Training in Massive MIMO Systems

Abstract

Massive multiple-input multiple-output (MIMO) systems have been gaining interest recently due to their potential to achieve high spectral efficiency [1]. Despite their potential, they come with certain issues such as pilot contamination. Pilot contamination occurs when cells simultaneously transmit the same pilot sequences, creating interference. Unsynchronizing the pilots can reduce pilot contamination, but it can produce data to pilot interference. This thesis investigates the impact of pilot contamination and other interference, namely data to pilot interference, on the performance of finite massive MIMO systems with synchronized and unsynchronized pilots. Two unsynchronized pilot schemes are considered. The first is based on an existing time-shifted pilot scheme, where pilots overlap with downlink data from nearby cells. The second timeshifted method overlaps pilots with uplink data from nearby cells. Results show that if there are small numbers of users, the first time-shifted method provides the best sum rate performance. However, for higher numbers of users, the second time-shifted method provides better performance than the other methods. We also show that time-synchronized pilots are not necessarily the worst case scenario in terms of sum rate performance when shadowing effects are considered. The wireless channel can be time and frequency varying due to the Doppler effect from mobile user equipment (UE) and a multipath channel. These variations can be simulated by using a selective channel model, where the channel can vary within the coherence block in both time and frequency domains. The block fading channel model approximates these variations by assuming the channel stays constant within a coherence block, but changes independently between blocks [2]. Due to its simplicity, the block fading model is widely used in massive MIMO studies [3–8]. Our research compares the impact of block fading and time-selective fading channel models in massive MIMO systems. To achieve this, we derive a novel closed form sum rate expression for time-selective channels. Results show that there are significant differences in sum rate performance between these models. In addition to time variation from Doppler effect, the channel can also experience frequency variation due to delay spread from multipath signal propagation. The combination of time and frequency selective channels can be described as a doubly-selective channel. Hence, the sum rate expression for time-selective channels can also be extended