Development of a Hybrid OMP – LASSO Model for Adaptive Sparse Channel Estimation in Pilot- Constrained Massive MIMO 6G Systems

• This study proposes a hybrid optimization framework for channel estimation algorithms. • The Orthogonal Matching Pursuit (OMP) optimization algorithm reduces pilot signals to improve the efficiency of channel bandwidth utilization. • The LASSO algorithm enhances channel estimation accuracy, ensuring that the received data is not corrupted by estimation errors at the receiver. • Although the number of pilot signals is limited, the proposed hybrid model is capable of improving channel efficiency while optimally reducing estimation errors. • Proper adjustment of the regularization factor (lambda) in the LASSO algorithm improves channel estimation accuracy, with the NMSE reaching its minimum values in the range of 0.001 to 0.005. Massive Multi-Input-Multi-Output (MIMO) technology facilitates large spectral efficiencies and energy efficiencies of a channel for the sixth generation of wireless communications. Sparse channel conditions and restrictive pilot conditions at high frequencies can seriously degrade channel estimation. Hence, the importance of channel estimation rests on the need to minimize overhead and pilot contamination. We address the problem of channel sparsity with a hybrid approach and use Orthogonal Matching Pursuit (OMP) with the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. In this algorithm, OMP retains the most significant channel elements, and LASSO improves the accuracy of the estimates of the channel coefficients. Results show that for OMP and LASSO used independently, the accuracy of channel estimation improves by 25.7% and 62.8%, respectively, when the computed Mean Squared Error (MSE) is used. Reduction of Normalized Mean Squared Error (NMSE) and Bit Error Rate (BER) improves the savings in overhead and pilot contamination, and maintains the regularization coefficient below 0.01 for the given range. Reducing computational complexity will allow more effective use of pilot resources in next-generation wireless systems.