상세정보

Recently, due to growing demands for mobile traffic, higher mobile communication capacity
is needed. Following the current trend, the next generation communication systems will
adopt various new technologies. First, using heterogeneous network composed of macrocells,
pico-cells, and femto-cells, higher area spectral density and extension of coverage are
expected. It also has come into the spotlight that devices do not connect a central node and directly
communicate with each other, called by device-to-device (D2D), machine-to-machine
(M2M), and internet of things (IoT). Furthermore, to increase communication capacity, new
antenna techniques such as massive multiple-input and multiple-output (massive MIMO),
coordinated multi-point (CoMP), and 3D beam forming and new radio access technologies
such as non-orthogonal multiple access (NOMA) are introduced.
These new technologies have changed physical environments of the communication systems.
Due to a saturation of frequency, millimetre-wave band has come to a new candidate
frequency band for the next generation communication systems. In the millimetre-wave frequency
band, diffraction loss is greatly increased and propagation paths by reflection are
dominant. In the millimetre-wave frequency band, the heights of base station (BS) antennas
become lower to secure propagation paths by reflection. In the millimetre-wave frequency
band, as 3D beam forming is used to overcome large path loss, an analysis of dominant
propagation path is also important. In D2D communication environments, as the heights of
transmit antenna and receiving antenna are lower than adjacent obstacles, the fading effect
becomes larger.
Not only changes of physical environments but computer simulation becomes complicated.
The numbers of mobile stations (MSs) and BSs become largely increased. As an
amount of computation of simulation is proportional to the number of pairs of MS and BS,
the computational load becomes serious. As simulation methods and channel models also become
complicated for realistic simulation, the complexity of simulation becomes increased.
So, the efficient implementation and verification of simulation come into the picture.
This thesis introduces wireless channel models considering the environments and dominant
propagation paths in preparation for the changes of physical environments. For the modeling,
dominant propagation path scenarios are analyzed based on geometric optics and ray
tracing simulation. The methodologies of implementation and verification are also proposed
for efficient and accurate simulation of the next generation communication systems.

Chapter 1 Introduction
1.1 Background
1.2 Contributions
Chapter 2 Path Loss Models for the Next Generation Communication Systems
2.1 Introduction
2.2 Ray Tracing Simulation for Channel Modeling
2.3 Path Loss Model for Propagation over Rooftops
2.3.1 Background and history of ITU-R Recommendation P.1411 Revision
2.3.2 Proposed Path Loss Model
2.3.3 Verification of the Proposed Model
2.4 Path Loss Model for Propagation within Street Canyons
2.4.1 Path Loss Model of ITU-R Recommendation P.1411
2.4.2 Proposed Path Loss Model
2.4.3 An Example Implementation of the Proposed Model
2.5 Summary
Chapter 3 An Efficient Implementation of the Channel Model
3.1 Introduction
3.2 Preliminaries
3.2.1 ITU-R Channel Model
3.2.2 ITU-R Channel Model Extension to D2D Channel
3.3 The Doppler Response-Based Fast Fading Channel Generation Mehthod
3.4 Experiment Results
3.5 Summary
Chapter 4 Verification Methodology for the Channel Model
4.1 Introduction
4.2 Functional Blocks for the Small Scale Parameters’ Generation
4.3 Verification with a Reference Code
4.4 Summary
Chapter 5 Conclusion
Bibliography