Performance of MIMO beamforming transmission scheme in the presence of mutual coupling

This paper reports investigations into mutual coupling effects on performance of a beamforming transmission scheme of a multiple-input multipleoutput (MIMO) system operating under Rician channel conditions. It is shown that the presence of mutual coupling in a transmitting array antenna degrades the radiation pattern. However, it does not adversely affect the system capacity. If the correlated Rayleigh component (NLOS) dominates the channel, the mutual coupling leads to lower capacity. The presence of mutual coupling results in a higher capacity when the LOS component prevails. For some specific ranges of array inter-element spacing, mutual coupling can be seen as beneficial in terms of increasing the capacity when a signal beamforming strategy is applied. © 2010 IEEE

On the Geometric Modeling of the Uplink Channel in a Cellular System

To meet the challenges of present and future wireless communications realistic propagation models that consider both spatial and temporal channel characteristics are used. However, the complexity of the complete characterization of the wireless medium has pointed out the importance of approximate but simple approaches. The geometrically based methods are typical examples of low–complexity but adequate solutions. Geometric modeling idealizes the aforementioned wireless propagation environment via a geometric abstraction of the spatial relationships among the transmitter, the receiver, and the scatterers. The paper tries to present an efficient way to simulate mobile channels using geometrical–based stochastic scattering models. In parallel with an overview of the most commonly used propagation models, the basic principles of the method as well the main assumptions made are presented. The study is focused on three well–known proposals used for the description of the Angle–of –Arrival and Time–of–Arrival statistics of the incoming multipaths in the uplink of a cellular communication system. In order to demonstrate the characteristics of these models illustrative examples are given. The physical mechanism and motivations behind them are also included providing us with a better understanding of the physical insight of the propagation medium

Simulation of Wireless Digital Communication Systems

Due to the explosive demands for high speed wireless services, such as wireless Internet, email and cellular video conferencing, digital wireless communications has become one of the most exciting research topics in electrical and electronic engineering field. The never-ending demand for such personal and multimedia services, however, demands technologies operating at higher data rates and broader bandwidths. In addition, the complexity of wireless communication and signal processing systems has grown considerably during the past decade. Therefore, powerful computer­aided techniques are required for the process of modeling, designing, analyzing and evaluating the performance of digital wireless communication systems. In this paper we discuss the basic propagation mechanisms affecting the performance of wireless communication systems, and present a simple, powerful and efficient way to simulate digital wireless communication systems using Matlab. The simulated results are compared with the theoretical analysis to validate the simulator. The simulator is useful in evaluating the performance of wireless multimedia services and the associated signal processing structures and algorithms for current and next generation wireless mobile communication systems

A combined channel-modified adaptive array MMSE canceller and viterbi equalizer

In this thesis, a very simple scheme is proposed which couples a maximum-likelihood sequence estimator (MLSE) with a X-element canceller. The method makes use of the MLSE\u27s channel estimator to modify the locally generated training sequence used to calculate the antenna array weights. This method will increase the array\u27s degree of freedom for interference cancellation by allowing the dispersive, desired signal to pass through the array undisturbed. Temporal equalization of the desired signal is then accomplished using maximum-likelihood sequence estimation. The T-spaced channel estimator coefficients and the array weights are obtained simultaneously using the minimum mean square error criteria. The result is a X-element receiver structure capable of canceling X- 1 in-band interferences without compromising temporal equalization

A statistical model for the dual polarised MIMO land mobile satellite channel at S-band

This thesis explores channel modelling approaches to the land mobile satellite (LMS) channel in S-band, focussing on the implementation of multiple input multiple output techniques through the use of dual polarisation. An Enhanced Statistical Model is presented and the output of this model is analysed and compared to the two current state-of-the-art models that simulate the dual polarised LMS channel, i.e. the statistical Liolis-CTTC model and the geometric ray-tracing QuaDRiGa model. The enhanced model builds on the Liolis-CTTC model and presents solutions to a number of issues that arise in the statistical modelling process. The enhancements in the new model include imposing temporal correlation on the slow variations without unwanted high frequency components from low-pass filtering, introducing Doppler effects including Doppler shaping of the fast variations, implementing a smooth state transition process and also implementing an interpolation process to sample the channel at the required sub-symbol rate for transmission. In addition to the analysis of the three models, real channel measurements of the dual polarised LMS channel from the MIMOSA campaign are analysed. A statistical comparison between the models and the real measurement data for simulated journeys in a number of user environments is conducted through analysis of the timeseries, the cumulative density function (CDF), average fading duration (AFD) and level-crossing rate (LCR). Capacity analysis and eigenvalue analysis is also conducted and allows for validation of the enhanced model. The comparisons with the measurement data show good agreement between the real measurement data and the enhanced model

A novel wideband dynamic directional indoor channel model based on a Markov process

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Beam alignment for millimeter wave vehicular communications

Millimeter wave (mmWave) has the potential to provide vehicles with high data rate communications that will enable a whole new range of applications. Its use, however, is not straightforward due to its challenging propagation characteristics. One approach to overcome the propagation challenge is the use of directional beams, but it requires a proper alignment and presents a challenging engineering problem, especially under the high vehicular mobility. In this dissertation, fast and efficient beam alignment solutions suitable for vehicular applications are developed. To better quantify the problem, first the impact of directional beams on the temporal variation of the channels is investigated theoretically. The proposed model includes both the Doppler effect and the pointing error due to mobility. The channel coherence time is derived, and a new concept called the beam coherence time is proposed for capturing the overhead of mmWave beam alignment. Next, an efficient learning-based beam alignment framework is proposed. The core of this framework is the beam pair selection methods that use side information (position in this case) and past beam measurements to identify promising beam directions and eliminate unnecessary beam training. Three offline learning methods for beam pair selection are proposed: two statistics-based and one machine learning-based methods. The two statistical learning methods consist of a heuristic and an optimal selection that minimizes the misalignment probability. The third one uses a learning-to-rank approach from the recommender system literature. The proposed approach shows an order of magnitude lower overhead than existing standard (IEEE 802.11ad) enabling it to support large arrays at high speed. Finally, an online version of the optimal statistical learning method is developed. The solution is based on the upper confidence bound algorithm with a newly introduced risk-aware feature that helps avoid severe misalignment during the learning. Along with the online beam pair selection, an online beam pair refinement is also proposed for learning to adapt the codebook to the environment to further maximize the beamforming gain. The combined solution shows a fast learning behavior that can quickly achieve positive gain over the exhaustive search on the original (and unrefined) codebook. The results show that side information can help reduce mmWave link configuration overhead.Electrical and Computer Engineerin