Personal wireless communications networks have flourished over the last decade as advances in
digital cellular technology have made them more accessible to the general public. Third
Generation Cellular Communication systems based on code division multiple access (CDMA)
as the multiple access technique, show great scope for improvement in terms of capacity,
through the use of advanced signal processing techniques. Two of the leading areas that
encompass these techniques are space-time processing (smart antennas) and multiuser detection
(MUD). Space-time-MUD (ST-MUD) is a relatively new field that hopes to bring together these
two techniques. The focus of this thesis is ST -MUD in the context of a multi-carrier direct
sequence CDMA (MC-DS-CDMA) communications system, which is one of the adopted
multiple access techniques for the upcoming third generation cellular communications systems.
The concepts of MUD and smart antennas are discussed, and their performance enhancing
capabilities are demonstrated. The use of vector channel models and their role in modelling the
propagation phenomena of the communications channel in terms of the space, time and
frequency domains is also illustrated. A ST-MUD receiver architecture is presented, and the
performance of the architecture with a minimum mean square error (MMSE) decision criterion
is analysed in a frequency selective Rayleigh fading channel. The analysis results are verified
via simulation. Three subspace MUD techniques are adapted for ST -MUD, and the joint space-frequency-
multi path MMSE solution on these subspaces is given. Simulation results are used to
quantify their relative performance. The relevance and applications of the subspace techniques
are elaborated. / Thesis (M.Sc.Eng.)-University of Natal, Durban, 2001.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/5417 |
| Date | January 2001 |
| Creators | Whitehead, James Bruce. |
| Contributors | Takawira, Fambirai. |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0021 seconds