Multiple-Input Multiple-Output (MIMO) Systems with Adaptive OFDM Modulation

This project demonstrates the implementation of Orthogonal Frequency Division Multiplexing (OFDM) with adaptive modulation techniques in Multiple-Input Multiple-Output (MIMO) communication systems. The simulation and analysis are structured into two complementary phases.

In the initial phase, we implement a variable-rate variable-power M-QAM (Multiple Quadrature Amplitude Modulation) scheme within a Single-Input Single-Output (SISO) OFDM framework. This implementation typically involves channel state estimation algorithms and dynamic bit-loading algorithms that adjust modulation order and transmit power per subcarrier based on real-time SNR measurements. The code structure would include modules for channel estimation, SNR calculation, and adaptive modulation selection tables.

The second phase extends adaptive modulation to general MIMO systems through Singular Value Decomposition (SVD) based channel decomposition. The implementation involves calculating the SVD of the channel matrix H = UΣV*, where U and V are unitary matrices and Σ contains the singular values. This decomposition transforms the MIMO channel into parallel independent subchannels, each with a gain corresponding to a singular value. The adaptive modulation algorithm then independently optimizes the modulation scheme and power allocation for each subchannel, typically using water-filling power allocation algorithms and rate adaptation based on subchannel quality.

The complete simulation includes performance metrics such as bit error rate (BER) analysis, spectral efficiency calculations, and comparative studies between fixed and adaptive modulation schemes. The MATLAB/Simulink implementation would feature modular design with separate functions for channel modeling, SVD computation, adaptive modulation logic, and performance evaluation.