Jitendra M Shah

https://doi.org/10.64823/ijter.2505010

This paper presents a comparative study of various hybrid multilevel inverter (HMLI) configurations with respect to their output voltage levels and overall performance. The focus is on harmonic elimination in HMLIs to reduce the total harmonic distortion (THD) of the voltage applied to the load, thereby improving power quality [1,2]. Different HMLI topologies are analyzed and compared, emphasizing their effectiveness in minimizing harmonics. By dividing the switching process into high- and low-frequency components, the proposed approach aims to enhance converter efficiency while simultaneously reducing size and cost [3]. Furthermore, this study introduces the performance analysis of a novel hybrid multilevel inverter topology, referred to as SHMLI, employing various pulse width modulation (PWM) strategies. The PWM techniques investigated include multicarrier phase disposition (PD) and phase shift modulation methods, which have been demonstrated to improve switching performance and harmonic profile [4,5]. All simulations and analyses are conducted using MATLAB-SIMULINK to validate the theoretical findings.

https://doi.org/10.64823/ijter.2505011

Massive multiple input multiple output (MIMO) is an important technology to 5G and beyond wireless communication systems because it is capable of improving the spectral efficiency, energy efficiency, and link reliability. However, precise channel state information (CSI) acquisition is a key requirement for obtaining these benefits. Channel estimation in Massive MIMO is a challenging task especially because of the problem of pilot contamination in which pilot signals from neighboring cells interfere and degrades estimation quality. This paper explores channel estimation techniques and pilot contamination mitigation strategies in Massive MIMO networks from both foundational and emerging perspectives. We describe how different estimation methods are implemented, including least squares (LS), minimum mean square error (MMSE), and compressed sensing (CS) based ones. Moreover, we investigate the effect of the pilot contamination and discuss mitigation approaches, including optimization of pilot reuse, advanced precoding, and deep learning-based approaches. Finally, we highlight open research challenges and future directions.