Nuts and Bolts of a Realistic Stochastic Geometric Analysis of mmWave HetNets: Hardware Impairments and Channel Aging

© 2019 IEEE.Motivated by heterogeneous network (HetNet) design in improving coverage and by millimeter-wave (mmWave) transmission offering an abundance of extra spectrum, we present a general analytical framework shedding light on the downlink of realistic mmWave HetNets consisting of K tiers of randomly located base stations. Specifically, we model, by virtue of stochastic geometry tools, the multi-Tier multi-user (MU) multiple-input multiple-output (MIMO) mmWave network degraded by the inevitable residual additive transceiver hardware impairments (RATHIs) and channel aging. Given this setting, we derive the coverage probability and the area spectral efficiency (ASE), and we subsequently evaluate the impact of residual transceiver hardware impairments and channel aging on these metrics. Different path-loss laws for line-of-sight and non-line-of-sight are accounted for the analysis, which are among the distinguishing features of mmWave systems. Among the findings, we show that the RATHIs have a meaningful impact at the high-signal-To-noise-ratio regime, while the transmit additive distortion degrades further than the receive distortion the system performance. Moreover, serving fewer users proves to be preferable, and the more directive the mmWaves are, the higher the ASE becomes.Peer reviewedFinal Accepted Versio

Array Architectures and Physical Layer Design for Millimeter-Wave Communications Beyond 5G

Ever increasing demands in mobile data rates have resulted in exploration of millimeter-wave (mmW) frequencies for the next generation (5G) wireless networks. Communications at mmW frequencies is presented with two keys challenges. Firstly, high propagation loss requires base stations (BSs) and user equipment (UEs) to use a large number of antennas and narrow beams to close the link with sufficient received signal power. Consequently, communications using narrow beams create a new challenge in channel estimation and link establishment based on fine angular probing. Current mmW system use analog phased arrays that can probe only one angle at the time which results in high latency during link establishment and channel tracking. It is desirable to design low latency beam training by exploring both physical layer designs and array architectures that could replace current 5G approaches and pave the way to the communications for frequency bands in higher mmW band and sub-THz region where larger antenna arrays and communications bandwidth can be exploited. To this end, we propose a novel signal processing techniques exploiting unique properties of mmW channel, and show both theoretically, in simulation and experiments its advantages over conventional approaches. Secondly, we explore different array architecture design and analyze their trade-offs between spectral efficiency and power consumption and area. For comprehensive comparison, we have developed a methodology for optimal design of system parameters for different array architecture candidates based on the spectral efficiency target, and use these parameters to estimate the array area and power consumption based on the circuits reported in the literature. We show that the hybrid analog and digital architectures have severe scalability concerns in radio frequency signal distribution with increased array size and spatial multiplexing levels, while the fully-digital array architectures have the best performance and power/area trade-offs.The developed approaches are based on a cross-disciplinary research that combines innovation in model based signal processing, machine learning, and radio hardware. This work is the first to apply compressive sensing (CS), a signal processing tool that exploits sparsity of mmW channel model, to accelerate beam training of mmW cellular system. The algorithm is designed to address practical issues including the requirement of cell discovery and synchronization that involves estimation of angular channel together with carrier frequency offset and timing offsets. We have analyzed the algorithm performance in the 5G compliant simulation and showed that an order of magnitude saving is achieved in initial access latency for the desired channel estimation accuracy. Moreover, we are the first to develop and implement a neural network assisted compressive beam alignment to deal with hardware impairments in mmW radios. We have used 60GHz mmW testbed to perform experiments and show that neural networks approach enhances alignment rate compared to CS. To further accelerate beam training, we proposed a novel frequency selective probing beams using the true-time-delay (TTD) analog array architecture. Our approach utilizes different subcarriers to scan different directions, and achieves a single-shot beam alignment, the fastest approach reported to date. Our comprehensive analysis of different array architectures and exploration of emerging architectures enabled us to develop an order of magnitude faster and energy efficient approaches for initial access and channel estimation in mmW systems

Millimeter Wave Systems for Wireless Cellular Communications

This thesis considers channel estimation and multiuser (MU) data transmission for massive MIMO systems with fully digital/hybrid structures in mmWave channels. It contains three main contributions. In this thesis, we first propose a tone-based linear search algorithm to facilitate the estimation of angle-of-arrivals of the strongest components as well as scattering components of the users at the base station (BS) with fully digital structure. Our results show that the proposed maximum-ratio transmission (MRT) based on the strongest components can achieve a higher data rate than that of the conventional MRT, under the same mean squared errors (MSE). Second, we develop a low-complexity channel estimation and beamformer/precoder design scheme for hybrid mmWave systems. In addition, the proposed scheme applies to both non-sparse and sparse mmWave channel environments. We then leverage the proposed scheme to investigate the downlink achievable rate performance. The results show that the proposed scheme obtains a considerable achievable rate of fully digital systems. Taking into account the effect of various types of errors, we investigate the achievable rate performance degradation of the considered scheme. Third, we extend our proposed scheme to a multi-cell MU mmWave MIMO network. We derive the closed-form approximation of the normalized MSE of channel estimation under pilot contamination over Rician fading channels. Furthermore, we derive a tight closed-form approximation and the scaling law of the average achievable rate. Our results unveil that channel estimation errors, the intra-cell interference, and the inter-cell interference caused by pilot contamination over Rician fading channels can be efficiently mitigated by simply increasing the number of antennas equipped at the desired BS.Comment: Thesi

Analysis of millimeter wave and massive MIMO cellular networks

Millimeter wave (mmWave) communication and massive multiple-input multiple-output (MIMO) are promising techniques to increase system capacity in 5G cellular networks. The prior frameworks for conventional cellular systems do not directly apply to analyze mmWave or massive MIMO networks, as (i) mmWave cellular networks differ in the different propagation conditions and hardware constraints; and (ii) with a order of magnitude more antennas than conventional multi-user MIMO systems, massive MIMO systems will be operated in time-division duplex (TDD) mode, which renders pilot contamination a primary limiting factor. In this dissertation, I develop stochastic geometry frameworks to analyze the system-level performance of mmWave, sub-6 GHz massive MIMO, and mmWave massive MIMO cellular networks. The proposed models capture the key features of each technique, and allow for tractable signal-to-interference-plus-noise ratio (SINR) and rate analyses. In the first contribution, I develop an mmWave cellular network model that incorporates the blockage effect and directional beamforming, and analyze the SINR and rate distributions as functions of the base station density, blockage parameters, and antenna geometry. The analytical results demonstrate that with a sufficiently dense base station deployment, mmWave cellular networks are capable to achieve comparable SINR coverage and much higher rates than conventional networks. In my second contribution, I analyze the uplink SINR and rate in sub-6 GHz massive MIMO networks with the incorporation of pilot contamination and fractional power control. Based on the analysis, I show scaling laws between the number of antennas and scheduled users per cell that maintain the uplink signal-to-interference ratio (SIR) distributions are different for maximum ratio combining (MRC) and zero-forcing (ZF) receivers. In my third contribution, I extend the sub-6 GHz massive MIMO model to mmWave frequencies, by incorporating key mmWave features. I leverage the proposed model to investigate the asymptotic SINR performance, when the number of antennas goes to infinity. Numerical results show that mmWave massive MIMO outperforms its sub-6 GHz counterpart in cell throughput with a dense base station deployment, while the reverse can be true with a low base station density.Electrical and Computer Engineerin

Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design

Massive multiple-input multiple-output (MIMO) systems are cellular networks where the base stations (BSs) are equipped with unconventionally many antennas, deployed on co-located or distributed arrays. Huge spatial degrees-of-freedom are achieved by coherent processing over these massive arrays, which provide strong signal gains, resilience to imperfect channel knowledge, and low interference. This comes at the price of more infrastructure; the hardware cost and circuit power consumption scale linearly/affinely with the number of BS antennas $N$. Hence, the key to cost-efficient deployment of large arrays is low-cost antenna branches with low circuit power, in contrast to today's conventional expensive and power-hungry BS antenna branches. Such low-cost transceivers are prone to hardware imperfections, but it has been conjectured that the huge degrees-of-freedom would bring robustness to such imperfections. We prove this claim for a generalized uplink system with multiplicative phase-drifts, additive distortion noise, and noise amplification. Specifically, we derive closed-form expressions for the user rates and a scaling law that shows how fast the hardware imperfections can increase with $N$ while maintaining high rates. The connection between this scaling law and the power consumption of different transceiver circuits is rigorously exemplified. This reveals that one can make the circuit power increase as $\sqrt{N}$, instead of linearly, by careful circuit-aware system design.Comment: Accepted for publication in IEEE Transactions on Wireless Communications, 16 pages, 8 figures. The results can be reproduced using the following Matlab code: https://github.com/emilbjornson/hardware-scaling-law

Bandwidth Compressed Waveform and System Design for Wireless and Optical Communications: Theory and Practice

This thesis addresses theoretical and practical challenges of spectrally efficient frequency division multiplexing (SEFDM) systems in both wireless and optical domains. SEFDM improves spectral efficiency relative to the well-known orthogonal frequency division multiplexing (OFDM) by non-orthogonally multiplexing overlapped sub-carriers. However, the deliberate violation of orthogonality results in inter carrier interference (ICI) and associated detection complexity, thus posing many challenges to practical implementations. This thesis will present solutions for these issues. The thesis commences with the fundamentals by presenting the existing challenges of SEFDM, which are subsequently solved by proposed transceivers. An iterative detection (ID) detector iteratively removes self-created ICI. Following that, a hybrid ID together with fixed sphere decoding (FSD) shows an optimised performance/complexity trade-off. A complexity reduced Block-SEFDM can subdivide the signal detection into several blocks. Finally, a coded Turbo-SEFDM is proved to be an efficient technique that is compatible with the existing mobile standards. The thesis also reports the design and development of wireless and optical practical systems. In the optical domain, given the same spectral efficiency, a low-order modulation scheme is proved to have a better bit error rate (BER) performance when replacing a higher order one. In the wireless domain, an experimental testbed utilizing the LTE-Advanced carrier aggregation (CA) with SEFDM is operated in a realistic radio frequency (RF) environment. Experimental results show that 40% higher data rate can be achieved without extra spectrum occupation. Additionally, a new waveform, termed Nyquist-SEFDM, which compresses bandwidth and suppresses out-of-band power leakage is investigated. A 4th generation (4G) and 5th generation (5G) coexistence experiment is followed to verify its feasibility. Furthermore, a 60 GHz SEFDM testbed is designed and built in a point-to-point indoor fiber wireless experiment showing 67% data rate improvement compared to OFDM. Finally, to meet the requirements of future networks, two simplified SEFDM transceivers are designed together with application scenarios and experimental verifications

On the performance of hybrid beamforming for millimeter wave wireless networks

The phenomenal growth in the demand for mobile wireless data services is pushing the boundaries of modern communication networks. Developing new technologies that can provide unprecedented data rates to support the pervasive and exponentially increasing demand is therefore of prime importance in wireless communications. In existing communication systems, physical layer techniques are commonly used to improve capacity. Nevertheless, the limited available resources in the spectrum are unable to scale up, fundamentally restricting further capacity increase. Consequently, alternative approaches which exploit both unused and underutilised spectrum bands are highly attractive. This thesis investigates the use of the millimeter wave (mmWave) spectrum as it has the potential to provide unlimited bandwidth to wireless communication systems. As a first step toward realising mmWave wireless communications, a cloud radio access network using mmWave technology in the fronthaul and access links is proposed to establish a feasible architecture for deploying mmWave systems with hybrid beamforming. Within the context of a multi-user communication system, an analytical framework of the downlink transmission is presented, providing insights on how to navigate across the challenges associated with high-frequency transmissions. The performance of each user is measured by deriving outage probability, average latency and throughput in both noise-limited and interference-limited scenarios. Further analysis of the system is carried out for two possible user association configurations. By relying on large antenna array deployment in highly dense networks, this architecture is able to achieve reduced outages with very low latencies, making it ideal to support a growing number of users. The second part of this work describes a novel two-stage optimisation algorithm for obtaining hybrid precoders and combiners that maximise the energy efficiency (EE) of a general multi-user mmWave multiple-input, multiple-output (MIMO) interference channel network involving internet of things (IoT) devices. The hybrid transceiver design problem considers both perfect and imperfect channel state information (CSI). In the first stage, the original non-convex multivariate EE maximization problem is transformed into an equivalent univariate problem and the optimal single beamformers are then obtained by exploiting the correlation between parametric and fractional programming problems and the relationship between weighted sum rate (WSR) and weighted minimum mean squared error (WMMSE) problems. The second stage involves the use of an orthogonal matching pursuit (OMP)-based algorithm to obtain the energy-efficient hybrid beamformers. This approach produces results comparable to the optimal beam-forming strategy but with much lower complexity, and further validates the use of mmWave networks in practice to support the demand from ubiquitous power-constrained smart devices. In the third part, the focus is on the more practical scenario of imperfect CSI for multi-user mmWave systems. Following the success of hybrid beamforming for mmWave wireless communication, a non-traditional transmission strategy called Rate Splitting (RS) is investigated in conjunction with hybrid beamforming to tackle the residual multi-user interference (MUI) caused by errors in the estimated channel. Using this technique, the transmitted signal is split into a common message and a private message with the transmitted power dynamically divided between the two parts to ensure that there is interference-free transmission of the common message. An alternating maximisation algorithm is proposed to obtain the optimal common precoder. Simulation results show that the RS transmission scheme is beneficial to multi-user mmWave transmissions as it enables remarkable rate gains over the traditional linear transmission methods. Finally, the fourth part analyses the spectral efficiency (SE) performance of a mmWave system with hybrid beamforming whilst accounting for real-life practice transceiver hardware impairments. An investigation is conducted into three major hardware impairments, namely, the multiplicative phase noise (PN), the amplified thermal noise (ATN) and the residual additive transceiver hardware impairments (RATHI). The hybrid precoder is designed to maximise the SE by the minimisation of the Euclidean distance between the optimal digital precoder and the noisy product of the hybrid precoders while the hybrid combiners are designed by the minimisation of the mean square error (MSE) between the transmitted and received signals. Multiplicative PN was found to be the most critical of the three impairments considered. It was observed that the additive impairments could be neglected for low signal-to-noise-ratio (SNR) while the ATNs caused a steady degradation to the SE performance