Self Interference Cancellation In Full Duplex Wireless Systems

Due to the tremendous increase in wireless data traffic, one of the major challenges for future wireless systems is the utilization of the available spectrum to achieve better data rates over limited spectrum. Currently, systems operate in what is termed "Half Duplex Mode," where they are either transmitting or receiving, but never both using the same temporal and spectral resources. Full-duplex transmission promises to double the spectral efficiency where bidirectional communications is carried out over the same temporal and spectral resources. The main limitation impacting full-duplex transmission is managing the strong self-interference signal imposed by the transmit antenna on the receive antenna within the same transceiver. Several recent publications have demonstrated that the key challenge in practical full-duplex systems is un-cancelled self-interference power caused by a combination of hardware imperfections, especially Radio Frequency (RF) circuits' impairments. In this thesis, we consider the problem of self-interference cancellation in full-duplex systems. The ultimate goal of this work is to design and build a complete, real-time, full-duplex system that is capable of achieving wireless full-duplex transmission using practical hardware platforms. Since RF circuits' impairments are shown to have significant impact on the self-interference cancellation performance, first, we present a thorough analysis of the effect of RF impairments on the cancellation performance, with the aim of identifying the main performance limiting factors and bottlenecks. Second, the thesis proposes several impairments mitigation techniques to improve the overall self-interference cancellation capability by mitigating most of the transceiver RF impairments. In addition to impairments mitigation, two novel full-duplex transceiver architectures that achieve significant self-interference cancellation performance are proposed. The performance of the proposed techniques is analytically and experimentally investigated in practical wireless environments. Finally, the proposed self-interference cancellation techniques are used to build a complete full-duplex system with a 90\% experimentally proven full-duplex rate improvement compared to half-duplex systems.

This book introduces the development of self-interference (SI)-cancellation techniques for full-duplex wireless communication systems. The authors rely on estimation theory and signal processing to develop SI-cancellation algorithms by generating an estimate of the received SI and subtracting it from the received signal. The authors also cover two new SI-cancellation methods using the new concept of active signal injection (ASI) for full-duplex MIMO-OFDM systems. The ASI approach adds an appropriate cancelling signal to each transmitted signal such that the combined signals from transmit antennas attenuate the SI at the receive antennas. The authors illustrate that the SI-pre-cancelling signal does not affect the data-bearing signal. This book is for researchers and professionals working in wireless communications and engineers willing to understand the challenges of deploying full-duplex and practical solutions to implement a full-duplex system. Advanced-level students in electrical engineering and computer science studying wireless communications will also find this book useful as a secondary textbook.

Many wireless systems could benefit from the ability to transmit and receive on the same frequency at the same time, which is known as In-Band Full-Duplex (IBFD). This technology could lead to enhanced spectral efficiency for future wireless networks, such as fifth-generation New Radio (5G NR) and beyond, and could enable capabilities and applications that were previously considered impossible, such as IBFD with phased array systems. In this exciting new book, experts from industry, academic, and federal research institutions discuss the various approaches that can be taken to suppress the inherent self-interference that is generated in IBFD systems. Both static and adaptive techniques that span across the propagation, analog and digital domains are presented. Details and measured results that encompass high-isolation antenna designs, RF, and photonic cancellation as well as signal processing approaches, which include beamforming and linear/non-linear equalization are detailed. Throughout this book, state-of-the-art IBFD systems that utilize these technologies will be provided as practical examples for various applications. Expert IBFD perspectives from multiple research organizations and companies, which would provide readers with the most accurate state-of-the-art approaches. This is the first book that dives into both the techniques that make IBFD systems possible as well as several different applications that use IBFD technology.

"Full-duplex operation for wireless communications can potentially double the spectral efficiency, compared to half-duplex operation, by using the same wireless resource to transmit and receive at the cost of a large power difference between the high-power self-interference (SI) from its own transmitted signal and the low-power intended signal received from the other distant transceiver. The SI can be gradually reduced by a combination of radiofrequency (RF) and baseband cancellation stages. Each stage requires the estimation of the different distortions that the SI endures such as the SI channel and the transceiver nonlinearities. This thesis deals with the development of SI-cancellation techniques that are well-adapted to the full-duplex operation.First, we recognize the sparseness of the SI channel and exploit it to develop a compressedsensing (CS) based SI channel estimator. The obtained estimate is used to reduce the SI at the RF prior to the receiver low-noise amplifier and analog-to- digital converter to avoid overloading them. To further reduce the SI, a subspace-based algorithm is developed to jointly estimate the residual SI channel, the intended channel between the two transceivers and the transmitter nonlinearities for the baseband cancellation stage. Including the unknown received intended signal in the estimation process represents the main advantage of the proposed algorithm compared to previous data-aided estimators that assume the intended signal as additive noise. By using the second-order statistics of the received signal, it is possible to obtain the noise subspace and then to estimate the different coefficients without knowing the intended signal. Depending on the number of transmit and receive antennas, we propose to use either the received signal or a combination of the received signal and its complex conjugate. Also, we develop a semi-blind maximum likelihood (ML) estimator that combines the known pilot and unknown data symbols from the intended transceiver to formulate the likelihood function. A closed-form expression of the ML solution is first derived, and an iterative procedure is developed to further improve the estimation performance at moderate to high signal-to-noise ratio. Simulations show significant improvement in SI-cancellation gain compared to the data-aided estimators. Moreover, we present two new SI-cancellation methods using active signal injection (ASI) for full-duplex MIMO-OFDM systems. The ASI approach adds an appropriate cancelling signal to each transmitted signal such that the combined signals from transmit antennas attenuate the SI at the receive antennas. In the first method, the SI-pre-cancelling signal uses some reserved subcarriers which do not carry data. In the second method, the constellation points are dynamically extended within the constellation boundary in order to minimize the received SI. Thus, the SI-pre-cancelling signal does not affect the data-bearing signal. Simulation results show that the proposed methods considerably reduce the SI at a modest computational complexity." --

With fast increasing demand of the wireless network, the current spectrum used for commercial wireless communication becomes very crowed. So it is critical to find an more efficient way to make the limited spectrum provide larger capacity and throughput. Full-duplex communication technology has caused much attention in the past ten years since it can double the spectrum efficiency theoretically. While the main challenge obstructing it promoting into the market is the self-interference problem in a full duplex system. This dissertation focus on the self-interference cancellation (SIC) theories. The RF impairments occurred in the practical full-duplex system will be discussed. Among them, the phase noise and I/Q imbalance are regarded as the bottleneck of the self-interference cancellation and a detailed analyzing will be included in this dissertation. The general self-interference cancellation methods can be divided into passive self-interference cancellation and active self-interference cancellation where the active cancellation can be further divided into digital cancellation, analog cancellation and hybrid cancellation. This dissertation will review the theories of the passive and active self-interference cancellation. For the analog cancellation, two models (quadratic model and affine model) will be explored to handle the I/Q imbalance and phase noise. Both of these two models are based on the blind tuning algorithm which has two procedures: training and optimizing. This dissertation will introduce the development of the algorithm. It contains the computer simulation results as well as the hardware experimental results to prove the validation of the proposed ideas.

This book constitutes the refereed proceedings of the 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, held in Costa de Caparica, Portugal, in July 2020. The 20 full papers and 24 short papers presented were carefully reviewed and selected from 91 submissions. The papers present selected results produced in engineering doctoral programs and focus on technological innovation for industry and service systems. Research results and ongoing work are presented, illustrated and discussed in the following areas: collaborative networks; decisions systems; analysis and synthesis algorithms; communication systems; optimization systems; digital twins and smart manufacturing; power systems; energy control; power transportation; biomedical analysis and diagnosis; and instrumentation in health.

This book focuses on the multidisciplinary state-of-the-art of full-duplex wireless communications and applications. Moreover, this book contributes with an overview of the fundamentals of full-duplex communications, and introduces the most recent advances in self-interference cancellation from antenna design to digital domain. Moreover, the reader will discover analytical and empirical models to deal with residual self-interference and to assess its effects in various scenarios and applications. Therefore, this is a highly informative and carefully presented book by the leading scientists in the area, providing a comprehensive overview of full-duplex technology from the perspective of various researchers, and research groups worldwide. This book is designed for researchers and professionals working in wireless communications and engineers willing to understand the challenges and solutions full-duplex communication so to implement a full-duplex system.

"Full-duplex (FD) wireless communications can potentially double the spectral efficiency by transmitting and receiving simultaneously over the same frequency at a cost of a large power difference between the high-power self-interference (SI), and the low-power intended signal received from the remote transmitter. SI can be reduced gradually by a combination of radio-frequency (RF) and baseband SI-cancellation stages. Each stage requires the estimation of various distortions that the SI endures, such as SI-channel and transceiver nonlinearities. This thesis deals with the development of SI-cancellation techniques that are well adapted to FD operations.We address SI-cancellation for FD operations in the presence of imperfect RF components. In particular, we develop a new scheme to jointly estimate the IQ mixer imbalance, power amplifier (PA) nonlinearities, up-/down-conversion phase-noise and SI-channel. First, we study and develop a baseband model that captures the most significant transceiver RF imperfections, for both separate- and common-oscillator structures used in the up- and down-conversions. A basis expansion model (BEM) is then derived to approximate the time-varying phase-noise, and to transform the problem of estimating the time-varying phase-noise into the estimation of a set of static coefficients. Using the method of maximum likelihood (ML) criterion, the likelihood function is derived in the presence of the unknown intended signal, which leads to the joint estimation of the intended channel, the SI-channel, the nonlinear impairments and the phase-noise. When the intended signal is unknown, an iterative procedure is developed to find the ML estimate of the different parameters based on its own known transmitted data, the known pilot symbols, and the statistic of the unknown intended signal received from the intended transmitter. We consider the two pilot-insertion structures used in LTE for the frequency-multiplexed pilots and the time-multiplexed pilots. Compared to training-based techniques, the full use of the received signal significantly reduces the required number of pilot symbols. Simulation results indicate that the proposed algorithms can offer a superior SI-cancellation performance, with the resulting signal-to-SI-and-noise ratio (SINR) being very close to the signal-to-noise ratio (SNR).Moreover, we study the power of SI after each cancellation stage, taking into account the transceiver impairments. One SI-cancellation scheme, which combines antenna cancellation, RF cancellation and digital cancellation, provides results from real world experiments that show the feasibility of an FD design. In general, it is difficult to assess the exact level of the SI reduction that is obtainable due to the interactions among factors such as transceiver impairments, wireless propagation channel and estimation error. We hereby identify the main factors that affect the cancellation performance. This allows for a better understanding of the obtained performance, and leads to the development of new methods that improves the cancellation capability of FD systems. We address the impact of each transceiver impairment in FD systems, and specify the limiting factors of the RF and baseband SI-cancellation stages for a given architecture. In addition, we demonstrate that reducing the SI before the LNA/ADC, via the RF SI-cancellation stage is necessary to avoid high quantization noise from the ADC. The analysis further reveals that the transmitter nonlinearities need to be modeled and canceled in the baseband SI-cancellation stage. Finally, in light of our simulation results, we discuss the trade-off between the amount of SI-cancellation and the number of cancellation stages, and propose the potential case scenarios for operations with one digital cancellation." --

To enable experimental characterization of full-duplex MAC layer algorithms, a cross-layered software-defined full-duplex radio testbed has been developed. In collaboration with researchers from the field of micro-electro-mechanical systems, we demonstrate a multi-band frequency-division duplexing system using a cavity-filter-based tunable duplexer and our integrated widely-tunable self-interference-cancelling receiver.

A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.