Study of Symbol Error Probability Constrained Precoding with Zero-Crossing Modulation for Wireless Systems with 1-Bit ADCs

TL;DR

This work addresses energy-efficient downlink MU-MIMO with 1-bit ADCs by leveraging oversampling and TI ZX modulation to encode information in zero-crossings. It introduces a QoS-based temporal precoding design that minimizes transmit energy under a target SER constraint, formulated as a convex optimization incorporating the SER-distance relation. A semi-analytical SER upper bound based on a multivariate Gaussian model provides tractable performance guarantees, complemented by PGD-based computation of the temporal precoder. Simulation results validate the approach, showing trade-offs between oversampling, temporal dimension, and transmit energy, with multiuser scenarios demonstrating the method's practicality for high-bandwidth, low-power transceivers.

Abstract

The next generation of wireless communications systems will employ new frequency bands such as those in the upper midband, millimeter-wave and sub-terahertz frequency bands. The high energy consumption of analog-to-digital converters resulting from their high resolution constituted a major limitation for future wireless communications systems, which will require low energy consumption and low-complexity devices at the transmitter and at the receiver. In this regard, we present a novel precoding method based on quality of service constraints for a multiuser multiple-input multiple-output downlink system with 1-bit quantization and oversampling. For this scenario, we consider the time-instance zero-crossing modulation, which conveys the information into the zero-crossings of the signals. Unlike prior works the proposed constraint is given in terms of the symbol error probability related to the minimum distance to the decision threshold and is included in the proposed optimization problem that is used in the design of the precoder. Simulation results illustrate the performance of the proposed precoding method evaluated under different parameters and scenarios.

Figures (13)

• Figure 1: Multiuser MIMO system model
• Figure 2: Representation of the $\boldsymbol{c}_{\text{out}}$ sequence for $M_{\textrm{Rx}}=3$.
• Figure 3: Semi-analytical and numerical SER comparison for the MMDDT precoding method with $M_{\text{Rx}}= M_{\text{Tx}}= 3$, $N=1$ and $\sigma_{n}^2 = 1$.
• Figure 4: Semi-analytical and numerical SER comparison for the MMDDT precoding method with $M_{\text{Rx}}= M_{\text{Tx}}= 2$, $N=2$ and $\sigma_{n}^2 = 1$.
• Figure 5: Semi-analytical and numerical BER comparison for the MMDDT precoding method with $M_{\text{Rx}}= M_{\text{Tx}}= 3$, $N=1$ and $\sigma_{n}^2 = 1$.