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

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper considers channel estimation and uplink achievable rate of the coarsely quantized massive multiple-input multiple-output (MIMO) system with radio frequency (RF) impairments. We utilize additive quantization noise model (AQNM) and extended error vector magnitude (EEVM) model to analyze the impacts of low-resolution analog-to-digital converters (ADCs) and RF impairments respectively. We show that hardware impairments cause a nonzero floor on the channel estimation error, which contraries to the conventional case with ideal hardware. The maximal-ratio combining (MRC) technique is then used at the receiver, and an approximate tractable expression for the uplink achievable rate is derived. The simulation results illustrate the appreciable compensations between ADCs’ resolution and RF impairments. The proposed studies support the feasibility of equipping economical coarse ADCs and economical imperfect RF components in practical massive MIMO systems

Massive MIMO Systems with Hardware Imperfections

Recent years have witnessed an unprecedented explosion in mobile data traffic, due to the expansion of numerous types of wireless devices. Moreover, each device needs a high throughput to support demanding applications such as real-time video, movie streaming and games. Thus, future wireless systems have to satisfy three main requirements: 1) having a high throughput; 2) simultaneously serving many users; and 3) less energy consumption. Massive multiple-input multiple-output (MIMO) systems meet the aforementioned requirements and is nowadays a well-established technology which forms the backbone of the fifth-generation (5G) cellular communication systems.\ua0However, massive MIMO systems, i.e. employing hundreds or even thousands of antennas, will be a viable solution in the future only if low-cost and energy-efficient hardware is deployed. Unfortunately, low-cost, low-quality hardware is prone to hardware impairments such as in-phase and quadrature imbalance (IQI) and phase noise.\ua0\ua0Moreover, one of the dominant sources of power consumption in massive MIMO systems are the data converters at the BS. The baseband signal at each radio-frequency (RF) chain is generated by a pair of analog-to-digital converters (ADCs). The power consumption of these ADCs increases exponentially with the resolution (in bits) and linearly with the bandwidth. In conventional multi-antenna systems, each RF port is connected to a pair of high-resolution ADCs (e.g., 10-bit or more). For massive MIMO systems this would lead to prohibitively high-power consumption due to the large number of required ADCs. Hence, the ADC resolution must be limited to keep the power budget within tolerable levels.In this thesis, we investigate the performance of massive MIMO systems in non-ideal hardware. We begin with by studying the impact of IQI on massive MIMO systems. Important insights are gained through the analysis of system performance indicators, such as channel estimation and achievable rates by deriving tractable approximations of the ergodic spectral efficiency.First, a novel pilot-based joint estimator of the uplink augmented MIMO channel matrix and receiver IQI coefficients is described and then, a low-complexity IQI compensation scheme is proposed which is based on the receiver IQI coefficients\u27 estimation and it is independent of the channel gain.\ua0Second, we investigate the impact of the transceiver IQI in massive MIMO considering a time division duplexing (TDD) system where we assume uplink/downlink channel reciprocity in the downlink precoding design. The uplink channel estimation accuracy and the achievable downlink rate of the regularized zero-forcing (RZF) and maximum ratio transmission (MRT) is studied when there is mismatch between the uplink and downlink channels.\ua0Finally, we analyze the quantization distortion in limited-precision ADCs in uplink massive MIMO systems whose channel state information (CSI) is not known a priori to transmitter and receiver. We show that even a small percentage of clipped samples at the receiver can downgrade considerably the systems performance and propose near-optimal low-complexity solutions to reconstruct the clipped signal

Performance Evaluation of Low Complexity Massive MIMO Techniques for SC-FDE Schemes

Massive-MIMO technology has emerged as a means to achieve 5G's ambitious goals; mainly to obtain higher capacities and excellent performances without requiring the use of more spectrum. In this thesis, focused on the uplink direction, we make a study of performance of low complexity equalization techniques as well as we also approach the impact of the non-linear elements located on the receivers of a system of this type. For that purpose, we consider a multi-user uplink scenario through the Single Carrier with Frequency Domain Equalization (SC-FDE) scheme. This seems to be the most appropriate due to the low energy consumption that it implies, as well as being less favorable to the detrimental effects of high envelope fluctuations, that is, by have a low Peak to Average Power Ratio (PAPR) comparing to other similar modulations, such as the Orthogonal Frequency Division Multiplexing (OFDM). Due to the greater number of antennas and consequent implementation complexity, the equalization processes for Massive- MIMO schemes are aspects that should be simplified, that is, they should avoid the inversion of matrices, contrary to common 4G, with the Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) techniques. To this end, we use low-complexity techniques, such as the Equal Gain Combining (EGC) and the Maximum Ratio Combining (MRC). Since these algorithms are not sufficiently capable of removing the entire Inter-Symbol Interference (ISI) and Inter-User Interference (IUI), we combine them with iterative techniques, namely with the Iterative Block with Decision Feedback Equalizer (IB-DFE) to completely remove the residual ISI and IUI. We also take into account the hardware used in the receivers, since the effects of non-linear distortion can impact negatively the performance of the system. It is expected a strong performance degradation associated to the high quantization noise levels when implementing low-resolution Analog to Digital Converters (ADCs). However, despite these elements with these configurations become harmful to the performance of the majority of the systems, they are considered a desirable solution for Massive-MIMO scenarios, because they make their implementation cheaper and more energy efficient. In this way, we made a study of the impact in the performance by the low-resolution ADCs. In this thesis we suggest that it is possible to bypass these negative effects by implementing a number of receiving antennas far superior to the number of transmitting antennas

Advanced Techniques for High-Throughput Cellular Communications

The next generation wireless communication systems require ubiquitous high-throughput mobile connectivity under a range of challenging network settings (urban versus rural, high device density, mobility, etc). To improve the performance of the system, the physical layer design is of great importance. The previous research on improving the physical layer properties includes: a) highly directional transmissions that can enhance the throughput and spatial reuse; b) enhanced MIMO that can eliminate contention, enabling linear increase of capacity with number of antennas; c) mmWave technologies which operate on GHz bandwidth to over substantially higher throughput; d) better cooperative spectrum sharing with cognitive radios; e) better multiple access method which can mitigate multiuser interference and allow more multi-users. This dissertation addresses several techniques in the physical layer design of the next generation wireless communication systems. In chapter two, an orthogonal frequency division with code division multiple access (OFDM-CDMA) systems is proposed and a polyphase code is used to improve multiple access performance and make the OFDM signal satisfy the peak to average ratio (PAPR) constraint. Chapter three studies the I/Q imbalance for direct down converter. For wideband transmitter and receiver that use direct conversion for I/Q sampling, the I/Q imbalance becomes a critical issue. With higher I/Q imbalance, there will be higher degradation in quadrature amplitude modulation, which degrades the throughput tremendously. Chapter four investigate a problem of spectrum sharing for cognitive wideband communication. An energy-efficient sub-Nyquist sampling algorithm is developed for optimal sampling and spectrum sensing. In chapter ve, we study the channel estimation of millimeter wave full-dimensional MIMO communication. The problem is formulated as an atomic-norm minimization problem and algorithms are derived for the channel estimation in different situations. In this thesis, mathematical optimization is applied as the main approach to analyze and solve the problems in the physical layer of wireless communication so that the high-throughput is achieved. The algorithms are derived along with the theoretical analysis, which are validated with numerical results