]]A generalized formula for the decision error probability is derivedfor an M-ary PAM system. Then, by applying the gradient method to thisgeneralized formula, a GMSER algorithm is developed to minimize thesymbol error rate for linear equalization. Then a SGMSER algorithm isobtained by further simplification of GMSER to reduce thecomputational complexity in GMSER. Comparison is then made between theSGMSER algorithm, the MMSE criterion, and an AMBER algorithm asproposed by Yeh and Barry. The results show that the minimum symbolerror rate criterion outperforms the minimum mean-squared errorcriterion. Then, between AMBER and SGMSER, we find that the AMBERoffers less computational complexity, while the SGMSER offers fasterconvergence rate and lower error rate for higher order signaling.[[sponsorship]]中山大學 National Sun Yat-Sen University[[conferencetype]]國際[[conferencedate]]20021121~20021124[[booktype]]紙本[[conferencelocation]]高雄, 臺

Application of a Novel Maximum-Likelihood Algorithm to the Estimation of Signal Propagation Delay in an Optical Fiber Link

[[incitationindex]]EI[[booktype]]紙