A Case for Digital Beamforming at mmWave

Abstract

Due to the heavy reliance of millimeter-wave (mmWave) wireless systems on directional links, beamforming (BF) with high-dimensional arrays is essential for cellular systems in these frequencies.How to perform the array processing in a power efficient manner is a fundamental challenge. Analog and hybrid BF require fewer analog-to-digital and digital-to-analog converters (ADCs and DACs), but can only communicate in a small number of directions at a time, limiting directional search, spatial multiplexing and control signaling. Digital BF enables flexible spatial processing, but must be operated at a low quantization resolution to stay within reasonable power levels. This decrease in quantizer resolution introduces noise in the received signal and degrades the quality of the transmitted signal.To assess the effect of low-resolution quantization on cellular system, we present a simple additive white Gaussian noise (AWGN) model for quantization noise. Simulations with this model reveal that at moderate resolutions (3-4 bits per ADC), there is negligible loss in downlink cellular capacity from quantization. In essence, the low-resolution ADCs limit the high SNR, where cellular systems typically do not operate. For the transmitter, it is shown that DACs with 4 or more bits of resolution do not violate the adjacent carrier leakage limit set by 3 rd Generation Partnership Project (3GPP) New Radio (NR) standards for cellular operations. Further, this work studies the effect of low resolution quantization on the error vector magnitude (EVM) of the transmitted signal.In fact, our findings suggests that low-resolution fully digital BF architectures can be a power efficient alternative to analog or hybrid beamforming for both transmitters and receivers at millimeter wave. 2 Millimeter wave, 5G cellular, Low resolution quantizers, Digital beamforming.

Finite-Alphabet MMSE Equalization for All-Digital Massive MU-MIMO mmWave Communication

“…An emerging alternative is the use of all-digital BS architectures [11]- [13]. While it is commonly believed that all-digital BS designs would be energy inefficient, it has been shown recently that the power consumption of the RF and data-conversion elements in an alldigital BS is comparable to that of hybrid solutions, provided that the resolution of the data converters at the BS is suitably reduced [10], [12]. The power consumption and system costs of baseband processing for all-digital BS architectures is, however, largely unexplored.…”

Finite-Alphabet Wiener Filter Precoding for mmWave Massive MU-MIMO Systems

“…Since the problems in (11) and (14) are NP-hard, FAWP-WF significantly reduces complexity. Concretely, FAWP-WF requires the same complexity of O(BU 2 ) as computing the infinite-precision Q WF in (7). As a result, we will use FAWP-WF as a baseline to evaluate the performance of the algorithm proposed next, which tackles the problems in (11) and (14).…”

“…To keep the power consumption within acceptable bounds, research has mostly focused on hybrid analog-digital architectures [3]- [5]. Such hybrid BS architectures are, however, limited in their beamforming capabilities [5]- [7], which leads to reduced spectral efficiency. Per contra, all-digital BS architectures [8]- [10] do not suffer from such limitations.…”

“…Per contra, all-digital BS architectures [8]- [10] do not suffer from such limitations. While it is natural to believe that all-digital solutions are more powerhungry than hybrid architectures, recent results show thatby reducing the data-converter resolution-the radio-frequency circuitry and data-converters in an all-digital BS (i) have similar power consumption as in a hybrid BS [7] and (ii) enable superior spectral efficiency [9]. Besides these recent results, the power consumption and silicon area of baseband processing in alldigital BS architectures are largely unexplored.…”

Algorithm and VLSI Design for 1-Bit Data Detection in Massive MIMO-OFDM

“…In massive MU-MIMO, the infrastructure basestations (BSs) are equipped with hundreds of antenna elements that simultaneously serve tens of user equipments (UEs) in the same frequency band. In alldigital massive MU-MIMO basestation architectures [4], [5], each radio-frequency (RF) chain is equipped with a pair of high-resolution (e.g., 10 bit to 12 bit) analog-to-digital converters (ADCs). The presence of hundreds of such highquality RF chains inevitably results in high power consumption, interconnect data rates, and hardware costs, especially when deployed for the large bandwidths offered at millimeter-wave (mmWave) frequencies [6], [7].…”