Power Optimization in MIMO Systems: SVD Decomposition and Water-Filling Algorithm Implementation

Power optimization in MIMO systems represents a critical research domain in wireless communications. The core methodology involves employing Singular Value Decomposition (SVD) to diagonalize the channel matrix, followed by water-filling algorithms to dynamically allocate power across different transmit antennas. This optimization framework typically includes calculating channel eigenvalues via SVD decomposition and implementing iterative water-filling algorithms that assign higher power to stronger subchannels. Through optimized power distribution, systems can achieve maximum channel capacity while minimizing inter-antenna interference and bit error rates. Key implementation steps involve mathematical operations for eigenvalue computation and threshold-based power allocation algorithms. Consequently, addressing power optimization challenges in MIMO configurations is fundamental for enhancing overall wireless communication system performance, particularly in capacity expansion and coverage improvement scenarios.