Performance and Compensation of I/Q Imbalance in Differential STBC-OFDM

Differential space time block coding (STBC) achieves full spatial diversity and avoids channel estimation overhead. Over highly frequency-selective channels, STBC is integrated with orthogonal frequency division multiplexing (OFDM) to achieve high performance. However, low-cost implementation of differential STBC-OFDM using direct-conversion transceivers is sensitive to In-phase/Quadrature-phase imbalance (IQI). In this paper, we quantify the performance impact of IQI at the receiver front-end on differential STBC-OFDM systems and propose a compensation algorithm to mitigate its effect. The proposed receiver IQI compensation works in an adaptive decision-directed manner without using known pilots or training sequences, which reduces the rate loss due to training overhead. Our numerical results show that our proposed compensation algorithm can effectively mitigate receive IQI in differential STBC-OFDM.Comment: 7 pages, 2 figures, IEEE GLOBECOM 201

Feasibility of In-band Full-Duplex Radio Transceivers with Imperfect RF Components: Analysis and Enhanced Cancellation Algorithms

In this paper we provide an overview regarding the feasibility of in-band full-duplex transceivers under imperfect RF components. We utilize results and findings from the recent research on full-duplex communications, while introducing also transmitter-induced thermal noise into the analysis. This means that the model of the RF impairments used in this paper is the most comprehensive thus far. By assuming realistic parameter values for the different transceiver components, it is shown that IQ imaging and transmitter-induced nonlinearities are the most significant sources of distortion in in-band full-duplex transceivers, in addition to linear self-interference. Motivated by this, we propose a novel augmented nonlinear digital self-interference canceller that is able to model and hence suppress all the essential transmitter imperfections jointly. This is also verified and demonstrated by extensive waveform simulations.Comment: 7 pages, presented in the CROWNCOM 2014 conferenc

Learning Robust Radio Frequency Fingerprints Using Deep Convolutional Neural Networks

Radio Frequency Fingerprinting (RFF) techniques, which attribute uniquely identifiable signal distortions to emitters via Machine Learning (ML) classifiers, are limited by fingerprint variability under different operational conditions. First, this work studied the effect of frequency channel for typical RFF techniques. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models leads to deterioration in MCC to under 0.05 (random guess), indicating that single-channel models are inadequate for realistic operation. Second, this work presented a novel way of studying fingerprint variability through Fingerprint Extraction through Distortion Reconstruction (FEDR), a neural network-based approach for quantifying signal distortions in a relative distortion latent space. Coupled with a Dense network, FEDR fingerprints were evaluated against common RFF techniques for up to 100 unseen classes, where FEDR achieved best performance with MCC ranging from 0.945 (5 classes) to 0.746 (100 classes), using 73% fewer training parameters than the next-best technique

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

Single carrier frequency domain equalization and energy efficiency optimization for MIMO cognitive radio.

This dissertation studies two separate topics in wireless communication systems. One topic focuses on the Single Carrier Frequency Domain Equalization (SC-FDE), which is a promising technique to mitigate the multipath effect in the broadband wireless communication. Another topic targets on the energy efficiency optimization in a multiple input multiple output (MIMO) cognitive radio network. For SC-FDE, the conventional linear receivers suffer from the noise amplification in deep fading channel. To overcome this, a fractional spaced frequency domain (FSFD) receiver based on frequency domain oversampling (FDO) is proposed for SC-FDE to improve the performance of the linear receiver under deep fading channels. By properly designing the guard interval, a larger sized Discrete Fourier Transform (DFT) is equipped to oversample the received signal in frequency domain. Thus, the effect of frequency-selective fading can still be eliminated by a one-tap frequency domain filter. Two types of FSFD receivers are proposed based on the least square (LS) and minimum mean square error (MMSE) criterion. Both the semi-analytical analysis and simulation results are given to evaluate the performance of the proposed receivers. Another challenge in SC-FDE is the in-phase/quadrature phase (IQ) imbalance caused by unideal radio frequency (RF) front-end at the transmitter or the receiver. Most existing works in single carrier transmission employ linear compensation methods, such as LS and MMSE, to combat the interference caused by IQ imbalance. Actually, for single carrier transmissions, it is possible for the receivers to adopt advanced nonlinear compensation methods to improve the system performance under IQ imbalance. For such purpose, an iterative decision feedback receiver is proposed to compensate the IQ imbalance caused by unideal RF front-end in SC-FDE. Numerical results show that the proposed iterative IQ imbalance compensation can significantly improve the performance of SC-FDE system under IQ imbalance compared with the conventional linear method. For the energy efficiency optimization in the MIMO cognitive radio network, multiple secondary users (SUs) coexisting with a primary user (PU) adjust their antenna radiation patterns and power allocations to achieve energy-efficient transmission. The optimization problems are formulated to maximize the energy efficiency of a cognitive radio network in both distributed and centralized point of views. Also, constraints on the transmission power and the interference to PU are introduced to protect the PU’s transmission. In order to solve the non-convex optimization problems, convex relaxations are used to transform them into equivalent problems with better tractability. Then three optimization algorithms are proposed to find the energy-efficient transmission strategies. Simulation results show that the proposed energy-efficiency optimization algorithms outperform the existing algorithms