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The fifth-generation (5G) wireless network has received a lot of attention from both academia and industry with many reported efforts. Multiple-input-multiple-output (MIMO) is the most promising wireless access technology for next-generation networks to provide high spectral and energy efficiency. For handheld devices such as smartphones, 2×2 MIMO antennas are currently employed in 4G systems and it is expected to employ a larger number of elements for 5G mobile terminals. Placing multiple antennas in the limited space of a smartphone PCB poses a significant challenge. Therefore, a new design technique using dual-polarized antenna resonators for 8×8 MIMO configuration is proposed for sub 6 GHz 5G applications. The proposed MIMO configuration could improve the channel capacity, diversity function, and multiplexing gain of the smartphone antenna system which makes it suitable for 5G applications. Different types of new and compact diversity MIMO antennas with Patch, Slot, and Planar inverted F antenna (PIFA) resonators are studied for different candidate bands of sub 6 GHz spectrum such as 2.6, 3.6, and 5.8 GHz. Unlike the reported MIMO antennas, the proposed designs provide full radiation coverage and polarization diversity with sufficient gain and efficiency values supporting different sides of the mainboard. Apart from the sub 6 GHz frequencies, 5G devices are also expected to support the higher bands at the centimeter/millimeter-wave spectrums. Compact antennas can be employed at different portions of a smartphone board to form linear phased arrays. Here, we propose new linear phased arrays with compact elements such as Dipole and Quasi Yagi resonators for 5G smartphones. Compared with the recently reported designs, the proposed phased arrays exhibit satisfactory features such as compact size, wide beam steering, broad bandwidth, end-fire radiation, high gain, and efficiency characteristics. The proposed 5G antennas can provide single-band, multi-band, and broad-band characteristics with reduced mutual coupling function. The fundamental characteristics of the 5G antennas are examined using both simulations and measurements and good agreement is observed. Furthermore, due to compact size and better placement of elements, quite good characteristics are observed in the presence of the user and the smartphone components. These advantages make the proposed antennas highly suitable for use in 5G smartphone applications.

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increase energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices cause a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS.