Multiuser Transmit and Receive Beamforming for One-dimensional Signalling
Internet of things (IoT), which enables connectivity of billions of devices to the Internet, is expected to be the next revolution in wireless ecosystem. Due to lack of available spectrum, it is imperative for wireless technologies to reuse spectrum by simultaneously providing service to multiple devices at the same frequency. Existing wireless technologies are designed to support a few simultaneous users with high data rates. The IoT, on the other hand, requires support for many users each having a very low data rate. The main focus of this dissertation is to support, at physical layer, massive deployment of low data rate devices by means of user selection, transmission, and receive techniques. This dissertation proposes user selection algorithms capable of selecting twice as many users as the number of transmit antennas in a broadcast channel by employing the concept of orthogonality in low-pass representation of signals. Moreover, we propose several reliable multiuser receive beamforming techniques, specific to low-cost devices with low data rate one-dimensional signalling by signal processing based on minimization of error probability. This approach leads to introduction of a new metric called signal minus interference to noise ratio (SMINR). Maximization of this metric results in a low-complexity closed-form solution for the beamforming weights of each user with reliable performance. This dissertation also proposes several reliable multiuser transmit precoding techniques, specific to low data rate one-dimensional signalling, that can support more users than the number of transmit antennas by employing minimum-probability-of-error as well as widely-linear based signal processing. The final contribution of this thesis is employing widely linear precoding for simultaneously transferring information and power in wireless broadcast channels. From a more general perspective, this dissertation addresses scenarios where bandwidth is scarce compared to the density of available users and proposes signal processing techniques to enable higher network throughput. In particular, it is shown that grater throughput may be achieved and the number of users can be increased in a multiuser communications system by using either widely linear or minimum probability of error based processing of one-dimensionally modulated signals compared to linear processing of both one-dimensionally and two-dimensionally modulated signals.
Request an alternative formatIf you require this document in an alternate, accessible format, please contact the Queen's Adaptive Technology Centre
The following license files are associated with this item: