Energy and spectrum efficient future wireless networks

Future Wireless Networks (FWN) will be heterogeneous and dynamic networks comprising of different wireless technologies such as cellular technologies; (LTE and LTE-A), Wireless Local Area Networks (WLAN), WiMAX and Wireless Sensor Networks (WSN). They are expected to provide high data rate in excess of I Gbit/s in a variety of scenarios involving mobile users. A number of technologies such as; Multiple Input Multiple Output (MIMO) antennas, Cognitive Radio (CR), Orthogonal Frequency Division Multiple Access (OFDMA), Dynamic Spectrum Access (DSA), Cooperative Communication, white space and 60GHz transmission have been identified as enablers of FWN. However, two critical challenges still facing the realization of the targets of FWNs are enormous energy consumption and limited spectrum bands useful for wireless communications. This thesis has focused on two enabling technologies in future wireless networks; MIMO antennas and Cognitive Radio technology. These two technologies have been chosen as they have the capability to tackle both energy optimization and spectrum scarcity challenges in FWN. This thesis has investigated energy and spectrum efficiency in MIMO antenna technology and has used the Long Term Evolution (LTE); which is positioned to be a strong player amongst cellular technologies in FWN as a case study. The work has presented adapted energy efficiency metrics which serves as a basis for comparison and has shown various relationships between the numbers of transmit and receive antennas, the feedback information and the energy and spectral efficiency of various MIMO schemes in LTE. This thesis has also investigated energy and spectrum efficiency in Cognitive Radio technology. In dealing with energy efficiency in cognitive radio environment, the options of making CR operations more energy efficient and an analytical evaluation of energy consumed at different stages of secondary spectrum usage have been explored. In dealing with spectrum efficiency in cognitive radio environment, this work has investigated and proposed a spectrum decision and allocation scheme whose performance evaluation confirms it has the ability to offer better utilisation of spectrum holes and offer better spectral efficiency.