Nonlinear Precoding for Phase-Quantized Constant-Envelope Massive MU-MIMO-OFDM

Abstract

We propose a nonlinear phase-quantized constantenvelope precoding algorithm for the massive multi-user (MU) multiple-input multiple-output (MIMO) downlink. Specifically, we adapt the squared-infinity norm Douglas-Rachford splitting (SQUID) precoder to systems that use oversampling digital-toanalog converters (DACs) at the base station (BS) and orthogonal frequency-division multiplexing (OFDM) to communicate over frequency-selective channels. We demonstrate that the proposed SQUID-OFDM precoder is able to generate transmit signals that are constrained to constant envelope, which enables the use of power-efficient analog radio-frequency circuitry at the BS. By quantizing the phase of the resulting constant-envelope signal, we obtain a finite-cardinality transmit signal that can be synthesized by low-resolution (e.g., 1-bit) DACs. We use error-rate simulations to demonstrate the superiority of SQUID-OFDM over linearquantized precoders for massive MU-MIMO-OFDM systems.

Timing and Frequency Synchronization for 1-bit Massive MU-MIMO-OFDM Downlink

“…The use 1-bit DACs in the massive MU-MIMO downlink has been investigated in, e.g., [4]- [8] for transmission over frequency-flat channels, and in, e.g., [9]- [11] for transmission over frequency-selective channels with orthogonal frequencydivision multiplexing (OFDM). All of these results show that high throughput at low bit-error rate (BER) can be achieved despite the quantization artifacts introduced by the 1-bit DACs.…”

Massive MU-MIMO-OFDM Uplink with Direct RF-Sampling and 1-Bit ADCs

“…Now, using (21) and (22), we can rewrite (20) as follows: By inserting (10), (17), (19), and (24) into (16) we arrive at an analytical expression for the EVM after DDC and ZF combing that depends on the second-order statistics of the input to the direct RF-sampling 1-bit ADCs, which in turn depends on the realization of the wireless channel.…”

A Framework for One-Bit and Constant-Envelope Precoding Over Multiuser Massive MISO Channels

“…The rationale is to minimize distortions that appear in the received signals, relative to the ground-truth symbols. Criteria used in the literature include minimum mean square error (MMSE) [11] and multiuser interference minimization in the least squares sense [12]; see [13][14][15][16] and [17][18][19][20] for more. In one-bit precoding, the MMSE-based algorithm in [11], called SQUID, is particularly popular.…”

“…U is given by (6) for one-bit precoding, by (7) for CE precoding, and by (8) for DCE precoding. As can be seen in (14), we intend to achieve the aforementioned aim by minimizing the worst SEP among all the users and at all symbol times. We should emphasize that Problem (14) not only designs the precoder, it also optimizes the QAM inter-point spacings for best performance.…”

“…The inter-point spacings are a key factor in enhancing SEP performance. Some existing works pre-fix the inter-point spacings [12,17,18,20], some uses analyses to predict [7], and some assume identical inter-point spacing for all users [13][14][15]. Our framework jointly optimizes the precoder and the inter-point spacings, and the treatment is more general than the previous.…”