680 research outputs found

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

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    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

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    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

    Accuracy-Complexity Tradeoff Analysis and Complexity Reduction Methods for Non-Stationary IMT-A MIMO Channel Models

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    open access journalHigh-mobility wireless communication systems have attracted growing interests in recent years. For the deployment of these systems, one fundamental work is to build accurate and efficient channel models. In high-mobility scenarios, it has been shown that the standardized channel models, e.g., IMT-Advanced (IMT-A) multiple-input multiple-output (MIMO) channel model, provide noticeable longer stationary intervals than measured results and the wide-sense stationary (WSS) assumption may be violated. Thus, the non-stationarity should be introduced to the IMT-A MIMO channel model to mimic the channel characteristics more accurately without losing too much efficiency. In this paper, we analyze and compare the computational complexity of the original WSS and non-stationary IMT-A MIMO channel models. Both the number of real operations and simulation time are used as complexity metrics. Since introducing the nonstationarity to the IMT-A MIMO channel model causes extra computational complexity, some computation reduction methods are proposed to simplify the non-stationary IMT-A MIMO channel model while retaining an acceptable accuracy. Statistical properties including the temporal autocorrelation function, spatial cross-correlation function, and stationary interval are chosen as the accuracy metrics for verifications. It is shown that the tradeoff between the computational complexity and modeling accuracy can be achieved by using these proposed complexity reduction methods

    Realistic geometry-based stochastic channel models for advanced wireless MIMO systems

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    The employment of multiple antennas at both the Transmitter (Tx) and Receiver (Rx) enables the so-called Multiple-Input Multiple-Output (MIMO) technologies to greatly improve the link reliability and increase the overall system capacity. MIMO has been recommended to be employed in various advanced wireless communication systems, e.g., the Fourth Generation (4G) wireless systems and beyond. For the successful design, performance test, and simulation of MIMO wireless communication systems, a thorough understanding of the underlying MIMO channels and corresponding models are indispensable. The approach of geometry-based stochastic modelling has widely been used due to its advantages, such as convenience for theoretical analysis and mathematical tractability. In addition, wireless Vehicle-to-Vehicle (V2V) communications play an important role in mobile relay-based cellular networks, vehicular ad hoc networks, and intelligent transportation systems. In V2V communication systems, both the Tx and Rx are in motion and equipped with low elevation antennas. This is di erent from conventional Fixed-to-Mobile (F2M) cellular systems, where only one terminal moves. This PhD project is therefore devoted to the modelling and simulation of wireless MIMO channels for both V2V and F2M communication systems. In this thesis, we rst propose a novel narrowband Three Dimensional (3D) theoretical Regular-Shape Geometry Based Stochastic Model (RS-GBSM) and the corresponding Sum-of-Sinusoids (SoS) simulation model for non-isotropic MIMO V2V Ricean fading channels. The proposed RS-GBSM has the ability to study the impact of the Vehicular Tra c Density (VTD) on channel statistics and jointly considers the azimuth and elevation angles by using the von Mises-Fisher (VMF) distribution. Moreover, a novel parameter computation method is proposed for jointly calculating the azimuth and elevation angles in the SoS channel simulator. Based on the proposed 3D theoretical RS-GBSM and its SoS simulation model, statistical properties are derived and thoroughly investigated. The impact of the elevation angle in the 3D model on key statistical properties is investigated by comparing with those of the corresponding Two Dimensional (2D) model. It is demonstrated that the 3D model is more practical to characterise real V2V channels, in particular for pico-cell scenarios. Secondly, actual V2V channel measurements have shown that the modelling assumption of Wide Sense Stationary (WSS) is valid only for very short time intervals. This fact inspires the requirement of non-WSS V2V channel models. Therefore, we propose a novel 3D theoretical wideband MIMO non-WSS V2V RS-GBSM and corresponding SoS simulation model. Due to the dynamic movement of both the Tx and Rx, the Angle of Departure (AoD) and Angle of Arrival (AoA) are time-variant, which makes our model non-stationary. The proposed RS-GBSMs are su ciently generic and adaptable to mimic various V2V scenarios. Furthermore, important local channel statistical properties are derived and thoroughly investigated. The impact of non-stationarity on these channel statistical properties is investigated by comparing with those of the corresponding WSS model. The proposed non-WSS RS-GBSMs are validated by measurements in terms of the channel stationary time. Thirdly, realistic MIMO channel models with a proper trade-o between accuracy and complexity are indispensable for the practical application. By comparing the accuracy and complexity of two latest F2M standardised channel models (i.e., LTE-A and IMT-A channel models), we employ some channel statistical properties as the accuracy metrics and the number of Real Operations (ROs) as the complexity metric. It is shown that the LTE-A MIMO channel model is simple but has signi cant aws in terms of the accuracy. The IMT-A channel model is complicated but has better accuracy. Therefore, we focus on investigating various complexity reduction methods to simplify the IMT-A channel model. The results have shown that the proposed methods do not degrade much the accuracy of the IMT-A channel model, whereas they can signi cantly reduce the complexity in terms of the number of ROs and channel coe cients computing time. Finally, to investigate the non-stationarity of the IMT-A MIMO channel model, we further propose a non-WSS channel model with time-varying AoDs and AoAs. The proposed time-varying functions can be applied to various scenarios according to moving features of Moving Clusters (MCs) and a Mobile Station (MS). Moreover, the impacts of time-varying AoDs and AoAs on local statistical properties are investigated thoroughly. Simulation results prove that statistical properties are varied with time due to the non-stationarity of the proposed channel model. In summary, the proposed reference models and channel simulators are useful for the design, testing, and performance evaluation of advanced wireless V2V and F2M MIMO communication systems

    MIMO channel modelling and simulation for cellular and mobile-to-mobile

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    Recently, mobile-to-mobile (M2M) communications have received much attention due to several emerging applications, such as wireless mobile ad hoc networks, relay-based cellular networks, and dedicated short range communications (DSRC) for intelligent transportation systems (e.g., IEEE 802.11p standard). Different from conventional fixed-to-mobile (F2M) cellular systems, in M2M systems both the transmitter (Tx) and receiver (Rx) are in motion and often equipped with low elevation antennas. Multiple-input-multiple-output (MIMO) technologies, employing multiple antennas at both the Tx and Rx, have widely been adopted for the third generation (3G) and beyond-3G (B3G) F2M cellular systems due to their potential benefits of improving coverage, link reliability, and overall system capacity. More recently, MIMO has been receiving more and more attention for M2M systems as well. Reliable knowledge of the propagation channel obtained from channel measurements and corresponding channel models serve as the enabling foundation for the design and analysis of MIMO F2M and M2M systems. Furthermore, the development of accurate MIMO F2M and M2M channel simulation models plays a major role in the practical simulation and performance evaluation of these systems. These form the primary motivation behind our research on MIMO channel modelling and simulation for F2M cellular and M2M communication systems. In this thesis, we first propose a new wideband theoretical multiple-ring based MIMO regular-shaped geometry-based stochastic model (RS-GBSM) for non-isotropic scattering F2M macro-cell scenarios and then derive a generic space-time-frequency (STF) correlation function (CF). The proposed theoretical reference wideband model can be reduced to a narrowband one-ring model, a new closed-form STF CF of which is derived as well. Narrowband and wideband sum-of-sinusoids (SoS) simulation models are then developed, demonstrating a good agreement with the corresponding reference models in terms of correlation functions. Secondly, based on a well-known narrowband two-ring single-input single-output (SISO) M2M channel reference model, we propose new deterministic and stochastic SoS simulation models for non-isotropic scattering environments. The proposed deterministic simulator is the first SISO M2M deterministic simulator with good performance, while the proposed stochastic simulator outperforms the existing one in terms of fitting the desired statistical properties of the corresponding reference model. Thirdly, a new adaptive narrowband MIMO M2M RS-GBSM is proposed for nonisotropic scattering environments. To the best of our knowledge, the proposed M2M model is the first RS-GBSM that has the ability to study the impact of the vehicular traffic density on channel statistics. From the proposed theoretical reference model, we comprehensively investigate some important M2M channel statistics including the STF CF, space-Doppler-frequency power spectral density, envelope level crossing rate, and average fade duration. A close agreement between some channel statistics obtained from the proposed reference model and measurement data is observed, confirming the utility of our model. Finally, we extend the above narrowband model to a new wideband MIMO M2M RSGBSM with respect to the frequency-selectivity. The proposed wideband reference model is validated by observing a good match between some statistical properties of the theoretical model and available measurement data. From the wideband reference model, we further design new wideband deterministic and stochastic SoS simulation models. The proposed wideband simulators can be easily reduced to narrowband ones. The utilities of the newly derived narrowband and wideband simulation models are validated by comparing their statistical properties with those of the corresponding reference models. The proposed channel reference models and simulators are expected to be useful for the design, testing, and performance evaluation of future MIMO cellular and M2M communication systems.Scottish Funding Counci

    A Study of 2D Non-Stationary Massive MIMO Channels by Transformation of Delay and Angular Power Spectral Densities

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    Novel 3D Non-Stationary Wideband Models for Massive MIMO Channels

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