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

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Massive MIMO Extensions to the COST 2100 Channel Model: Modeling and Validation

To enable realistic studies of massive multiple-input multiple-output systems, the COST 2100 channel model is extended based on measurements. First, the concept of a base station-side visibility region (BS-VR) is proposed to model the appearance and disappearance of clusters when using a physically-large array. We find that BS-VR lifetimes are exponentially distributed, and that the number of BS-VRs is Poisson distributed with intensity proportional to the sum of the array length and the mean lifetime. Simulations suggest that under certain conditions longer lifetimes can help decorrelating closely-located users. Second, the concept of a multipath component visibility region (MPC-VR) is proposed to model birth-death processes of individual MPCs at the mobile station side. We find that both MPC lifetimes and MPC-VR radii are lognormally distributed. Simulations suggest that unless MPC-VRs are applied the channel condition number is overestimated. Key statistical properties of the proposed extensions, e.g., autocorrelation functions, maximum likelihood estimators, and Cramer-Rao bounds, are derived and analyzed.Comment: Submitted to IEEE Transactions of Wireless Communication

Statistical millimeter wave channel modelling for 5G and beyond

Millimetre wave (mmWave) wireless communication is one of the most promising technologies for the fifth generation (5G) wireless communication networks and beyond. The very broad bandwidth and directional propagation are the two features of mmWave channels. In order to develop the channel models properly reflecting the characteristics of mmWave channels, the in-depth studies of mmWave channels addressing those two features are required. In this thesis, three mmWave channel models and one beam alignment scheme are proposed related to those two features. First, for studying the very broad bandwidth feature of mmWave channels, we introduce an averaged power delay profile (APDP) method to estimate the frequency stationarity regions (FSRs) of channels. The frequency non-stationary (FnS) properties of channels are found in the data analysis. A FnS model is proposed to model the FnS channels in both the sub-6 GHz and mmWave frequency bands and cluster evolution in the frequency domain is utilised in the implementation of FnS model. Second, for studying the directional propagation feature of mmWave channels, we develop an angular APDP (A-APDP) method to study the planar angular stationarity regions (ASRs) of directional channels (DCs). Three typical directional channel impulse responses (D-CIRs) are found in the data analysis and light-of-sight (LOS), non-LOS (NLOS), and outage classes are used to classify those DCs. A modified Saleh-Valenzuela (SV) model is proposed to model the DCs. The angular domain cluster evolution is utilised to ensure the consistency of DCs. Third, we further extend the A-APDP method to study the spherical-ASRs of DCs. We model the directional mmWave channels by three-state Markov chain that consists of LOS, NLOS, and outage states and we use stationary model, non-stationary model, and “null” to describe the channels in each Markov state according to the estimated ASRs. Then, we propose to use joint channel models to simulate the instantaneous directional mmWave channels based on the limiting distribution of Markov chain. Finally, the directional propagated mmWave channels when the Tx and Rx in motion is addressed. A double Gaussian beams (DGBs) scheme for mobile-to-mobile (M2M) mmWave communications is proposed. The connection ratios of directional mmWave channels in each Markov state are studied

Propagation channel characterisation and modelling for high-speed train communication systems

High-mobility scenarios, e.g., High-Speed Train (HST) scenarios, are expected to be typical scenarios for the Fifth Generation (5G) communication systems. With the rapid development of HSTs, an increasing volume of wireless communication data is required to be transferred to train passengers. HST users demand high network capacity and reliable communication services regardless of their locations or speeds, which are beyond the capability of current HST communication systems. The features of HST channels are significantly different from those of low-mobility cellular communication systems. For a proper design and evaluation of future HST wireless communication systems, we need accurate channel models that can mimic the underlying channel characteristics, especially the non-stationarity for different HST scenarios. Inspired by the lack of such accurate HST channel models in the literature, this PhD project is devoted to the modelling and simulation of non-stationary Multiple-Input Multiple-Output (MIMO) channels for HST communication systems. In this thesis, we first give a comprehensive review of the measurement campaigns conducted in different HST scenarios and address the recent advances in HST channel models. We also highlight the key challenges of HST channel measurements and models. Then, we study the characterisation of non-stationary channels and propose a theoretical framework for deriving the statistical properties of these channels. HST wireless communication systems encounter different channel conditions due to the difference of surrounding geographical environments or scenarios. HST channel models in the literature have either considered large-scale parameters only and/or neglected the non-stationarity of HST channels and/or only consider one of the HST scenarios. Therefore, we propose a novel generic non-stationary Geometry-Based Stochastic Model (GBSM) for wideband MIMO HST channels in different HST scenarios, i.e., open space, viaduct, and cutting. The corresponding simulation model is then developed with angular parameters calculated by the Modified Method of Equal Area (MMEA). The system functions and statistical properties of the proposed channel models are thoroughly studied. The proposed generic non-stationary HST channel models are verified by measurements in terms of stationary time for the open space scenario and the Autocorrelation Function (ACF), Level Crossing Rate (LCR), and stationary distance for the viaduct and cutting scenarios. Transmission techniques which are capable of utilising Three-Dimensional (3D) spatial dimensions are significant for the development of future communication systems. Consequently, 3D MIMO channel models are critical for the development and evaluation of these techniques. Therefore, we propose a novel 3D generic non-stationary GBSM for wideband MIMO HST channels in the most common HST scenarios. The corresponding simulation model is then developed with angular parameters calculated by the Method of Equal Volume (MEV). The proposed models considers several timevarying channel parameters, such as the angular parameters, the number of taps, the Ricean K-factor, and the actual distance between the Transmitter (Tx) and Receiver (Rx). Based on the proposed generic models, we investigate the impact of the elevation angle on some of the channel statistical properties. The proposed 3D generic models are verified using relevant measurement data. Most standard channel models in the literature, like Universal Mobile Telecommunications System (UMTS), COST 2100, and IMT-2000 failed to introduce any of the HST scenarios. Even for the standard channel models which introduced a HST scenario, like IMT-Advanced (IMT-A) and WINNER II channel models, they offer stationary intervals that are noticeably longer than those in measured HST channels. This has inspired us to propose a non-stationary IMT-A channel model with time-varying parameters including the number of clusters, powers, delays of the clusters, and angular parameters. Based on the proposed non-stationary IMT-A channel model, important statistical properties, i.e., the time-variant spatial Cross-correlation Function (CCF) and time-variant ACF, are derived and analysed. Simulation results demonstrate that the stationary interval of the developed non-stationary IMT-A channel model can match that of relevant HST measurement data. In summary, the proposed theoretical and simulation models are indispensable for the design, testing, and performance evaluation of 5G high-mobility wireless communication systems in general and HST ones in specific

Massive MIMO channel modelling for 5G wireless communication systems

Massive Multiple-Input Multiple-Output (MIMO) wireless communication systems, equipped with tens or even hundreds of antennas, emerge as a promising technology for the Fifth Generation (5G) wireless communication networks. To design and evaluate the performance of massive MIMO wireless communication systems, it is essential to develop accurate, flexible, and efficient channel models which fully reflect the characteristics of massive MIMO channels. In this thesis, four massive MIMO channel models have been proposed. First, a novel non-stationary wideband multi-confocal ellipse Two-Dimensional (2-D) Geometry Based Stochastic Model (GBSM) for massive MIMO channels is proposed. Spherical wavefront is assumed in the proposed channel model, instead of the plane wavefront assumption used in conventional MIMO channel models. In addition, the Birth-Death (BD) process is incorporated into the proposed model to capture the dynamic properties of clusters on both the array and time axes. Second, we propose a novel theoretical non-stationary Three-Dimensional (3-D) wideband twin-cluster channel model for massive MIMO communication systems with carrier frequencies in the order of gigahertz (GHz). As the dimension of antenna arrays cannot be ignored for massive MIMO, nearfield effects instead of farfield effects are considered in the proposed model. These include the spherical wavefront assumption and a BD process to model non-stationary properties of clusters such as cluster appearance and disappearance on both the array and time axes. Third, a novel Kronecker Based Stochastic Model (KBSM) for massive MIMO channels is proposed. The proposed KBSM can not only capture antenna correlations but also the evolution of scatterer sets on the array axis. In addition, upper and lower bounds of KBSM channel capacities in both the high and low Signal-to-Noise Ratio (SNR) regimes are derived when the numbers of transmit and receive antennas are increasing unboundedly with a constant ratio. Finally, a novel unified framework of GBSMs for 5G wireless channels is proposed. The proposed 5G channel model framework aims at capturing key channel characteristics of certain 5G communication scenarios, such as massive MIMO systems, High Speed Train (HST) communications, Machine-to-Machine (M2M) communications, and Milli-meter Wave (mmWave) communications