Millimetre-Wave Fibre-Wireless Technologies for 5G Mobile Fronthaul

The unprecedented growth in mobile data traffic, driven primarily by bandwidth rich applications and high definition video is accelerating the development of fifth generation (5G) mobile network. As mobile access network evolves towards centralisation, mobile fronthaul (MFH) architecture becomes essential in providing high capacity, ubiquitous and yet affordable services to subscribers. In order to meet the demand for high data rates in the access, Millimetre-wave (mmWave) has been highlighted as an essential technology in the development of 5G-new radio (5G-NR). In the present MFH architecture which is typically based on common public radio interface (CPRI) protocol, baseband signals are digitised before fibre transmission, featuring high overhead data and stringent synchronisation requirements. A direct application of mmWave 5G-NR to CPRI digital MFH, where signal bandwidth is expected to be up to 1GHz will be challenging, due to the increased complexity of the digitising interface and huge overhead data that will be required for such bandwidth. Alternatively, radio over fibre (RoF) technique can be employed in the transportation of mmWave wireless signals via the MFH link, thereby avoiding the expensive digitisation interface and excessive overhead associated with its implementation. Additionally, mmWave carrier can be realised with the aid of photonic components employed in the RoF link, further reducing the system complexity. However, noise and nonlinearities inherent to analog transmission presents implementation challenges, limiting the system dynamic range. Therefore, it is important to investigate the effects of these impairments in RoF based MFH architecture. This thesis presents extensive research on the impact of noise and nonlinearities on 5G candidate waveforms, in mmWave 5G fibre wireless MFH. Besides orthogonal frequency division multiplexing (OFDM), another radio access technology (RAT) that has received significant attention is filter bank multicarrier (FBMC), particularly due to its high spectral containment and excellent performance in asynchronous transmission. Hence, FBMC waveform is adopted in this work to study the impact of noise and nonlinearities on the mmWave fibre-wireless MFH architecture. Since OFDM is widely deployed and it has been adopted for 5G-NR, the performance of OFDM and FBMC based 5G mmWave RAT in fibre wireless MFH architecture is compared for several implementations and transmission scenarios. To this extent, an end to end transmission testbed is designed and implemented using industry standard VPI Transmission Maker® to investigate five mmWave upconversion techniques. Simulation results show that the impact of noise is higher in FBMC when the signal to-noise (SNR) is low, however, FBMC exhibits better performance compared to OFDM as the SNR improved. More importantly, an evaluation of the contribution of each noise component to the overall system SNR is carried out. It is observed in the investigation that noise contribution from the optical carriers employed in the heterodyne upconversion of intermediate frequency (IF) signals to mmWave frequency dominate the system noise. An adaptive modulation technique is employed to optimise the system throughput based on the received SNR. The throughput of FBMC based system reduced significantly compared to OFDM, due to laser phase noise and chromatic dispersion (CD). Additionally, it is shown that by employing frequency domain averaging technique to enhance the channel estimation (CE), the throughput of FBMC is significantly increased and consequently, a comparable performance is obtained for both waveforms. Furthermore, several coexistence scenarios for multi service transmission are studied, considering OFDM and FBMC based RATs to evaluate the impact inter band interference (IBI), due to power amplifier (PA) nonlinearity on the system performance. The low out of band (OOB) emission in FBMC plays an important role in minimising IBI to adjacent services. Therefore, FBMC requires less guardband in coexistence with multiple services in 5G fibre-wireless MFH. Conversely, OFDM introduced significant OOB to adjacent services requiring large guardband in multi-service coexistence transmission scenario. Finally, a novel transmission scheme is proposed and investigated to simultaneously generate multiple mmWave signals using laser heterodyning mmWave upconversion technique. With appropriate IF and optical frequency plan, several mmWave signals can be realised. Simulation results demonstrate successful simultaneous realisation of 28GHz, 38GHz, and 60GHz mmWave signals

PAPR Reduction Solutions for 5G and Beyond

The latest fifth generation (5G) wireless technology provides improved communication quality compared to earlier generations. The 5G New Radio (NR), specified by the 3rd Generation Partnership Project (3GPP), addresses the modern requirements of the wireless networks and targets improved communication quality in terms of for example peak data rates, latency and reliability. On the other hand, there are still various crucial issues that impact the implementation and energy-efficiency of 5G NR networks and their different deployments. The power-efficiency of transmitter power amplifiers (PAs) is one of these issues. The PA is an important unit of a communication system, which is responsible from amplifying the transmit signal towards the antenna. Reaching high PA power-efficiency is known to be difficult when the transmit waveform has a high peak-to-average power ratio (PAPR). The cyclic prefix (CP)-orthogonal frequencydivision multiplexing (OFDM) that is the main physical-layer waveform of 5G NR, suffers from such high PAPR challenge. There are generally many PAPR reduction methods proposed in the literature, however, many of these have either very notable computational complexity or impose substantial inband distortion. Moreover, 5G NR has new features that require redesigning the PAPR reduction methods. In line with these, the first contribution of this thesis is the novel frequencyselective PAPR reduction concept, where clipping noise is shaped in a frequencyselective manner over the active passband. This concept is in line with the 5G NR, where aggressive frequency-domain multiplexing is considered as an important feature. Utilizing the frequency-selective PAPR reduction enables the realization of the heterogeneous resource utilization within one passband. The second contribution of this thesis is the frequency-selective single-numerology (SN) and mixed-numerology (MN) PAPR reduction methods. The 5G NR targets utilizing different physical resource blocks (PRBs) and bandwidth parts (BWPs) within one passband flexibly. Yet, existing PAPR reduction methods do not exploit these features. Based on this, novel algorithms utilizing PRB and BWP level control of clipping noise are designed to meet error vector magnitude (EVM) limits of the modulations while reducing the PAPR. TheMNallocation has one critical challenge as inter numerology interference (INI) emerges after aggregation of subband signals. Proposed MN PAPR reduction algorithm overcomes this issue by cancelling INI within the PAPR reduction loop, which has not been considered earlier. The third contribution of this thesis is the proposal of two novel non-iterative PAPR reduction methods. First method utilizes the fast-convolution filteredOFDM (FC-F-OFDM) that has excellent spectral containment, and combines it with clipping. Moreover, clipping noise is also allocated to guard bands by filter passband extension (FPE) and clipping noise in out-of-band (OOB) regions is essentially filtered through FC filtering. The second method is the guard-tone reservation (GTR) which is applied to discrete Fourier transform-spread-OFDM (DFT-s-OFDM). Uniquely, GTR estimates the time domain peaks in data symbol domain before inverse fast Fourier transform (IFFT), and uses guard band tones for PAPR reduction. The fourth contribution of the thesis is the design of two novel machine learning (ML) algorithms that improve the drawbacks of frequency-selective PAPRreduction. The first ML algorithm, PAPRer, models the nonlinear relation between the PAPR target and the realized PAPR value. Then, it auto-tunes the optimal PAPR target and this way minimizes the realized PAPR. The second ML algorithm, one-shot clipping-and-filtering (OSCF), solves the complexity problem of iterative clipping and filtering (ICF)-like methods by generating proper approximated clipping noise signal after running only one iteration, leading to very efficient PAPR reduction. Finally, an over-arching contribution of this thesis is the experimental validation of the performance benefits of the proposed methods by considering realistic 5GNR uplink (UL) and downlink (DL) testbeds that include realistic PAs and associated hardware. It is very important to confirm the practical benefits of the proposed methods and, this is realized with the conducted experimental work

Joint compensation of I/Q impairments and PA nonlinearity in mobile broadband wireless transmitters

The main focus of this thesis is to develop and investigate a new possible solution for compensation of in-phase/quadrature-phase (I/Q) impairments and power amplifier (PA) nonlinearity in wireless transmitters using accurate, low complexity digital predistortion (DPD) technique. After analysing the distortion created by I/Q modulators and PAs together with nonlinear crosstalk effects in multi-branch multiple input multiple output (MIMO) wireless transmitters, a novel two-box model is proposed for eliminating those effects. The model is realised by implementing two phases which provide an optimisation of the identification of any system. Another improvement is the capability of higher performance of the system without increasing the computational complexity. Compared with conventional and recently proposed models, the approach developed in this thesis shows promising results in the linearisation of wireless transmitters. Furthermore, the two-box model is extended for concurrent dual-band wireless transmitters and it takes into account cross-modulation (CM) products. Besides, it uses independent processing blocks for both frequency bands and reduces the sampling rate requirements of converters (digital-to-analogue and analogue-to-digital). By using two phases for the implementation, the model enables a scaling down of the nonlinear order and the memory depth of the applied mathematical functions. This leads to a reduced computational complexity in comparison with recently developed models. The thesis provides experimental verification of the two-box model for multi-branch MIMO and concurrent dual-band wireless transmitters. Accordingly, the results ensure both the compensation of distortion and the performance evaluation of modern broadband wireless transmitters in terms of accuracy and complexity

Multiantenna Interference Mitigation Schemes and Resource Allocation for Cognitive Radio

Maximum and efficient utilization of available resources has been a central theme of research on various areas of science and engineering. Wireless communication is not an exception to this. With the rapid growth of wireless communication applications, radio frequency spectrum has become a valuable commodity. Supporting very high demands for data rate and throughput has become a challenging problem which requires innovative solutions. Dynamic spectrum sharing (DSS) based cognitive radio (CR) is envisioned as a promising technology for future wireless communication systems, such as fifth generation (5G) further development and sixth generation (6G). Extensive research has been done in the areas of CRs and it is considered to mitigate the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Spectrum sensing, which enables CRs to identify spectral holes, is a critical component in CR technology. Furthermore, improving the efficiency of the radio spectrum use through spectrum sensing and dynamic spectrum access (DSA) is one of the emerging trends. In the first part of this thesis, we focus on enhancing the spectrum usage of CR’s using interference cancellation methods that provides considerable performance gains with realistic computational complexity, especially, in the context of the widely used multicarrier waveforms. The primary focus is on interference rejection combining (IRC) methods, applied to the black-space cognitive radio (BS-CR). Earlier studies on the BS-CR in the literature were focused on using CRs as repeaters for the primary transmitter to guarantee that the CR is not causing significant interference to nearby primary users’ receivers. This kind of approaches are transmitter-centric in nature. In this thesis, receiver-centric approaches such as multi-antenna diversity combining, especially enhanced IRC methods, are considered and evaluated. IRC methods have been widely studied and adopted in several practical wireless communication systems. We focus on developing such BS-CR schemes under strong interference conditions, which has not been studied in the CR literature so far. Spatial covariance matrix estimation under mobility and high carrier frequencies is found to be the most critical part of such scheme. Algorithms and methods to mitigate these effects are developed in this thesis and they are evaluated under realistic BS-CR receiver operating conditions. We use sample covariance estimation approach with silent gaps in the CR transmisison. Covariance interpolation between silent gaps improves greatly the robustness with time-varying channels. Good link performance can be reached with low mobility at carrier frequency considered for the TV white-spaced case. The proposed BS-CR scheme could be feasible at below 6 GHz frequencies with pedestrian mobilities. The second part of this thesis investigates the effect of radio frequency (RF) impairments on the performance of the cognitive wireless communication. There are various unavoidable imperfections, mainly due to the limitations of analog high-frequency transmitter and receiver circuits. These imperfections include power amplifier (PA) non-linearities, receiver nonlinearities, and carrier frequency offset (CFO), which are considered in this study. These effects lead to significant signal distortion and, as a result of this, the wireless link quality may deteriorate. In multicarrier communications such signal distortions may lead to additional interference, and it is important to evaluate their effects on spectrum sensing quality and on the performance of the proposed BS-CR scheme. This part of the thesis provides critical analysis and insights into such issues caused by RF imperfections and demonstrates the need for designing proper compensation techniques required to avoid/reduce such degradations. It is found that the transmitter’s PA nonlinearities affect in the same way as in basic OFDM systems and BS-CR receiver’s linearity requirements are similar to those for advanced DSP-intensive software defined radios. The CR receiver’s CFO with respect to the PU has the most critical effect. However, synchronizing the CR with the needed high accuracy is considered achievable due to the PU signal’s high-power level. The final part of the thesis briefly looks at alternate waveforms and techniques that can be used in CRs. The filter bank multicarrier (FBMC) waveforms are considered as an alternative to the widely used OFDM schemes. Here the core idea is interference avoidance, targeting to reduce the interference leakage between CRs and the primary systems, by means of using a waveform with good spectrum localization properties. FBMC system’s performance is compared with OFDM based system in the context of CRs. The performance is compared from a combined spectrum sensing and resource allocation point of view through simulations. It is found that well-localized CR waveforms improve the CR link capacity, but with poorly localized primary signals, these possibilities are rather limited

I/Q Imbalance in Multiantenna Systems: Modeling, Analysis and RF-Aware Digital Beamforming

Wireless communications has experienced an unprecedented increase in data rates, numbers of active devices and selection of applications during recent years. However, this is expected to be just a start for future developments where a wireless connection is seen as a fundamental resource for almost any electrical device, no matter where and when it is operating. Since current radio technologies cannot provide such services with reasonable costs or even at all, a multitude of technological developments will be needed. One of the most important subjects, in addition to higher bandwidths and flexible network functionalities, is the exploitation of multiple antennas in base stations (BSs) as well as in user equipment (UEs). That kind of multiantenna communications can boost the capacity of an individual UE-BS link through spatial antenna multiplexing and increase the quality as well as robustness of the link via antenna diversity. Multiantenna technologies provide improvements also on the network level through spatial UE multiplexing and sophisticated interference management. Additionally, multiple antennas can provide savings in terms of the dissipated power since transmission and reception can be steered more efficiently in space, and thus power leakage to other directions is decreased. However, several issues need to be considered in order to get multiantenna technologies widely spread. First, antennas and the associated transceiver chains are required to be simple and implementable with low costs. Second, size of the antennas and transceivers need to be minimized. Finally, power consumption of the system must be kept under control. The importance of these requirements is even emphasized when considering massive multiple-input multiple-output (MIMO) systems consisting of devices equipped with tens or even hundreds of antennas.In this thesis, we consider multiantenna devices where the associated transceiver chains are implemented in such a way that the requirements above can be met. In particular, we focus on the direct-conversion transceiver principle which is seen as a promising radio architecture for multiantenna systems due to its low costs, small size, low power consumption and good flexibility. Whereas these aspects are very promising, direct-conversion transceivers have also some disadvantages and are vulnerable to certain imperfections in the analog radio frequency (RF) electronics in particular. Since the effects of these imperfections usually get even worse when optimizing costs of the devices, the scope of the thesis is on the effects and mitigation of one of the most severe RF imperfection, namely in-phase/quadrature (I/Q) imbalance.Contributions of the thesis can be split into two main themes. First of them is multiantenna narrowband beamforming under transmitter (TX) and receiver (RX) I/Q imbalances. We start by creating a model for the signals at the TX and RX, both under I/Q imbalances. Based on these models we derive analytical expressions for the antenna array radiation patterns and notice that I/Q imbalance distorts not only the signals but also the radiation characteristics of the array. After that, stemming from the nature of the distortion, we utilize widely-linear (WL) processing, where the signals and their complex conjugates are processed jointly, for the beamforming task under I/Q imbalance. Such WL processing with different kind of statistical and adaptive beamforming algorithms is finally shown to provide a flexible operation as well as distortion-free signals and radiation patterns when being under various I/Q imbalance schemes.The second theme extends the work to wideband systems utilizing orthogonal frequency-division multiplexing (OFDM)-based waveforms. The focus is on uplink communications and BS RX processing in a multiuser MIMO (MU-MIMO) scheme where spatial UE multiplexing is applied and further UE multiplexing takes place in frequency domain through the orthogonal frequency-division multiple access (OFDMA) principle. Moreover, we include the effects of external co-channel interference into our analysis in order to model the challenges in heterogeneous networks. We formulate a flexible signal model for a generic uplink scheme where I/Q imbalance occurs on both TX and RX sides. Based on the model, we analyze the signal distortion in frequency domain and develop augmented RX processing methods which process signals at mirror subcarrier pairs jointly. Additionally, the proposed augmented methods are numerically shown to outperform corresponding per-subcarrier method in terms of the instantaneous signal-to-interference-and-noise ratio (SINR). Finally, we address some practical aspects and conclude that the augmented processing principle is a promising tool for RX processing in multiantenna wideband systems under I/Q imbalance.The thesis provides important insight for development of future radio networks. In particular, the results can be used as such for implementing digital signal processing (DSP)-based RF impairment mitigation in real world transceivers. Moreover, the results can be used as a starting point for future research concerning, e.g., joint effects of multiple RF impairments and their mitigation in multiantenna systems. Overall, this thesis and the associated publications can help the communications society to reach the ambitious aim of flexible, low-cost and high performance radio networks in the future

Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World

Remotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challenge, but with a wide range of research opportunities. The ten contributions in this Special Issue have addressed the following four research topics: (1) Evapotranspiration estimation; (2) rainfall monitoring and prediction; (3) flood simulations and predictions; and (4) monitoring of ecohydrological processes using remote sensing techniques. Moreover, the authors have provided broader discussions on how to capitalize on state-of-the-art remote sensing techniques to improve hydrological model simulations and predictions, to enhance their skills in reproducing processes for the fast-changing world