Joint AGC and Receiver Design for Large-Scale MU-MIMO Systems with Coarsely Quantized Signals and C-RANs
arXiv:1912.06282
Abstract
In this work, we propose the joint optimization of the automatic gain control (AGC), which works in the remote radio heads (RHHs), and a low-resolution aware (LRA) linear receive filter based on the minimum mean square error (MMSE), which works on the baseband unit (BBU) pool, for large-scale multi-user multiple-input multiple-output (MU-MIMO) systems with coarsely quantized signals in cloud radio access networks. We develop successive interference cancellation receivers based on the proposed joint AGC and LRA-MMSE (AGC-LRA-MMSE) approach. An analysis of the achievable sum rates is also carried out. Simulations show that the proposed design has better error rates and higher achievable rates than existing techniques.
arXiv comment7 pages, 4 figures
References in corpus (7)
- Throughput Analysis of Massive MIMO Uplink with Low-Resolution ADCs
- 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
- Multi-Branch Tomlinson-Harashima Precoding for MU-MIMO Systems: Theory and Algorithms
- 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