Third generation (3G) cellular communication standards are based on Wideband Code Division Multiple Access (WCDMA). The wideband signals experience frequency-selective fading due to multi-path propagation, hence increasing the Multiple Access Interference (MAI). To combat this effect, an efficient channel estimation algorithm, based on the Maximum Likelihood (ML) approach is derived. The algorithm handles the situation of multiuser, and multi-path by estimating a composite Channel Impulse Response (CIR). This estimation is performed in the reverse link, for each user, without needs of estimating each individual channel parameters. This has the achievement of reducing the computational complexity. The efficiency of the proposed channel estimator is measured in terms of Mean Squared Error (MSE), handling capacity, loss due to estimation, as well as resistance to MAI.
Several models were proposed to predict the attenuation of microwave signals due to sand and dust storms. Those models were developed based on theoretical assumptions like Rayleigh approximation, Mie equations or numerical methods. This paper presents a comparison between attenuation predicted by three different theoretical models with measured attenuation at 14 GHz. Dielectric constant of dust particles is one of the important parameter in prediction models. This constant is estimated from measured dust samples and is utilized for predictions. All models are found largely underestimating the measurement. Humidity is also monitored and has been observed higher during dust storm. Hence dielectric constants are re-estimated with relative humidity conditions using available conversion model. The prediction has a great impact of humidity and predicted attenuations are found much higher in humid than dry dust condition. However, all models underestimate the measurement even considering 100% of relative humidity. Hence it is recommended to investigate the models by considering humidity and other environmental factors that change during dust storm.
In some communication systems, it is desirable for the receiver to synchronize to the received signal and to adjust the equalizer without having knowledge of a training sequence. Blind equalization uses the initial adjustment of the coefficients without making use of a training sequence. Different adaptive blind equalization algorithms have been developed over the past four decades. In this paper, we investigate the effect of blind equalization on space communication channels. The space channel under investigation is considered to be a multipath frequency selective channel having four paths. The channel is subjected to the phenomenon of InterSymbol Interference (ISI) which severely degrades the performance of the space communication system. Two blind algorithms are used in equalizer adjustment. The impulse responses of the space channel, the blind equalizer and the combination of channel and equalizer for QPSK and 16-QAM transmission are shown. The scatter diagrams for the transmitted sequence, received sequence, and the output of the equalizer using two of the blind algorithms are shown.
Orthogonal Frequency Division Multiplexing (OFDM) is an emerging multi-carrier modulation scheme, which has been adopted for several wireless standards such as IEEE 802.11a and HiperLAN2. In OFDM systems, the performance is very sensitive to subcarrier frequency errors (offset). This paper shows the analysis and derivations of intercarrier interference (ICI) complex gain that used in self-cancellation scheme and its dependence on subcarrier frequency offset. Simulation shows that better improvement in performance is achieved for systems that use this cancellation scheme. Moreover, analysis and simulation show that theoretical carrier-to-interference ratio (CIR) for OFDM with cancellation scheme is greater than conventional one by more than 14dB.DOI:Â 10.18495/comengapp.11.013023
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