Massive MIMO downlink 1-bit precoding with linear programming for PSK signaling

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 and the quantization distortions in a downlink multi-user (MU) multiple-input-single-output (MISO) system with 1-bit quantization at the transmitter. This work is restricted to PSK modulation schemes. The transmit signal vector is optimized for every desired received vector taking into account the 1-bit quantization. The optimization is based on maximizing the safety margin to the decision thresholds of the PSK modulation. Simulation results show a significant gain in terms of the uncoded bit-error-ratio (BER) compared to the existing linear precoding techniques

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 and the quantization distortions in a downlink multi-user 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 a relaxed version of the QCE constraint. The optimization is based on maximizing the safety margin to the decision thresholds of the receiver constellation modulation. Due to the linear property of the objective function and the constraints, the optimization problem is formulated as a linear programming problem. The simulation results show a significant gain in terms of the uncoded bit error rate compared to the existing precoding techniques

Precoding under instantaneous per-antenna peak power constraint

We consider a multi-user (MU) multiple-input-single-output (MISO) downlink system with M single-antenna users and N transmit antennas with a nonlinear power amplifier (PA) at each antenna. Instead of emitting constant envelope (CE) signals from the antennas to have highly power efficient PAs, we relax the CE constraint and allow the transmit signals to have instantaneous power less than or equal to the available power at each PA. The PA power efficiency decreases but simulation results show that the same performance in terms of bit-error-ratio (BER) can be achieved with less transmitted power and less PA power consumption. We propose a linear and a nonlinear precoder design to mitigate the multi-user interference (MUI) under the constraint of a maximal instantaneous per-antenna peak power

A Comparison of Hybrid Beamforming and Digital Beamforming With Low-Resolution ADCs for Multiple Users and Imperfect CSI

For 5G, it will be important to leverage the available millimeter wave spectrum. To achieve an approximately omnidirectional coverage with a similar effective antenna aperture compared to state-of-the-art cellular systems, an antenna array is required at both the mobile and base station. Due to the large bandwidth and inefficient amplifiers available in CMOS for mmWave, the analog front end of the receiver with a large number of antennas becomes especially power hungry. Two main solutions exist to reduce the power consumption: hybrid beam forming and digital beam forming with low resolution Analog to digital converters (ADCs). In this paper, we compare the spectral and energy efficiency of both systems under practical system constraints. We consider the effects of channel estimation, transmitter impairments, and multiple simultaneous users for a wideband multipath model. Our power consumption model considers components reported in the literature at 60 GHz. In contrast to many other works, we also consider the correlation of the quantization error, and generalize the modeling of it to nonuniform quantizers and different quantizers at each antenna. The result shows that as the signal-to-noise ratio (SNR) gets larger the ADC resolution achieving the optimal energy efficiency gets also larger. The energy efficiency peaks for 5-b resolution at high SNR, since due to other limiting factors, the achievable rate almost saturates at this resolution. We also show that in the multiuser scenario digital beamforming is in any case more energy efficient than hybrid beamforming. In addition, we show that if mixed ADC resolutions are used, we can achieve any desired tradeoff between power consumption and rate close to those achieved with only one ADC resolution