Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems
碩士 === 國立交通大學 === 電信工程系 === 91 === The frequency uncertainty associated with an orthogonal frequency division multiplexing (OFDM) signal, depending on the application, can be as large as many tens subcarrier spacings. This carrier frequency offset (CFO) uncertainty i...
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ndltd-TW-091NCTU04350132016-06-22T04:14:27Z http://ndltd.ncl.edu.tw/handle/73794105001352323694 Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems 正交分頻多工系統之最大可靠度頻率偏移估計法 JiunHung Yu 余俊宏 碩士 國立交通大學 電信工程系 91 The frequency uncertainty associated with an orthogonal frequency division multiplexing (OFDM) signal, depending on the application, can be as large as many tens subcarrier spacings. This carrier frequency offset (CFO) uncertainty is usually partitioned into an integer part and a fractional part and must be compensated for before other synchronization and demodulation operations take place. This thesis presents complete optimal (in the generalized maximum likelihood sense) and near-optimal solutions for the above CFO compensation problem. Based on the generalized maximum likelihood (ML) principle and assuming the availability of pilot symbols, we derive efficient algorithms for estimating either the fractional part or the integer part of the CFO, assuming a fractional-then-integer frequency synchronization procedure. By deriving the ML fractional CFO estimates based on repetitive identical training symbols, we show that all previous correlation-based algorithms use only a part of the sufficient statistic. We then convert the problem of obtaining the ML solution from searching exhaustively over the entire uncertainty range to that of solving a spectrum polynomial whence greatly reduce the computational load. By properly truncating the spectrum polynomial, we obtain a closed-form expression for the corresponding zeros so that the root-searching procedure is much simplified. The complexity of locating the desired root is further reduced at almost no expense of performance degradation by an alternate algorithm that uses the fact that the solution is related to the root of a special factor of the polynomial. This alternate method is very attractive for its simplicity and excellent performance that, even at low signal-to-noise ratios (SNRs), is very close to the corresponding Cram\''r-Rao lower bound. We also present detailed analysis of the mean-squared error (MSE) performance and validate our analysis by simulations. The frequency ambiguity due to the presence of an integer CFO should be resolved once the fractional part has been estimated. We propose a special pilot symbols structure that can be used in both fractional and integer CFO estimations. A class of new ML integer CFO estimation algorithms is derived and the associated performance is presented. The pilot structure is a generalization of some earlier proposals and our derivation gives these proposal a unified theoretical foundation. To reduce the estimation complexity, we examine some variations of the ML estimate and suggest a two-stage method whose performance is almost as good as that of the optimal estimate. Yu T. Su 蘇育德 2003 學位論文 ; thesis 61 zh-TW |
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碩士 === 國立交通大學 === 電信工程系 === 91 === The frequency uncertainty associated with an orthogonal frequency
division multiplexing (OFDM) signal, depending on the application,
can be as large as many tens subcarrier spacings. This carrier
frequency offset (CFO) uncertainty is usually partitioned into an
integer part and a fractional part and must be compensated for
before other synchronization and demodulation operations take
place.
This thesis presents complete optimal (in the generalized maximum
likelihood sense) and near-optimal solutions for the above CFO
compensation problem. Based on the generalized maximum likelihood
(ML) principle and assuming the availability of pilot symbols, we
derive efficient algorithms for estimating either the fractional
part or the integer part of the CFO, assuming a
fractional-then-integer frequency synchronization procedure.
By deriving the ML fractional CFO estimates based on repetitive
identical training symbols, we show that all previous
correlation-based algorithms use only a part of the sufficient
statistic. We then convert the problem of obtaining the ML
solution from searching exhaustively over the entire uncertainty
range to that of solving a spectrum polynomial whence greatly
reduce the computational load. By properly truncating the spectrum
polynomial, we obtain a closed-form expression for the
corresponding zeros so that the root-searching procedure is much
simplified.
The complexity of locating the desired root is further reduced at
almost no expense of performance degradation by an alternate
algorithm that uses the fact that the solution is related to the
root of a special factor of the polynomial. This alternate method
is very attractive for its simplicity and excellent performance
that, even at low signal-to-noise ratios (SNRs), is very close to
the corresponding Cram\''r-Rao lower bound. We also present
detailed analysis of the mean-squared error (MSE) performance and
validate our analysis by simulations.
The frequency ambiguity due to the presence of an integer CFO
should be resolved once the fractional part has been estimated. We
propose a special pilot symbols structure that can be used in both
fractional and integer CFO estimations. A class of new ML integer
CFO estimation algorithms is derived and the associated
performance is presented. The pilot structure is a generalization
of some earlier proposals and our derivation gives these proposal
a unified theoretical foundation. To reduce the estimation
complexity, we examine some variations of the ML estimate and
suggest a two-stage method whose performance is almost as good as
that of the optimal estimate.
|
author2 |
Yu T. Su |
author_facet |
Yu T. Su JiunHung Yu 余俊宏 |
author |
JiunHung Yu 余俊宏 |
spellingShingle |
JiunHung Yu 余俊宏 Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems |
author_sort |
JiunHung Yu |
title |
Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems |
title_short |
Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems |
title_full |
Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems |
title_fullStr |
Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems |
title_full_unstemmed |
Maximum Likelihood Frequency Offset Estimation Algorithms for OFDM Systems |
title_sort |
maximum likelihood frequency offset estimation algorithms for ofdm systems |
publishDate |
2003 |
url |
http://ndltd.ncl.edu.tw/handle/73794105001352323694 |
work_keys_str_mv |
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