Related papers: Multiuser-MIMO Systems Using Comparator Network-Ai…
This paper develops a linear minimum mean-square error (LMMSE) channel estimator for single and multicarrier systems that takes advantage of the mutual coupling in antenna arrays. We model the mutual coupling through multiport networks and…
In millimeter wave (mmWave) systems, we investigate uplink user scheduling when a basestation employs low-resolution analog-to-digital converters (ADCs) with a large number of antennas. To reduce power consumption in the receiver,…
Fixed low-resolution Analog to Digital Converters (ADC) help reduce the power consumption in millimeter-wave Massive Multiple-Input Multiple-Output (Ma-MIMO) receivers operating at large bandwidths. However, they do not guarantee optimal…
Future wireless communications will rely on multiple-input multiple-output (MIMO) beamforming operating at millimeter wave (mmWave) frequency bands to deliver high data rates. To support flexible spatial processing and meet the demands of…
This paper is concerned with channel estimation in MIMO systems with few-bit ADCs. In these systems, a linear minimum mean-squared error (MMSE) channel estimator obtained in closed-form is not an optimal solution. We first consider a deep…
Channel estimation at millimeter wave (mmWave) is challenging when large antenna arrays are used. Prior work has leveraged the sparse nature of mmWave channels via compressed sensing based algorithms for channel estimation. Most of these…
In this paper, we propose a hybrid analog-digital beamforming architecture with resolution-adaptive ADCs for millimeter wave (mmWave) receivers with large antenna arrays. We adopt array response vectors for the analog combiners and derive…
Massive MIMO is a variant of multiuser MIMO where the number of base-station antennas $M$ is very large (typically 100), and generally much larger than the number of spatially multiplexed data streams (typically 10). Unfortunately, the…
High hardware cost and high power consumption of massive multiple-input and multiple output (MIMO) are two challenges for the future wireless communications including beyond fifth generation (B5G) and sixth generation (6G). Adopting the…
The high path loss associated with millimeter wave (mmWave) frequency communication can be compensated by large scale antenna arrays such as multiple-input multiple-output (MIMO) systems. The hybrid beamforming architecture which uses fewer…
With bandwidths on the order of a gigahertz in emerging wireless systems, high-resolution analog-to-digital convertors (ADCs) become a power consumption bottleneck. One solution is to employ low resolution one-bit ADCs. In this paper, we…
High power consumption and hardware cost are two barriers for practical massive multiple-input multiple-output (mMIMO) systems. A promising solution is to employ low-resolution analog-to-digital converters (ADCs). In this paper, we consider…
Massive multiple-input multiple-output (MIMO) communications using low-resolution analog-to-digital converters (ADCs) is a promising technology for providing high spectral and energy efficiency with affordable hardware cost and power…
In this paper, we propose a Singular-Value-Decomposition-based variable-resolution Analog to Digital Converter (ADC) bit allocation design for a single-user Millimeter wave massive Multiple-Input Multiple-Output receiver. We derive the…
Linear minimum mean square error (LMMSE) receivers are often applied in practical communication scenarios for single-input-multiple-output (SIMO) systems owing to their low computational complexity and competitive performance. However,…
All-digital basestation (BS) architectures for millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO), which equip each radio-frequency chain with dedicated data converters, have advantages in spectral…
Millimeter wave systems suffer from high power consumption and are constrained to use low resolution quantizers --digital to analog and analog to digital converters (DACs and ADCs). However, low resolution quantization leads to reduced data…
In this paper, we propose a low-complexity beamspace channel denoising algorithm for millimeter-wave (mmWave) massive multi-input multi-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). The proposed method…
Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single-antenna systems. Owing to the many antennas, low-cost implementation and low power consumption…
The practical deployment of massive multiple-input multiple-output (MIMO) in future fifth generation (5G) wireless communication systems is challenging due to its high hardware cost and power consumption. One promising solution to address…