Macrodiversity MIMO Transceivers
Thesis DisciplineElectrical Engineering
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
In wireless systems, radio signals are corrupted due to fading, interference and noise. In order to handle the effects of fading and interference, modern systems employ various techniques including multi-antenna transceivers. Initially, multi-antenna systems were proposed only for point-point communication. More recently, multi-antenna transceivers have been proposed for multiuser (MU) wireless systems. There are various topologies in which multi-antenna transceivers can be used in a multiuser wireless environment. Among them, macrodiversity is an important concept driven by many scenarios, including base station cooperation, coordinated multipoint (CoMP) transmission and network multiple input multiple output (MIMO). A communication system where antenna elements at both source and receiver are widely (geographically) separated is described as a macrodiversity communication system. For these macrodiversity systems, every link may have a different average signal to noise ratio (SNR) since the sources and the receive antennas are all in different locations. This variation in average SNR across the links makes the performance analysis of such systems more complex. For this reason, most of the results currently available are based on simulation. However, the value of analytical results can be immense for efficient computation and optimized operation. Therefore, in this thesis we present a comprehensive, and rigorous analytical investigation of various aspects of multiuser macrodiversity MIMO systems. Two main aspects of macrodiversity MIMO systems are considered: the multiple access channel (MAC) and uplink user scheduling. In the earlier chapters of the thesis, we investigate the performance of uplink transmission employing multi-antenna transmitters and receivers. We analyze the signal-to-interference plus noise ratio (SINR) performance, symbol error rate (SER) and ergodic sum capacity etc. In a later chapter, we consider multiuser scheduling issues in macrodiversity multiuser MIMO systems. The primary emphasis is on the MIMO-MAC where we present some systematic performance metrics and approaches to multiuser scheduling which only require the long term channel state information (CSI). These methods provide a double advantage over scheduling using instantaneous CSI. First, the computational burden is lower and secondly, the delay between obtaining and using channel estimation is reduced.