One-bit massive MIMO: Channel estimation and high-order modulations

Abstract

Abstract-We investigate the information-theoretic throughout achievable on a fading communication link when the receiver is equipped with one-bit analog-to-digital converters (ADCs). The analysis is conducted for the setting where neither the transmitter nor the receiver have a priori information on the realization of the fading channels. This means that channel-state information needs to be acquired at the receiver on the basis of the one-bit quantized channel outputs. We show that least-squares (LS) channel estimation combined with joint pilot and data processing is capacity achieving in the single-user, single-receive-antenna case.We also investigate the achievable uplink throughput in a massive multiple-input multiple-output system where each element of the antenna array at the receiver base-station feeds a one-bit ADC. We show that LS channel estimation and maximum-ratio combining are sufficient to support both multiuser operation and the use of high-order constellations. This holds in spite of the severe nonlinearity introduced by the one-bit ADCs.

Quantized Massive MU-MIMO-OFDM Uplink

“…In summary, the results in [4], [7], [8], [11] suggest that massive MU-MIMO provides resilience against noise caused by coarse quantization. However, all these results pertain to massive MU-MIMO systems operating over frequency-flat fading channels.…”

“…The analysis in [7] has been extended recently to higher-order modulation schemes in [8]. There, it was shown that amplitude information about the transmitted signal can be recovered even in the presence of a single-bit quantizer, provided that the number of receive antennas is sufficiently large and the signalto-noise ratio (SNR) is not too high.…”

“…In essence, we only replace the conditional probabilities p(·|·) in (Q-CHE) and (Q-DET) with the mismatched conditional probabilityp(·|·) in (8). While the dimensionality of the resulting problems remains unchanged, the algorithms that use the mismatched quantizer exhibit improved numerical stability and (often) faster convergence rates at the cost of a small degradation in performance (see Section V for the details).…”

“…The objective function, i.e., the negative log-likelihood of the quantization labels given the noiseless received signal is the MIMO generalization of the objective function given in (13) for the SISO-OFDM case. 8 The first constraint simply transforms a per-frequency representation into a per-BS-antenna representation as illustrated in Fig. 2; this simplifies the form of the objective function.…”

One-bit ADCs in wideband massive MIMO systems with OFDM transmission

“…The use of such radically coarse quantization has been suggested for use in massive Multiple-Input Multiple-Output (MIMO) base stations, where the large number of radio chains makes high resolution quantization very power consuming [2]. Recent studies have shown that the performance loss due to the coarse quantization of one-bit ADCs becomes less severe as the number of receiving antennas grows; and, in a massive MIMO base station that has hundreds of antennas, the power saving that comes with one-bit ADCs might well outweigh this performance loss [3][4][5].…”