A review on Beamspace Channel Estimation Algorithms in Wireless Communication
Smita G. Daware, Pinalkumar J. Engineer, Shweta N. Shah · 2023
Over the past decade, the multi-user multiple-input and multiple-output (MU-MIMO) technology has made significant advancements. One area of particular interest is Massive MIMO, which has demonstrated the benefits of installing numerous antennas at the base station. In comparison to traditional channel estimate methods, beamspace channel estimation algorithms offer several advantages, including reduced complexity and increased accuracy. These algorithms can be further improved by incorporating structured sparsity models and compressed sensing methods. However, there are still challenges that need to be addressed in beamspace channel estimation algorithms. Utilizing multiple antennas provides advantages in terms of gain, signal-to-noise ratio (SNR), coverage, capacity, transmission throughput, and reduced latency. This study provides an overview of the channel model, methodologies, and channel estimate algorithms, offering a comprehensive analysis of current developments in beamspace channel estimation techniques. Beamspace channel estimation is a critical component of contemporary wireless communication systems that utilize multi-antenna arrays. The main focus of this paper is to highlight open research issues and potential prospects for the discipline.