128 research outputs found

    Performance of Dual Selection Combiners Over Correlated Nakagami-m Fading With Different Fading Parameters

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    This letter presents infinite series expressions for the outage probability, the probability density function (PDF), the average error probability for binary modulations, and average signal-to-noise ratio (SNR) of dual selection combiners (SC) over correlated fading with arbitrary fading parameters at each input of the combiner. The outage probability is calculated for both thermal noise and interference-limited scenarios. The results obtained for the outage probabilities specified for identical fading parameters at both branches of the combiner are contrasted with the results of other studies in the literature.Reig, J.; Rubio Arjona, L.; Rodrigo Peñarrocha, VM. (2006). Performance of Dual Selection Combiners Over Correlated Nakagami-m Fading With Different Fading Parameters. IEEE Transactions on Communications. 54(9):1527-1532. doi:10.1109/TCOMM.2006.881188S1527153254

    小型衛星搭載の合成開口レーダー用の集中型送受信システムを有する2偏波対応進行波型アンテナ

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    学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 齋藤 宏文, 東京大学教授 橋本 樹明, 東京大学教授 保立 和夫, 東京電機大学教授 小林 岳彦, 東京工業大学教授 廣川 二郎University of Tokyo(東京大学

    MIMO techniques for higher data rate wireless communications

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    The demand for higher data rate, higher spectral efficiency and better quality of service in wireless communications is growing fast in the past few years. However, obtaining these requirements become challenging for wireless communication systems due to the problems of channel multi-path fading, higher power loss and power bandwidth limitations. A lot of research interest has been directed towards implementing new techniques in wireless communication systems, such as MIMO an OFDM, to overcome the above mentioned problems. Methods of achieving higher data rate and better spectral efficiency have been dealt with in the thesis. The work comprised three parts; the first part focuses on channel modelling, the second looks at fading mitigation techniques, and the third part deals with adaptive transmission schemes for different diversity techniques. In the first part, we present multiple-input multiple-output (MIMO) space-time geometrical channel model with hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment. The model is based on one-ring scattering assumption. This MIMO model provides statistics of the time of arrival (TOA) and direction of arrival (DOA). Our analytical results are validated with measurement data and compared to different geometrical based signal bounce macro-cell (GBSSBM) channel models including Gaussian scatterer density (GSD) channel model, the geometrical based exponential (GBE) channel model. On the other hand, for the same channel model we investigate the analytical methods which capture physical wave and antenna configuration at both ends representing in a matrix form. In the second part, we investigate the proposed channel model using joint frequency and spatial diversity system. . We combine STBC with OFDM to improve the error performance in the fading channels. We consider two different fading scenarios namely frequency selective and time selective fading channels. For the first scenario we propose a new technique to suppress the frequency error offset caused by the motion of mobile (Doppler shift). On the other hand, we examine the performance of STBC-OFDM in time selective macro-cell channel environment. In the last part, we evaluate the spectral efficiency for different receiver diversity namely maximal ratio combiner (MRC), selection combiner (SC), and Hybrid (MRC/SC). We derive closed form expressions for the single user capacity, taking into account the effect of imperfect channel estimation at the receiver. The channel considered is a slowly varying spatially independent flat Rayleigh fading channel. Three adaptive transmission schemes are analysed: 1) optimal power rate and rate adaptation (opra), constant power with optimal rate adaptation (ora), and 3) channel inversion with fixed rate (cifr). Furthermore, we derive analytical results for capacity statistics including moment generating function (MGF), complementary cumulative distribution function (CDF) and probability density function (pdf)
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