94 research outputs found
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
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
- …