411 research outputs found
A WINNER+ Based 3-D Non-Stationary Wideband MIMO Channel Model
In this paper, a three-dimensional (3-D) non-stationary wideband
multiple-input multiple-output (MIMO) channel model based on the WINNER+
channel model is proposed. The angular distributions of clusters in both the
horizontal and vertical planes are jointly considered. The receiver and
clusters can be moving, which makes the model more general. Parameters
including number of clusters, powers, delays, azimuth angles of departure
(AAoDs), azimuth angles of arrival (AAoAs), elevation angles of departure
(EAoDs), and elevation angles of arrival (EAoAs) are time-variant. The cluster
time evolution is modeled using a birth-death process. Statistical properties,
including spatial cross-correlation function (CCF), temporal autocorrelation
function (ACF), Doppler power spectrum density (PSD), level-crossing rate
(LCR), average fading duration (AFD), and stationary interval are investigated
and analyzed. The LCR, AFD, and stationary interval of the proposed channel
model are validated against the measurement data. Numerical and simulation
results show that the proposed channel model has the ability to reproduce the
main properties of real non-stationary channels. Furthermore, the proposed
channel model can be adapted to various communication scenarios by adjusting
different parameter values
A General 3D Non-Stationary 5G Wireless Channel Model
A novel unified framework of geometry-based stochastic models (GBSMs) for the
fifth generation (5G) wireless communication systems is proposed in this paper.
The proposed general 5G channel model aims at capturing small-scale fading
channel characteristics of key 5G communication scenarios, such as massive
multiple-input multiple-output (MIMO), high-speed train (HST),
vehicle-to-vehicle (V2V), and millimeter wave (mmWave) communication scenarios.
It is a three-dimensional (3D) non-stationary channel model based on the WINNER
II and Saleh-Valenzuela (SV) channel models considering array-time cluster
evolution. Moreover, it can easily be reduced to various simplified channel
models by properly adjusting model parameters. Statistical properties of the
proposed general 5G small-scale fading channel model are investigated to
demonstrate its capability of capturing channel characteristics of various
scenarios, with excellent fitting to some corresponding channel measurements
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
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
MASSIVE MIMO FOR HIGH-SPEED TRAIN COMMUNICATION SYSTEMS
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
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