Investigation of spectrum efficiency and power allocation for massive MIMO multi-cell wireless communication systems

In the next generation wireless communication systems, providing high spectrum efficiency (SE) service is among the most important targets due to the spectrum occupancy problem. Hereby, this thesis focuses on high SE gain in massive MIMO communication systems. In this context, different scenario analyzes that provide high SE performance using Maximum Ratio Combining (MRC) or Zero Forcing (ZF) with either a fixed or different length pilot sequence with Time Division Duplex (TDD) or Frequency Division Duplex (FDD) mode combinations are presented to guide the researchers. In particular, it has been understood that the number of antennas in the base station (BS) and the pilot reuse factor in massive MIMO systems, as well as the ideal number of user terminals (U), are important for efficient resource allocation on the basis of SE. Within this scope, closed-form SE equations with signal-to-noise-and-noise ratios (SINR) based on three interference levels are obtained later in the thesis. Simulations are performed considering multiple pilot reuse factors and various processing schemes such as MRC and ZF as a function of the number of antennas in the BS. From the results, it was understood that U varies according to the processing schemes. In general, these results are presented as a contribution to the literature, with the maximum utilization of SE in multicellular systems, considering the U obtained in this thesis. Thus, in heterogeneous networks, the input data is presented to the network switching algorithms for routing the user to another network that wants to be included in a cell that reaches the ideal U number in terms of SE. Also, in this thesis, a novel pilot power allocation algorithm is proposed to maximize energy efficiency (EE) in massive MIMO systems. The algorithm optimizes the pilot powers by polarizing the corresponding SINR values. It has been observed that the total power budget is reduced even more thanks to these optimized power values. The performance of the algorithm was measured using the cumulative distribution function (CDF)-EE outputs of the simulation system. In addition, equal pilot power allocation (EPPA) and water fill pilot power allocation (WF-PPA) schemes have also been applied to compare performances under the same simulation environments, and our proposed heuristic approach has proven to be superior to EPPA and WF-PPA methods.