Linear Detection and Circuit Structure Based on ZF, MMSE Matrix Iteration and Operations

The Multiple-Input Multiple-Output (MIMO) technology substantially boosts the reliability and data transfer rates of communication links by enabling the parallel transmission of multiple data signals over the same frequency bandwidth, utilizing multiple transmit and receive antennas.Despite these enhancements, traditional MIMO systems are approaching their theoretical throughput limits, which underscores the need for developing new algorithms to tackle computational complexity.This paper categorizes the primary technical approaches into three types: iterative approximation methods, matrix operation-based methods, and the emerging Joint channel Estimation and Data detection (JED) algorithms.It delves into the Neumann series approximation for efficient matrix inversion in large-scale MIMO systems, the Gauss-Seidel iterative approach for soft-output detection, and LDLT decomposition-based algorithms for matrix inversion efficiency. Additionally, the paper emphasizes the JED algorithm, such as PROX, which presents a low-complexity solution for large Single-Input Multiple-Output (SIMO) wireless systems.