2,152 research outputs found

    MASSIVE MIMO FOR HIGH-SPEED TRAIN COMMUNICATION SYSTEMS

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    With the current development in wireless communications in high-mobility systems such as high-speed train (HST), the HST scenario is accepted as among the different scenarios for the fifth-generation (5G). Massive Multiple-Input-Multiple-Output (MIMO) systems, which are equipped with tens or hundreds of antennas has become an improved MIMO system which can assist in achieving the ever-growing demand of data for 5G wireless communication systems. In this study, the associated 5G technologies, as well as the equivalent channel modeling in HST settings and the challenges of deploying massive MIMO on HST, was investigated The channel model was modeled using the WINNER II channel model. With regrads, the proposed non-stationary IMT-A massive MIMO channel models, the essential statistical properties such as the spatial cross-correlation function (CCF), local temporal autocorrelation function (ACF) of the massive MIMO channel model using different propagation scenarios such as open space, viaduct and cutting was analyzed and investigated. The results from the simulations were compared with the analytical results in other to show that the statistical properties vary with time as a result of the non-stationarity of the proposed channel model. The agreement between the stationary interval of the non-stationary IMT-A channel model and the HST under different propagation scenarios shows the efficiency of the proposed channel model. Based on findings; the impact of the deployment of a large antenna on the channel capacity should be thoroughly investigated under different HST propagation scenario. Also, more HST train propagation scenarios such as the tunnel, hilly terrain, and the station should be considered in the non-stationary IMT-A massive MIMO channel models

    A Non-Stationary MIMO Channel Model for High-Speed Train Communication Systems

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    Abstract—This paper proposes a non-stationary wideband geometry-based stochastic model (GBSM) for multiple-input multiple-output (MIMO) high-speed train (HST) channels. The proposed model has the ability to investigate the non-stationarity of HST environment caused by the high speed movement of the receiver. Based on the proposed model, the space-time-frequency (STF) correlation function (CF) and STF local scattering function (LSF) are derived for different taps. Numerical results show the non-stationarity of the proposed channel model. I

    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

    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

    Performance investigation of spatial modulation systems under realistic channel models

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    In order to fulfil the explosive demand for convenient wireless data access, novel wireless technologies such as the multiple-input-multiple-output (MIMO) have widely been used to improve the link reliability and capacity of wireless communication systems. In recent years, a new MIMO technology named the spatial modulation (SM) has attracted signi cant research interest due to its reported enhancement on the system performance with the reasonable system complexity. Before a new technology comes into real use, it is necessary to comprehensively evaluate its performance under different scenarios. In this thesis, we investigate the performance of SM systems under some important realistic scenarios for future wireless communications, such as the vehicle-to-vehicle (V2V), the high-speed train (HST), and the massive MIMO scenarios. Firstly, the bit error rate (BER) performance of SM systems under a novel threedimensional (3D) geometry based stochastic model (GBSM) for V2V MIMO channels is investigated by both theoretical analysis and system simulations. The impacts of vehicle tra c density (VTD), Doppler effect, and 3D feature on the BER performance of SM systems are thoroughly studied. In addition, other MIMO technologies, such as the vertical Bell Labs layered space-time (V-BLAST), the Alamouti scheme are compared with SM under different simulation settings. Secondly, the BER performance of SM systems is studied under a non-stationary wideband HST GBSM considering the non-ideal channel estimation case. The timevarying behaviour of the channel and its impact on the performance of SM systems are comprehensively investigated. The accurate theoretical BER expression of SM systems under a non-stationary wideband HST channels with non-ideal channel estimation is derived. A novel statistic property named stationary interval in terms of the space-time correlation function (STCF) is introduced in order to clearly explain all theoretical and simulation results. Thirdly, the performance of SM systems is evaluated under a Kroneck-based massive MIMO channel model. As a massive MIMO system employs large numbers of antennas, antenna elements are distributed over a wide range. Thus, different antenna elements may observe different sets of clusters. How this phenomenon affects the performance of SM systems is investigated by considering a survival probability of clusters, which abstracts the birth-death process of each cluster in the channel model. Moreover, the performance of SM systems is also compared with that of other MIMO technologies under the massive MIMO channel model. In summary, all research works in this thesis have considered realistic MIMO channel models, which are meaningful for the test, performance evaluation, and implementation of SM technology for future advanced wireless communications systems

    Novel 3D Non-Stationary mmWave Massive MIMO Channel Models for 5G High-Speed Train Wireless Communications

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