Iterative decoding improves mixed near and far field XL-MIMO systems
Study of Iterative Detection and Decoding for {Mixed Near- and Far-Field} XL-MIMO Systems
Information Theory
Summary
Wireless systems with many antennas can serve users nearby and far away but face challenges in managing signals due to different wave patterns. The authors designed a new method that better orders signal decoding using the unique features of waves near the antennas. They combined this with iterative error-checking and improved signal measurements to make communication more reliable. Their tests show this approach works better than existing methods, helping signals from many users be separated and decoded accurately.
What this means in practice
- •For wireless network engineers: Enhance multi-user signal decoding in extra-large antenna systems that serve users near and far to improve network throughput and reliability.
- •For communications system integrators: Integrate iterative detection and weighted ordering schemes into advanced MIMO platform designs to better handle varied user locations and reduce interference effects.
Authors
Nayyab Haider, Rodrigo C. de Lamare
Abstract
Extra-large multiple-input multiple-output (XL-MIMO) systems {serving users across near-field and far-field regions} experience spherical wavefront propagation that provides enhanced spatial resolution over traditional far-field systems. In this work, we propose a novel weighted rate (WR) ordering-based successive interference cancellation (SIC) scheme that exploits the spatial degrees of freedom inherent in near-field propagation. We also develop an iterative detection and decoding (IDD) framework that integrates the proposed WR ordering with low-density parity-check (LDPC) coding and channel estimation. We then analyze the information rates and the impact of near-field channel characteristics. Numerical results show that the proposed WR-SIC and the IDD scheme outperform existing approaches.