Massive multiple-input multiple-output (MIMO) is still valid as an important system to increase performance of fifth generation (5G) and beyond wireless communication technologies. Spectrum efficiency (SE), high data rate and energy efficiency (EE) are among these performances. Recently, due to the increase in interconnected devices, the spread of internet of things (IoT) systems and the limited resources, various performance improvements have become inevitable. It is seen that there are various studies to realize such improvements with Massive MIMO. There are many researches especially for spectrum efficiency and energy efficiency. Because issue of energy and bandwidth problem are among the issues that need to be solved and developed first. In recent years, it is understood that power allocation algorithms have been focused on solving these two problems. In this study, researches on power allocation algorithms for MIMO systems are examined. The main points of the studies are emphasized. In addition, the comparison of three different power allocation algorithms, which will be among the basic power allocation algorithms, are carried out in terms of spectrum efficiency.

In this paper, we propose a distinctive pilot power allocation algorithm to maximize the sum rate in a multi-cell multi-user massive multiple-input multiple-output (MIMO) system. The algorithm optimizes pilot powers by polarizing the corresponding SINR values. In order to polarize SINRs, the difference between average SINR per cell and individual SINR is calculated for each user of the whole cells. The exponential form of the difference is used in the calculations of the weights for power allocation. New power values are obtained in proportion to these weights. Therefore, the power budget is utilized more efficiently thanks to these optimized power values. The efficiency of the algorithm is measured using the cumulative average SINR of the simulation system. Furthermore, equal pilot power allocation (EPPA) and water-filling pilot power allocation (WF-PPA) schemes are also implemented to compare the performances under the same simulation environments. A vast number of simulations results prove that our proposed heuristic approach is more efficient than EPPA and WF-PPA methods.

Spectrum efficiency studies of Massive MIMO systems have continued and still have not been fully explored in the literature. Therefore, the spectrum efficiency definition of a particular user in a cell in a Massive MIMO network is expressed in this paper. In addition, the uplink spectrum efficiency expressions for the Rayleigh fading are included. The Monte Carlo simulations are performed to verify these expressions. Due to the expectation of reaching to a thousand antennas together with the millimetre wave structure in the next years, in this study, it is contributed to the literature by explaining how to select the pilot reuse factor. The realization of this contribution is based on Zero Forcing (ZF) and Maximum Ratio Combining (MRC) schemes. The results of this study are useful for optimal design conditions, such as the number of antennas on the base station and pilot reuse factor selection for the next generation networks in order to obtain spectrum efficiency in Massive MIMO systems.

Suppose that a multi-user multiple-input multiple-output (MIMO) system is developed from scratch to equally envelop a defined region with optimal spectrum efficiency (SE) in next generation wireless communication systems such as sixth-generation (6G) and beyond networks. What are the ideal number of user terminals U, number of base stations antennas, and used pilot reuse factor? The purpose of this paper is to address this specific issue. Three interference levels are specified for this. Based on these interference levels, signal-to-interference-and-noise ratios (SINRs) are extracted. Closed-form spectrum efficiency equations are thus obtained. As a function of the base station (BS) antenna number, simulations are carried out considering multiple pilot reuse factors and diverse processing schemes such as Maximum Ratio Combining (MRC) and Zero-Forcing (ZF). From the results, it is understood that U varies according to the processing schemes. Therefore, evaluating the results considering the fixed number of users K will not give an accurate result in determining the design parameters for the next generation communication systems. In general, these results are useful statements that spectrum efficiency is maximized when the ideal number of users U is used in multi-cell systems.

In this paper, we propose a novel pilot power allocation method that focuses on the maximization of the energy efficiency. The core algorithm of this method, which is a dynamic approach that takes into account signal-to-interference-plus-noise ratio (SINR), is called pilot power allocation polarizing SINRs (PS-PPA). The aim is to maximize the energy efficiency of the system along with the proposed pilot power allocation method using this algorithm in a multi-cell multi-user massive multiple-input multiple-output (MIMO) system. The algorithm determines difference between average SINR per cell and SINRs of users individually, during the scan of the whole cells sequentially. Therefore, it always updates the allocation for the latest SINR of users in power updates to improve the energy efficiency of the system. In power updates, PS-PPA calculates weights using an exponential function of the SINR difference. This weighting function is defined for each real number, so it can always result in a specific number. In addition, the weighting function is performed in the [ρ min ,ρ max ] range where the power values are predefined. The energy efficiency of the system is measured in a number of simulations by calculating the average SINR per cell. Furthermore, all these performance results are obtained for equal pilot power allocation (EPPA) and water-filling pilot power allocation (WF-PPA) schemes. As a result of simulation results, proposed pilot power allocation method has proven to be more superior than EPPA and WF-PPA methods.

Wireless Sensor Networks (WSNs) based on Internet of Things (IoT) applications are increasing day by day. These applications include healthcare, infrastructure monitoring, smart homes, wearable devices and smart cars. However, considering the fact that many different application areas will emerge in next generation wireless communication systems, efficient use of frequency spectrum is important. Because the whole frequency spectrum is now very crowded, it is important to ensure maximum spectrum efficiency for effective WSNs based on IoT. This study sought to determine which mode more effectively achieves spectrum efficiency for the performance of effective IoT systems under given conditions with respect to the length of the pilot sequence, Time Division Duplexing (TDD) or Frequency Division Duplexing (FDD). The results were obtained by Monte Carlo simulations. To the best of our knowledge, a study of effective mode selection analysis for spectrum efficiency in IoT based systems has not been available in the literature yet. The results of this study are useful for determining the appropriate design conditions for WSNs based on IoT.

In wireless communication systems, the improvement of data rate and quality is a priority as a result of users' requests. During the improvement of these priority situations, there will also be a number of losses in the signals. It is known that the techniques used in large systems to solve such problems are not efficient in small systems like modem. Therefore, when using a smaller system such as a modem, the recommended techniques will have to be different. Multimode antenna designs will be an important alternative for next generation wireless communication systems especially for MIMO systems due to the physical advantages of small antenna structures. In this study, MIMO channel structure is shown and performance analysis and theories of compact micro-strip and reconfigurable multiple antenna designs used for the development of MIMO communication systems are mentioned. Index Terms-Compact Multimode Micro-strip Antennas, MIMO, Reconfigurable Multiple Antenna Systems. I. INTRODUCTION OWADAYS, great advances are observed with the developing technology in wireless communication field. At the same time, wireless communication is widely used in many industrial environments. The wireless communication system is simply an event that the signal is transmitted from the transmitter to the receiver. The signal between the transmitter and the receiver is transmitted to the user through source coding, channel coding, modulator, demodulator, channel decoding and source decoding [1]. In wireless communication systems, improving data rate and quality performances is a priority as a result of users' requests.