Design and Analysis of 1-Bit Quantized Massive MIMO Beamforming for Sustainable 6G Wireless Systems

With the rise of 6 G wireless systems, achieving both high data throughput and energy efficiency has become a key research focus. Massive MIMO and low-resolution hardware are pivotal in enabling scalable and sustainable networks. However, traditional high-resolution DAC-based beamforming introduces excessive power consumption and hardware complexity. These limitations hinder the practicality of massive MIMO in dense deployments. Conventional methods such as 4 -bit Zero-Forcing (ZF) precoding offer good performance but consume significant energy. Similarly, existing 1-bit precoding schemes suffer from performance degradation under quantization constraints. This paper proposes a novel 1-bit quantized beamforming scheme optimized for massive MIMO downlink scenarios. The design ensures high reliability and spectral efficiency, even with coarse quantization. Simulations were conducted under i.i.d. Rayleigh fading using a 128 -antenna transmitter serving 8 users with QPSK modulation. The system operates over a 100 MHz bandwidth at a 28 GHz carrier frequency. The framework was implemented using MATLAB with $\mathbf{1, 0 0 0}$ Monte Carlo runs to ensure robustness. Comparisons were made with conventional 1bit and 4-bit ZF beamformers. The proposed method achieves a spectral efficiency of $22.4 \mathrm{bps} / \mathrm{Hz}$ and BER of $1.2 \times 10^{-8}$ at 30 dB SNR, with an energy efficiency of $\mathbf{7. 3 0}$ bits/Joule-outperforming baseline methods. In conclusion, the proposed 1-bit beamforming approach demonstrates superior performance, power efficiency, and robustness under imperfect CSI, making it highly suitable for future 6 G deployments.