On Performance of Quantized Transceiver in Multiuser Massive MIMO Downlinks

Abstract

Abstract-Low-resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) are considered to reduce cost and power consumption in multiuser massive multipleinput multiple-output (MIMO). Using the Bussgang theorem, we derive the asymptotic downlink achievable rate w.r.t the resolutions of both DACs and ADCs, i.e., bDA and bAD, under the assumption of large antenna number, N , and fixed user load ratio, β. We characterize the rate loss caused by finite-bitresolution converters and reveal that the quantization distortion is ignorable at low signal-to-noise ratio (SNR) even with lowresolution converters at both sides. While for maintaining the same rate loss at high SNR, it is discovered that one-more-bit DAC resolution is needed when more users are scheduled with β increased by four times. More specifically for one-bit rate loss requirement, bDA can be set by bAD + 1 2 log β given bAD. Similar observations on ADCs are also obtained with numerical verifications.

On the Uplink Achievable Rate of Massive MIMO System with Low-Resolution ADC and RF Impairments

“…Under the assumption of additive quantization noise model (AQNM), the impacts of low-resolution ADCs on the uplink achievable rate of massive MIMO system were investigated in [2], [3], and the asymptotic downlink achievable rate was derived in [4]. For the special case of 1-bit quantization, channel estimation and performance of massive MIMO system have been investigated in [5].…”

Performance Analysis of Multi-Cell Millimeter-Wave Massive MIMO Networks With Low-Precision ADCs

“…Fortunately, an approximately linear representation has been widely adopted by using the Bussgang theorem [38]. This quantization model has been verified accurate enough for characterizing commonly used ADCs, especially for popular quantization levels in practice [10] [39]. It decomposes the ADC quantization into two uncorrelated parts as…”

“…It has been demonstrated in [9] that low-precision, e.g., 2-3 bits, ADCs only cause limited sum rate loss under some mild assumptions for an amplifyand-forward relay uplink network. Studies in [10] and [11] have analyzed the performance of low-precision transceivers in multiuser massive MIMO downlinks. On the other hand, radio-frequency (RF) chains can be also constrained to reduce the total number of required converters, which leads to a hybrid transceiver architecture [12] [13].…”

Wideband mmWave Channel Estimation for Hybrid Massive MIMO With Low-Precision ADCs

“…After defining Ψ A * t ⊗A r and using matrix vectorization for notational simplicity, we denote h v [k] vec(H v [k]) as the equivalent channel coefficient vector to be estimated. From (9) and the unitary properties of A t and A r , we write [11] which applied the Bussgang theorem [12] on modelling non-linear quantization, it showed that the output of the non-linear quantizer with Gaussian input can be expressed in closed form by decomposing it into a desired signal component and an uncorrelated quantization distortion, e q . The output signal after ADC quantization is modelled as where η b is the distortion factor in terms of the number of quantization bits of ADCs, i.e., b, and…”