Study of Adaptive Activity-Aware Constellation List-Based Detection for Massive Machine-Type Communications
arXiv:1912.06852
Abstract
In this work, we propose an adaptive list-based decision feedback detector along with an -norm regularized recursive least-squares algorithm that only requires pilot symbols (AA-CL-DF). The proposed detector employs a list strategy based on the signal constellation points to generate different candidates for detection. Simulation results show that the proposed AA-CL-DF successfully mitigates the error propagation and approaches the performance for the oracle LMMSE algorithm.
arXiv comment7 pages, 7 figures
References in corpus (5)
- Branch-and-Bound Precoding for Multiuser MIMO Systems with 1-Bit Quantization
- Design of Robust Adaptive Beamforming Algorithms Based on Low-Rank and Cross-Correlation Techniques
- Sparsity-Aware Adaptive Algorithms Based on Alternating Optimization with Shrinkage
- Adaptive Reduced-Rank Minimum Symbol-Error-Rate Receive Processing for Large-Scale Multiple-Antenna Systems
- Direction Finding Algorithms with Joint Iterative Subspace Optimization