ITSPITMar 24

Enhanced Uplink Data Detection for Massive MIMO with 1-Bit ADCs: Analysis and Joint Detection

arXiv:2312.0418310.51 citationsh-index: 12
Predicted impact top 60% in IT · last 90 daysOriginality Incremental advance
AI Analysis

This addresses performance limitations in massive MIMO systems with low-resolution ADCs, which is an incremental improvement for wireless communication applications.

The paper tackles uplink data detection in massive MIMO systems with 1-bit ADCs by analyzing conventional receivers and proposing a new LMMD receiver and joint detection strategies, showing that the LMMD receiver significantly outperforms conventional ones and the joint detection provides a significant boost over single-UE detection.

We present a new analytical framework on the uplink data detection for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters (ADCs). We first characterize the expected values of the soft-estimated symbols (after the linear receiver and prior to the data detection), which are affected by the 1-bit quantization during both the channel estimation and the uplink data transmission. In our analysis, we consider conventional receivers such as maximum ratio combining (MRC), zero forcing, and minimum mean squared error (MMSE), with multiple user equipments (UEs) and correlated Rayleigh fading. Additionally, we design a linear minimum mean dispersion (LMMD) receiver tailored for the data detection with 1-bit ADCs, which exploits the expected values of the soft-estimated symbols previously derived. Then, we propose a joint data detection (JD) strategy that exploits the interdependence among the soft-estimated symbols of the interfering UEs, along with its low-complexity variant. These strategies are compared with the robust maximum likelihood data detection with 1-bit ADCs. Numerical results examining the symbol error rate show that MMSE exhibits a considerable performance gain over MRC, whereas the proposed LMMD receiver significantly outperforms all the conventional receivers. Lastly, the proposed JD and its low-complexity variant provide a significant boost in comparison with the single-UE data detection.

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