On Out-of-Band Emissions of Quantized Precoding in Massive MU-MIMO-OFDM

We analyze out-of-band (OOB) emissions in the massive multi-user (MU) multiple-input multiple-output (MIMO) downlink. We focus on systems in which the base station (BS) is equipped with low-resolution digital-to-analog converters (DACs) and orthogonal frequency-division multiplexing (OFDM) is used to communicate to the user equipments (UEs) over frequency-selective channels. We demonstrate that analog filtering in combination with simple frequency-domain digital predistortion (DPD) at the BS enables a significant reduction of OOB emissions, but degrades the signal-to-interference-noise-and-distortion ratio (SINDR) at the UEs and increases the peak-to-average power ratio (PAR) at the BS. We use Bussgang's theorem to characterize the tradeoffs between OOB emissions, SINDR, and PAR, and to study the impact of analog filters and DPD on the error-rate performance of the massive MU-MIMO-OFDM downlink. Our results show that by carefully tuning the parameters of the analog filters, one can achieve a significant reduction in OOB emissions with only a moderate degradation of error-rate performance and PAR.Comment: Presented at the 2017 Asilomar Conference on Signals, Systems, and Computers, 6 page

Reconsidering Linear Transmit Signal Processing in 1-Bit Quantized Multi-User MISO Systems

In this contribution, we investigate a coarsely quantized Multi-User (MU)-Multiple Input Single Output (MISO) downlink communication system, where we assume 1-Bit Digital-to-Analog Converters (DACs) at the Base Station (BS) antennas. First, we analyze the achievable sum rate lower-bound using the Bussgang decomposition. In the presence of the non-linear quanization, our analysis indicates the potential merit of reconsidering traditional signal processing techniques in coarsely quantized systems, i.e., reconsidering transmit covariance matrices whose rank is equal to the rank of the channel. Furthermore, in the second part of this paper, we propose a linear precoder design which achieves the predicted increase in performance compared with a state of the art linear precoder design. Moreover, our linear signal processing algorithm allows for higher-order modulation schemes to be employed

Quantized Constant Envelope Precoding with PSK and QAM Signaling

Coarsely quantized massive Multiple-Input Multiple-Output (MIMO) systems are gaining more interest due to their power efficiency. We present a new precoding technique to mitigate the Multi-User Interference (MUI) and the quantization distortions in a downlink Multi-User (MU) MIMO system with coarsely Quantized Constant Envelope (QCE) signals at the transmitter. The transmit signal vector is optimized for every desired received vector taking into account the QCE constraint. The optimization is based on maximizing the safety margin to the decision thresholds of the receiver constellation modulation. Simulation results show a significant gain in terms of the uncoded Bit Error Ratio (BER) compared to the existing linear precoding techniques