Babai-guided Interference-aware Adaptive QRD-M Detection in MIMO-OFDM Communication Systems

This paper presents an adaptive QRD-M detection algorithm designed to reduce the computational complexity of MIMO systems while maintaining near-maximum likelihood detection (near-MLD) performance. The proposed method introduces a dynamic threshold mechanism based on a breadth-first tree search, where pruning is guided by both symbol reliability and interlayer interference derived from the upper-triangular structure of the QR-decomposed channel matrix. The threshold is further refined using a Babai estimate obtained from Lenstra-Lenstra-Lovász (LLL) lattice reduction, allowing the algorithm to adaptively adjust the candidate set at each detection stage. The simulation results across 4 × 4 and 8 × 8 MIMO systems using 16-QAM and 64-QAM modulation schemes demonstrate that the proposed Babai-guided interference-aware adaptive QRD-M (BIA-QRD-M) algorithm achieves near-MLD performance. The proposed method achieves a reduction of up to 49% in the average number of branch metric computations at high SNR and an approximately 29% reduction over the entire 0-25 dB SNR range, compared to conventional QRD-M in an 8 × 8 MIMO-OFDM system with 16-QAM modulation.