Browsing by Author "Wu, Wen Rong"

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A low-complexity design method for DMT time domain equalizers
(2006)
Lee, Chun Fang
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Wu, Wen Rong
;
電信工程研究所
;
Institute of Communications Engineering
The time-domain equalizer (TEQ) is a commonly used device to shorten the channel impulse response in a discrete multitone (DMT) receiver. With a capacity maximization criterion, a TEQ design method called minimum intersymbol interference (minISI) has shown to have nearly optimum performance. However, the minISI design method require high computational complexity. adversely affecting its real-world implementation. In this papers we propose a low-complexity method to overcome this problem. The main idea is to use a subset of the subchannels, instead of all,. for capacity maximization. With a simple equally-spaced sampling method, the number of subchannels required for calculation can be effectively reduced. Simulations show that the performance of the proposed algorithm is almost the same as the original minISI while its computation is dramatically reduced.
A multistage IIR time domain equalizer for OFDM systems
(2007)
Lee, Chun Fang
;
Wu, Wen Rong
;
電信工程研究所
;
Institute of Communications Engineering
The time-domain equalizer (TEQ) is a commonly used device to shorten the channel impulse response in an orthogonal frequency division multiplexing (OFDM) receiver. With a SSNR maximization criterion, the MSSNR TEQ method is one attractive method with its supreme performance. However, the MSSNR method suffers from high computation complexity when employing the TEQ with long taps. We first demonstrate the MSSNR method and the Steiglitz McBride method for translating the prescribed FIR to an IIR form. Then we propose a multistage TEQ method with the Steiglitz McBride method. Based on the structures, we analyze the computational complexity. Simulations show that the proposed method is almost the same performance as the existing ones and its computation can be reduced dramatically.
Blind Maximum-Likelihood Carrier-Frequency-Offset Estimation for Interleaved OFDMA Uplink Systems
(2011-01-01)
Hsieh, Hung-Tao
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Wu, Wen Rong
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電信工程研究所
;
Institute of Communications Engineering
Blind maximum-likelihood (ML) carrier-frequency-offset (CFO) estimation is considered to be difficult in interleaved orthogonal frequency-division multiple-access (OFDMA) uplink systems. This is because multiple CFOs have to be simultaneously estimated (each corresponding to a user's carrier), and an exhaustive multidimensional search is required. The computational complexity of the search may be prohibitively high. Methods such as the multiple signal classification and the estimation of signal parameters via the rotational invariance technique have been proposed as alternatives. However, these methods cannot maximize the likelihood function, and the performance is not optimal. In this paper, we propose a new method to solve the problem. With our formulation, the likelihood function can be maximized, and the optimum solution can be obtained by solving a polynomial function. Compared with the exhausted search, the computational complexity can be reduced dramatically. Simulations show that the performance of the proposed method can approach that of the Cramer-Rao lower bound.
Intra-Site CoMP in LTE-A Systems: an Antenna-Selection-Based Solution
(2012)
Liao, Bin-Sung
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Wu, Wen Rong
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Hsieh, Hung-Tao
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電機工程學系
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Department of Electrical and Computer Engineering
It is known that in cellular systems, the users in cell edge suffer from the interference from interfering cells. In LTE-A, coordinated multi-point (CoMP) processing was proposed to solve the problem. In CoMP, the transmitted/received signals of the users in neighbor cells can be jointly processed such that interference can be either avoided or estimated as desired signals. In the current CoMP operations, precoding is only conducted between individual base-stations and the served user. If we take all the base-stations and the served user into consideration, a network multiple-input-multiple-output (MIMO) system can be constructed. Precoding in such system will have better performance but require a high-dimension codebook which is not supported by current LTE-A systems. In this paper, we first propose a method to solve the problem. The idea is to use the antenna selection technique reducing the number of transmitted antennas such that the existing codebooks can still be used. Existing selection criteria for the maximum likelihood receivers often require sophisticated matrix operations such as QR-decomposition (QRD). Thus, the required computational complexity is high. We then propose some selection criteria without involving matrix operations. Simulations show that while the antenna-selection based precoding method can reduce the feedback overhead and at the same time improve the precoding performance. Also, the performance of the proposed low-complexity criteria is similar to that of the QRD-based criteria.
Maximum likelihood timing and carrier frequency offset estimation for OFDM systems with periodic preambles
(2006)
Hsieh, Hung Dau
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Wu, Wen Rong
;
電信工程研究所
;
Institute of Communications Engineering
Timing offset (TO) and carrier frequency offset (CFO) are two common problems observed in OFDM systems. Maximum likelihood (ML) methods have been proposed for CFO estimation. The conventional ML estimates consider a pilot-assisted system, in which two identical preambles are repeatedly transmitted. In some applications, the preambles of an OFDM system are repeated more than two times. A typical example is the preambles of the EEEE802.11a/g wireless local area network (LAN) system. A ML CFO estimation method for the system was proposed recently; however, the method has to solve the roots of the derivative of the likelihood function, and the computational complexity is high. Also, the TO estimation problem is not considered. In this paper, new methods are developed for the TO and CFO estimation problems. Our method is simple and does not rely on the root-finding approach. Simulations show that while the performance of the proposed method is either equal to or better than the existing method, the computational complexity is much lower.