Beam Space Hybrid Precoding for Rayleigh Fading MIMO-OFDM Systems Using Compressive Sensing and SVD

Beam space hybrid precoding techniques for MIMO-OFDM systems are investigated in this work. The system uses beam space transformation, which lowers complexity and improves signal processing efficiency, in conjunction with singular value decomposition (SVD) for hybrid precoding, which boosts data rate by minimizing interference. Least Absolute Shrinkage and Selection Operator (LASSO) is used for channel estimation to give a more accurate estimate of the sparse channel with fewer observations. Simulations are developed for both fully and partial connected hybrid beamforming techniques. The bit error rate (BER) and spectral efficiency of the system are evaluated under the influence of colored noise that better simulates real-world interference. Time complexities are also calculated. Simulation results show that beam space hybrid precoding performs well at minimal complexity over a broad range of signal-to-noise ratios (SNRs) and requires execution time much less than fully digital beamforming techniques.