REVIEW OF WIRELESS MIMO CHANNEL MODELS

The need to increase spectral efficiency has led to the design of multiple antenna systems for both transmit and receive sides otherwise known as MIMO. Channel modeling forms an integral part of this design. Therefore it is very important to investigate and understand existing MIMO channel models. This paper provides a detailed review of existing MIMO channel models, their characteristics, tradeoffs and challenges. As with most models in the scientific and technical fields, open issues in MIMO channel modeling have also been enumerated. http://dx.doi.org/10.4314/njt.v35i2.2

Broadband wireless communication systems: Channel modeling and system performance analysis

Wideband channel modeling, which can accurately describe the most important characteristics of wideband mobile fading channels, is essential for the design, evaluation, and optimization of broadband wireless communication systems. In the field of wideband channel modeling, the tradeoff between the prediction accuracy and simulation efficiency has to be taken into account. On one hand, channel models should be as accurate as possible. On the other hand, channel models are supposed to be simple and easy to put into use. There are several commonly used approaches to channel modeling, e.g., measurement-based channel modeling and deterministic channel modeling. Both methods are efficient in capturing the fading behavior of real-world wireless channels. However, the resulting channel models are only valid for the specific environments as those where the measurements were carried out or the ray-tracing scenario was considered. Moreover, these methods are quite time consuming with high computational cost. Alternatively, the geometry-based stochastic channel modeling approach can be employed to model wideband mobile fading channels. The most attractive feature of this method is that the derived channel models are able to predict fading behavior for various propagation environments, and meanwhile they can be easily implemented. Thus, the dissertation will complete the wideband channel modeling task by adopt the geometry-based stochastic approach. In the dissertation, several geometry-based channel models are proposed for both outdoor and indoor propagation scenarios. The significance of the work lies in the fact that it develops channel models under more realistic propagation conditions which have seldom been considered, such as for non-isotropic scattering environxi ments and mobile-to-mobile (M2M) fading channels. In addition, the proposed channel models remove the scarcity that proper geometry-based channel models are missing for indoor environments. The most important statistical properties of the developed channel models including their temporal autocorrelation function (ACF), the two-dimensional (2D) space cross-correlation function (CCF), and the frequency correlation function (FCF) are analyzed. Furthermore, efficient channel simulators with low realization expenditure are obtained. Finally, the validity of the proposed channel models is demonstrated by comparing their analytical channel statistics with the empirical ones measured from real world channels. Besides the work in the field of wideband channel modeling, another part of the dissertation is dedicated to investigate the performance of SISO1 orthogonal frequency division multiplexing (OFDM) broadband communication systems and space-time (ST) coded MIMO2 OFDM broadband communication systems. This work provides a deep insight into the performance of a broadband mobile radio communication system over realistic wideband fading channels. Analytical expressions are derived for bit error probability (BEP) or symbol error rate (SER) of systems. In order to confirm the correctness of the theoretical results as well as to show the usefulness of the wideband channel models in the testing and analysis of a broadband communication system, SISO OFDM systems and space-time coded MIMO OFDM systems are simulated in the dissertation. In order to improve the reliability of digital transmission over broadband wireless radio channels, a differential super-orthogonal space-time trellis code (SOSTTC) is designed for noncoherent communications, where neither the transmitter nor the receiver needs the channel state information (CSI) for decoding. In addition, a new decoding algorithm is proposed. The new algorithm has exactly the same decoding performance as the traditional one. However, it is superior from the standpoint of overall computing complexity

State-of-the-art assessment of 5G mmWave communications

Deliverable D2.1 del proyecto 5GWirelessMain objective of the European 5Gwireless project, which is part of the H2020 Marie Slodowska- Curie ITN (Innovative Training Networks) program resides in the training and involvement of young researchers in the elaboration of future mobile communication networks, focusing on innovative wireless technologies, heterogeneous network architectures, new topologies (including ultra-dense deployments), and appropriate tools. The present Document D2.1 is the first deliverable of Work- Package 2 (WP2) that is specifically devoted to the modeling of the millimeter-wave (mmWave) propagation channels, and development of appropriate mmWave beamforming and signal processing techniques. Deliver D2.1 gives a state-of-the-art on the mmWave channel measurement, characterization and modeling; existing antenna array technologies, channel estimation and precoding algorithms; proposed deployment and networking techniques; some performance studies; as well as a review on the evaluation and analysis toolsPostprint (published version

Physical-statistical modeling of dynamic indoor power delay profiles

This paper presents a physical-statistical radio channel power delay profiles model for room-to-room communication systems combining the room electromagnetic theory for modeling deterministic channel components with a geometry-based stochastic channel model with time-variant statistics for modeling stochastic components. The deterministic channel component, i.e., mean power delay spectrum, is comprised of specularly reflected paths plus diffuse components due to scattering and diffraction. The specular components are modeled with a set Dirac function, whereas the diffuse components modeling approach is a room electromagnetic theory-based model. Dynamic indoor communication channels are characterized by a non-stationary time-and delay-fading process due to changes in the environment. We analyze and model the time-delay variability of channels using K-factor for small-scale variations and the t-location scale distribution parameters for large-scale variations. It turns out that these parameters cannot be assumed to be constant in time and delay. After modeling of time-delay variations of the first order statistics, we generate channel realizations with appropriate second order statistics. As the result, the presented model enables to describe the evolution of the power delay profile in the time domain

Statistical modeling, simulation, and experimental verification of wideband indoor mobile radio channel

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Classification and comparison of massive MIMO propagation channel models

Considering great benefits brought by massive multiple-input multiple-output (MIMO) technologies in Internet of things (IoT), it is of vital importance to analyze new massive MIMO channel characteristics and develop corresponding channel models. In the literature, various massive MIMO channel models have been proposed and classified with different but confusing methods, i.e., physical vs. analytical method and deterministic vs. stochastic method. To have a better understanding and usage of massive MIMO channel models, this work summarizes different classification methods and presents an up-to-date unified classification framework, i.e., artificial intelligence (AI)-based predictive channel models and classical non-predictive channel models, which further clarify and combine the deterministic vs. stochastic and physical vs. analytical methods. Furthermore, massive MIMO channel measurement campaigns are reviewed to summarize new massive MIMO channel characteristics. Recent advances in massive MIMO channel modeling are surveyed. In addition, typical non-predictive massive MIMO channel models are elaborated and compared, i.e., deterministic models and stochastic models, which include correlation-based stochastic model (CBSM), geometry-based stochastic model (GBSM), and beam domain channel model (BDCM). Finally, future challenges in massive MIMO channel modeling are given