Basis Function Selection of Frequency-Domain Hammerstein Self-Interference Canceller for In-Band Full-Duplex Wireless Communications

This paper presents a basis function selection technique of a frequency-domain Hammerstein digital selfinterference canceller for in-band full-duplex communications. The power spectral density (PSD) of the nonlinear selfinterference signal is theoretically analyzed in detail, and a nonlinear self-interference PSD estimation method is developed. The proposed selection technique decides on the basis functions necessary for cancellation and relaxes the computational cost of the frequency-domain Hammerstein canceller based on the estimated PSD of the self-interference of each basis function. Furthermore, the convergence performance of the canceller is improved by the proposed selection technique. Simulation results are then presented, showing that the proposed technique can achieve similar cancellation performance compared with the original frequency-domain Hammerstein canceller and a time-domain nonlinear canceller. Additionally, it is shown that the proposed technique improves the computational cost and the convergence performance of the original frequency-domain Hammerstein canceller

Aperture-Level Simultaneous Transmit and Receive (STAR) with Digital Phased Arrays

In the signal processing community, it has long been assumed that transmitting and receiving useful signals at the same time in the same frequency band at the same physical location was impossible. A number of insights in antenna design, analog hardware, and digital signal processing have allowed researchers to achieve simultaneous transmit and receive (STAR) capability, sometimes also referred to as in-band full-duplex (IBFD). All STAR systems must mitigate the interference in the receive channel caused by the signals emitted by the system. This poses a significant challenge because of the immense disparity in the power of the transmitted and received signals. As an analogy, imagine a person that wanted to be able to hear a whisper from across the room while screaming at the top of their lungs. The sound of their own voice would completely drown out the whisper. Approaches to increasing the isolation between the transmit and receive channels of a system attempt to successively reduce the magnitude of the transmitted interference at various points in the received signal processing chain. Many researchers believe that STAR cannot be achieved practically without some combination of modified antennas, analog self-interference cancellation hardware, digital adaptive beamforming, and digital self-interference cancellation. The aperture-level simultaneous transmit and receive (ALSTAR) paradigm confronts that assumption by creating isolation between transmit and receive subarrays in a phased array using only digital adaptive transmit and receive beamforming and digital self-interference cancellation. This dissertation explores the boundaries of performance for the ALSTAR architecture both in terms of isolation and in terms of spatial imaging resolution. It also makes significant strides towards practical ALSTAR implementation by determining the performance capabilities and computational costs of an adaptive beamforming and self-interference cancellation implementation inspired by the mathematical structure of the isolation performance limits and designed for real-time operation

Modeling and Digital Mitigation of Transmitter Imperfections in Radio Communication Systems

To satisfy the continuously growing demands for higher data rates, modern radio communication systems employ larger bandwidths and more complex waveforms. Furthermore, radio devices are expected to support a rich mixture of standards such as cellular networks, wireless local-area networks, wireless personal area networks, positioning and navigation systems, etc. In general, a "smart'' device should be flexible to support all these requirements while being portable, cheap, and energy efficient. These seemingly conflicting expectations impose stringent radio frequency (RF) design challenges which, in turn, call for their proper understanding as well as developing cost-effective solutions to address them. The direct-conversion transceiver architecture is an appealing analog front-end for flexible and multi-standard radio systems. However, it is sensitive to various circuit impairments, and modern communication systems based on multi-carrier waveforms such as Orthogonal Frequency Division Multiplexing (OFDM) and Orthogonal Frequency Division Multiple Access (OFDMA) are particularly vulnerable to RF front-end non-idealities.This thesis addresses the modeling and digital mitigation of selected transmitter (TX) RF impairments in radio communication devices. The contributions can be divided into two areas. First, new modeling and digital mitigation techniques are proposed for two essential front-end impairments in direct-conversion architecture-based OFDM and OFDMA systems, namely inphase and quadrature phase (I/Q) imbalance and carrier frequency offset (CFO). Both joint and de-coupled estimation and compensation schemes for frequency-selective TX I/Q imbalance and channel distortions are proposed for OFDM systems, to be adopted on the receiver side. Then, in the context of uplink OFDMA and Single Carrier FDMA (SC-FDMA), which are the air interface technologies of the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) and LTE-Advanced systems, joint estimation and equalization techniques of RF impairments and channel distortions are proposed. Here, the challenging multi-user uplink scenario with unequal received power levels is investigated where I/Q imbalance causes inter-user interference. A joint mirror subcarrier processing-based minimum mean-square error (MMSE) equalizer with an arbitrary number of receiver antennas is formulated to effectively handle the mirror sub-band users of different power levels. Furthermore, the joint channel and impairments filter responses are efficiently approximated with polynomial-based basis function models, and the parameters of basis functions are estimated with the reference signals conforming to the LTE uplink sub-frame structure. The resulting receiver concept adopting the proposed techniques enables improved link performance without modifying the design of RF transceivers.Second, digital baseband mitigation solutions are developed for the TX leakage signal-induced self-interference in frequency division duplex (FDD) transceivers. In FDD transceivers, a duplexer is used to connect the TX and receiver (RX) chains to a common antenna while also providing isolation to the receiver chain against the powerful transmit signal. In general, the continuous miniaturization of hardware and adoption of larger bandwidths through carrier aggregation type noncontiguous allocations complicates achieving sufficient TX-RX isolation. Here, two different effects of the transmitter leakage signal are investigated. The first is TX out-of-band (OOB) emissions and TX spurious emissions at own receiver band, due to the transmitter nonlinearity, and the second is nonlinearity of down-converter in the RX that generates second-order intermodulation distortion (IMD2) due to the TX in-band leakage signal. This work shows that the transmitter leakage signal-induced interference depends on an equivalent leakage channel that models the TX path non-idealities, duplexer filter responses, and the RX path non-idealities. The work proposes algorithms that operate in the digital baseband of the transceiver to estimate the TX-RX non-idealities and the duplexer filter responses, and subsequently regenerating and canceling the self-interference, thereby potentially relaxing the TX-RX isolation requirements as well as increasing the transceiver flexibility.Overall, this thesis provides useful signal models to understand the implications of different RF non-idealities and proposes compensation solutions to cope with certain RF impairments. This is complemented with extensive computer simulations and practical RF measurements to validate their application in real-world radio transceivers

Architectures, Antennas and Circuits for Millimeter-wave Wireless Full-Duplex Applications

Demand for wireless network capacity keeps growing exponentially every year, as a result a 1000-fold increase in data traffic is projected over the next 10 years in the context of 5G wireless networks. Solutions for delivering the 1000-fold increase in capacity fall into three main categories: deploying smaller cells, allocating more spectrum and improving spectral efficiency of wireless systems. Smaller cells at RF frequencies (1-6GHz) are unlikely to deliver the demanded capacity increase. On the other hand, millimeter-wave spectrum (frequencies over 24GHz) offers wider, multi-GHz channel bandwidths, and therefore has gained significant research interest as one of the most promising solutions to address the data traffic demands of 5G. Another disruptive technology is full-duplex which breaks a century-old assumption in wireless communication, by simultaneous transmission and reception on the same frequency channel. In doing so, full-duplex offers many benefits for wireless networks, including an immediate spectral efficiency improvement in the physical layer. Although FD promises great benefits, self-interference from the transmitter to its own receiver poses a fundamental challenge. The self-interference can be more than a billion times stronger than the desired signal and must be suppressed below the receiver noise floor. In recent years, there has been some research efforts on fully-integrated full-duplex RF transceivers, but mm-wave fully-integrated full-duplex systems, are still in their infancy. This dissertation presents novel architectures, antenna and circuit techniques to merge two exciting technologies, mm-wave and full-duplex, which can potentially offer the dual benefits of wide bandwidths and improved spectral efficiency. To this end, two different antenna interfaces, namely a wideband reconfigurable T/R antenna pair with polarization-based antenna cancellation and an mm-wave fully-integrated magnetic-free non-reciprocal circulator, are presented. The polarization-based antenna cancellation is employed in conjunction with the RF and digital cancellation to design a 60GHz full-duplex 45nm SOI CMOS transceiver with nearly 80dB self-interference suppression. The concepts and prototypes presented in this dissertation have also profound implications for emerging applications such as vehicular radars, 5G small-cell base-stations and virtual reality

Variants of partial update augmented CLMS algorithm and their performance analysis

Naturally complex-valued information or those presented in complex domain are effectively processed by an augmented complex least-mean-square (ACLMS) algorithm. In some applications, the ACLMS algorithm may be too computationally and memory-intensive to implement. In this paper, a new algorithm, termed partial-update ACLMS (PU-ACLMS) algorithm is proposed, where only a fraction of the coefficient set is selected to update at each iteration. Doing so, two types of partial update schemes are presented referred to as the sequential and stochastic partial-updates, to reduce computational load and power consumption in the corresponding adaptive filter. The computational cost for full-update PU-ACLMS and its partial update implementations are discussed. Next, the steady-state mean and mean-square performance of PU-ACLMS for noncircular complex signals are analyzed and closed-form expressions of the steady-state excess mean-square error (EMSE) and mean-square deviation (MSD) are given. Then, employing the weighted energy-conservation relation, the EMSE and MSD learning curves are derived. The simulation results are verified and compared with those of theoretical predictions through numerical examples

TRANSMISSION PERFORMANCE OPTIMIZATION IN FIBER-WIRELESS ACCESS NETWORKS USING MACHINE LEARNING TECHNIQUES

The objective of this dissertation is to enhance the transmission performance in the fiber-wireless access network through mitigating the vital system limitations of both analog radio over fiber (A-RoF) and digital radio over fiber (D-RoF), with machine learning techniques being systematically implemented. The first thrust is improving the spectral efficiency for the optical transmission in the D-RoF to support the delivery of the massive number of bits from digitized radio signals. Advanced digital modulation schemes like PAM8, discrete multi-tone (DMT), and probabilistic shaping are investigated and implemented, while they may introduce severe nonlinear impairments on the low-cost optical intensity-modulation-direct-detection (IMDD) based D-RoF link with a limited dynamic range. An efficient deep neural network (DNN) equalizer/decoder to mitigate the nonlinear degradation is therefore designed and experimentally verified. Besides, we design a neural network based digital predistortion (DPD) to mitigate the nonlinear impairments from the whole link, which can be integrated into a transmitter with more processing resources and power than a receiver in an access network. Another thrust is to proactively mitigate the complex interferences in radio access networks (RANs). The composition of signals from different licensed systems and unlicensed transmitters creates an unprecedently complex interference environment that cannot be solved by conventional pre-defined network planning. In response to the challenges, a proactive interference avoidance scheme using reinforcement learning is proposed and experimentally verified in a mmWave-over-fiber platform. Except for the external sources, the interference may arise internally from a local transmitter as the self-interference (SI) that occupies the same time and frequency block as the signal of interest (SOI). Different from the conventional subtraction-based SI cancellation scheme, we design an efficient dual-inputs DNN (DI-DNN) based canceller which simultaneously cancels the SI and recovers the SOI.Ph.D

Compensation of Physical Impairments in Multi-Carrier Communications

Among various multi-carrier transmission techniques, orthogonal frequency-division multiplexing (OFDM) is currently a popular choice in many wireless communication systems. This is mainly due to its numerous advantages, including resistance to multi-path distortions by using the cyclic prefix (CP) and a simple one-tap channel equalization, and efficient implementations based on the fast Fourier and inverse Fourier transforms. However, OFDM also has disadvantages which limit its use in some applications. First, the high out-of-band (OOB) emission in OFDM due to the inherent rectangular shaping filters poses a challenge for opportunistic and dynamic spectrum access where multiple users are sharing a limited transmission bandwidth. Second, a strict orthogonal synchronization between sub-carriers makes OFDM less attractive in low-power communication systems. Furthermore, the use of the CP in OFDM reduces the spectral efficiency and thus it may not be suitable for short-packet and low-latency transmission applications. Generalized frequency division multiplexing (GFDM) and circular filter-bank multi-carrier offset quadrature amplitude modulation (CFBMC-OQAM) have recently been considered as alternatives to OFDM for the air interface of wireless communication systems because they can overcome certain disadvantages in OFDM. Specifically, these two systems offer a flexibility in choosing the shaping filters so that the high OOB emission in OFDM can be avoided. Moreover, the strict orthogonality requirement in OFDM is relaxed in GFDM and CFBMC-OQAM which are, respectively, non-orthogonal and real-field orthogonal systems. Although a CP is also used in these two systems, the CP is added for a block of many symbols instead of only one symbol as in OFDM, which, therefore, improves the spectral efficiency. Given that the performance of a wireless communication system is affected by various physical impairments such as phase noise (PN), in-phase and quadrature (IQ) imbalance and imperfect channel estimation, this thesis proposes a number of novel signal processing algorithms to compensate for physical impairments in multi-carrier communication systems, including OFDM, GFDM and CFBMC-OQAM. The first part of the thesis examines the use of OFDM in full-duplex (FD) communication under the presence of PN, IQ imbalance and nonlinearities. FD communication is a promising technique since it can potentially double the spectral efficiency of the conventional half-duplex (HD) technique. However, the main challenge in implementing an FD wireless device is to cope with the self-interference (SI) imposed by the device's own transmission. The implementation of SI cancellation (SIC) faces many technical issues due to the physical impairments. In this part of research, an iterative algorithm is proposed in which the SI cancellation and detection of the desired signal benefit from each other. Specifically, in each iteration, the SI cancellation performs a widely linear estimation of the SI channel and compensates for the physical impairments to improve the detection performance of the desired signal. The detected desired signal is in turn removed from the received signal to improve SI channel estimation and SI cancellation in the next iteration. Results obtained show that the proposed algorithm significantly outperforms existing algorithms in SI cancellation and detection of the desired signal. In the next part of the thesis, the impact of PN and its compensation for CFBMC-OQAM systems are considered. The sources of performance degradation are first quantified. Then, a two-stage PN compensation algorithm is proposed. In the first stage, the channel frequency response and PN are estimated based on the transmission of a preamble, which is designed to minimize the channel mean squared error (MSE). In the second stage the PN compensation is performed using the estimate obtained from the first stage together with the transmitted pilot symbols. Simulation results obtained under practical scenarios show that the proposed algorithm effectively estimates the channel frequency response and compensates for the PN. The proposed algorithm is also shown to outperform an existing algorithm that implements iterative PN compensation when the PN impact is high. As a further development from the second part, the third part of the thesis considers the impacts of both PN and IQ imbalance and proposes a unified two-stage compensation algorithm for a general multi-carrier system, which can include OFDM, GFDM and CFBMC-OQAM. Specifically, in the first stage, the channel impulse response and IQ imbalance parameters are first estimated based on the transmission of a preamble. Given the estimates obtained from the first stage, in the second stage the IQ imbalance and PN are compensated in that order based on the pilot symbols for the rest of data transmission blocks. The preamble is designed such that the estimation of IQ imbalance does not depend on the channel and PN estimation errors. The proposed algorithm is then further extended to a multiple-input multiple-output (MIMO) system. For such a MIMO system, the preamble design is generalized so that the multiple IQ imbalances as well as channel impulse responses can be effectively estimated based on a single preamble block. Simulation results are presented and discussed in a variety of scenarios to show the effectiveness of the proposed algorithm