Optimizing Massive MIMO : Precoder Design and Power Allocation

Abstract

The past decades have seen a rapid growth of mobile data traffic, both in terms of connected devices and data rate. To satisfy the ever growing data traffic demand in wireless communication systems, the current cellular systems have to be redesigned to increase both spectral efficiency and energy efficiency. Massive MIMO (Multiple-Input-Multiple-Output) is one solution that satisfy both requirements. In massive MIMO systems, hundreds of antennas are employed at the base station to provide service to many users at the same time and frequency. This enables the system to serve the users with uniformly good quality of service simultaneously, with low-cost hardware and without using extra bandwidth and energy. To achieve this, proper resource allocation is needed. Among the available resources, transmit power beamforming are the most important degrees of freedom to control the spectral efficiency and energy efficiency. Due to the use of excessive number of antennas and low-end hardware at the base station, new aspects of power allocation and beamforming compared to current systems arises.In the first part of the thesis, new uplink power allocation schemes that based on long term channel statistics is proposed. Since quality of the channel estimates is crucial in massive MIMO, in addition to data power allocation, joint power allocation that includes the pilot power as additional variable should be considered. Therefore a new framework for power allocation that matches practical systems is developed, as the methods developed in the literature cannot be applied directly to massive MIMO systems. Simulation results confirm the advantages brought by the the proposed new framework.In the second part, we introduces a new approach to solve the joint precoding and power allocation for different objective in downlink scenarios by a combination of random matrix theory and optimization theory. The new approach results in a simplified problem that, though non-convex, obeys a v simple separable structure. Simulation results showed that the proposed scheme provides large gains over heuristic solutions when the number of users in the cell is large, which is suitable for applying in massive MIMO systems.In the third part we investigate the effects of using low-end amplifiers at the base stations. The non-linear behavior of power consumption in these amplifiers changes the power consumption model at the base station, thereby changes the power allocation and beamforming design. Different scenarios are investigated and results show that a certain number of antennas can be turned off in some scenarios.In the last part we consider the use of non-orthogonal-multiple-access (NOMA) inside massive MIMO systems in practical scenarios where channel state information (CSI) is acquired through pilot signaling. Achievable rate analysis is carried out for different pilot signaling schemes including both uplink and downlink pilots. Numerical results show that when downlink CSI is available at the users, our proposed NOMA scheme outperforms o...

Blind Massive MIMO Base Stations : Downlink Transmission and Jamming

“…To derive the bound in (35) it was assumed that the  allocates the same amount of power to all users, which is not optimal in general. Power controlor how to distribute the power among the users-can greatly impact the system performance both in the uplink and in the downlink [59][60][61]. One popular method of power control in massive  is the so-called max-min fairness power control, in which the power is allocated in such a way to make the effective  the same for all users [6,7,62].…”