2,197 research outputs found
Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems
Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER
On Optimal Turbo Decoding of Wideband MIMO-OFDM Systems Under Imperfect Channel State Information
We consider the decoding of bit interleaved coded modulation (BICM) applied
to both multiband and MIMO OFDM systems for typical scenarios where only a
noisy (possibly very bad) estimate of the channel is provided by sending a
limited number of pilot symbols. First, by using a Bayesian framework involving
the channel a posteriori density, we adopt a practical decoding metric that is
robust to the presence of channel estimation errors. Then this metric is used
in the demapping part of BICM multiband and MIMO OFDM receivers. We also
compare our results with the performance of a mismatched decoder that replaces
the channel by its estimate in the decoding metric. Numerical results over both
realistic UWB and theoretical Rayleigh fading channels show that the proposed
method provides significant gain in terms of bit error rate compared to the
classical mismatched detector, without introducing any additional complexity
Performance Analysis and Enhancement of Multiband OFDM for UWB Communications
In this paper, we analyze the frequency-hopping orthogonal frequency-division
multiplexing (OFDM) system known as Multiband OFDM for high-rate wireless
personal area networks (WPANs) based on ultra-wideband (UWB) transmission.
Besides considering the standard, we also propose and study system performance
enhancements through the application of Turbo and Repeat-Accumulate (RA) codes,
as well as OFDM bit-loading. Our methodology consists of (a) a study of the
channel model developed under IEEE 802.15 for UWB from a frequency-domain
perspective suited for OFDM transmission, (b) development and quantification of
appropriate information-theoretic performance measures, (c) comparison of these
measures with simulation results for the Multiband OFDM standard proposal as
well as our proposed extensions, and (d) the consideration of the influence of
practical, imperfect channel estimation on the performance. We find that the
current Multiband OFDM standard sufficiently exploits the frequency selectivity
of the UWB channel, and that the system performs in the vicinity of the channel
cutoff rate. Turbo codes and a reduced-complexity clustered bit-loading
algorithm improve the system power efficiency by over 6 dB at a data rate of
480 Mbps.Comment: 32 pages, 10 figures, 1 table. Submitted to the IEEE Transactions on
Wireless Communications (Sep. 28, 2005). Minor revisions based on reviewers'
comments (June 23, 2006
Development of a dc-ac power conditioner for wind generator by using neural network
This project present of development single phase DC-AC converter for wind
generator application. The mathematical model of the wind generator and Artificial
Neural Network control for DC-AC converter is derived. The controller is designed to
stabilize the output voltage of DC-AC converter. To verify the effectiveness of the
proposal controller, both simulation and experimental are developed. The simulation and
experimental result show that the amplitude of output voltage of the DC-AC converter
can be controlled
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