Low-Complexity Sub-band Digital Predistortion for Spurious Emission Suppression in Noncontiguous Spectrum Access

Noncontiguous transmission schemes combined with high power-efficiency requirements pose big challenges for radio transmitter and power amplifier (PA) design and implementation. Due to the nonlinear nature of the PA, severe unwanted emissions can occur, which can potentially interfere with neighboring channel signals or even desensitize the own receiver in frequency division duplexing (FDD) transceivers. In this article, to suppress such unwanted emissions, a low-complexity sub-band DPD solution, specifically tailored for spectrally noncontiguous transmission schemes in low-cost devices, is proposed. The proposed technique aims at mitigating only the selected spurious intermodulation distortion components at the PA output, hence allowing for substantially reduced processing complexity compared to classical linearization solutions. Furthermore, novel decorrelation based parameter learning solutions are also proposed and formulated, which offer reduced computing complexity in parameter estimation as well as the ability to track time-varying features adaptively. Comprehensive simulation and RF measurement results are provided, using a commercial LTE-Advanced mobile PA, to evaluate and validate the effectiveness of the proposed solution in real world scenarios. The obtained results demonstrate that highly efficient spurious component suppression can be obtained using the proposed solutions

Reduced-complexity Digital Predistortion in Flexible Radio Spectrum Access

Wireless communications is nowadays seen as one of the main foundations of technological advancements in, e.g., healthcare, education, agriculture, transportation, computing, personal communications, media, and entertainment. This requires major technological developments and advances at different levels of the wireless communication systems and networks. In particular, it is required to utilize the currently available frequency spectrum in a more and more efficient way, while also adopting new spectral bands. Moreover, it is required that cheaper and smaller electronic components are used to build future wireless communication systems to facilitate increasingly cost-effective solutions. Meanwhile, energy efficiency becomes extremely important in wide scale deployments of the networks both from a running cost point of view, and from an environmental impact point of view. This is the big picture, or the so called ‘bird’s eye view’ of the challenges that are yet to be met in this very interesting and fast developing field of science.The power amplifier (PA) is the most power-hungry component in most RF transmitters. Consequently, its energy efficiency significantly contributes to the overall energy efficiency of the transmitter, and in fact the whole wireless network. Unfortunately, energy efficiency enhancement implies operating the PA closer to its saturation region, which typically results in severe nonlinear distortion that can deteriorate the signal quality and cause interference to neighboring users, both of which negatively impact the system spectral efficiency. Moreover, in flexible spectrum access scenarios, which are essential for improving the spectral efficiency, particular in the form of non-contiguous radio spectrum access, the nonlinear distortion due to the PA becomes even more severe and can significantly impact the overall network performance. For example, in noncontiguous carrier aggregation (CA) in LTE-Advanced, it has been demonstrated that in addition to the classical in-band distortion and regrowth around the main carriers, harmful spurious emission components are generated which can easily violate the spurious emission limits even in the case of user equipment (UE) transmitters.Technological advances in the digital electronics domain have enabled us to approach this problem from a digital signal processing point of view in the form of widely-adopted and researched digital predistortion (DPD) technology. However, when the signal bandwidth gets larger, and flexible or non-contiguous spectrum access is introduced, the complexity of the DPD increases and the power consumed in the digital domain by the DPD itself becomes higher and higher, to the extent that it might be close to, or even surpass, the energy savings achieved from using a more efficient PA. The problem becomes even more challenging at the UE side which has relatively limited computational capabilities and lower transmit power. This dilemma can be resolved by developing novel reduced-complexity DPD solutions in such flexible spectrum access and/or wide bandwidth scenarios while not sacrificing the DPD performance, which is the main topic area that this thesis work contributes to.The first contribution of this thesis is the development of a spur-injection based sub-band DPD structure for spurious emission mitigation in noncontiguous transmission scenarios. A novel and effective learning algorithm is also introduced, for the proposed sub-band DPD, based on the decorrelation principle. Mathematical models of the unwanted emissions are formulated based on realistic PA models with memory, followed by developing an efficient DPD structure for mitigating these emissions with reducedcomplexity in both the DPD main processing and learning paths while providing excellent spurious emission suppression. In the special case when the spurious emissions overlap with the own RX band in frequency division duplexing (FDD) transceivers, a novel subband DPD solution is also developed that uses the main RX for DPD learning without requiring any additional observation RX, thus further reducing the DPD complexity.The second contribution is the development of a novel reduced-complexity concurrent DPD, with a single-feedback receiver path, for carrier aggregation-like scenarios. The proposed solution is based on a simple and flexible DPD structure with decorrelationbased parameter learning. Practical simulations and RF measurements demonstrate that the proposed concurrent DPD provides excellent linearization performance, in terms of in-band error vector magnitude (EVM) and adjacent channel leakage ratio (ACLR), when compared to state-of-the-art concurrent DPD solutions, despite its reduced computational complexity in both the DPD main path processing and parameter learning.The third contribution is the development of a new and novel frequency-optimized DPD solution which can tailor its linearization capabilities to any particular regions of the spectrum. Detailed mathematical expressions of the power spectrum at the PA output as a function of the DPD coefficients are formulated. A Newton-Raphson optimization routine is then utilized to optimize the suppression of unwanted emissions at arbitrary pre-specified frequencies at the PA output. From a complexity reduction perspective, this means that for a given linearization performance at a particular frequency range, an optimized and reduced-complexity DPD can be used.Detailed quantitative complexity analysis, of all the proposed DPD solutions, is performed in this thesis. The complexity and linearization performance are also compared to state-of-the-art DPD solutions in the literature to validate and demonstrate the complexity reduction aspect without sacrificing the linearization performance. Moreover, all the DPD solutions developed in this thesis are tested in practical RF environments using real cellular power amplifiers that are commercially used in the latest wireless communication systems, both at the base station side and at the mobile terminal side. These experiments, along with the strong theoretical foundation of the developed DPD solutions prove that they can be commercially used as such to enhance the performance, energy efficiency, and cost effectiveness of next generation wireless transmitters

Bandlimited Digital Predistortion of Wideband RF Power Amplifiers

The increase in the demand for high data rates has led to the deployment of wider bandwidths and complex waveforms in wireless communication systems. Multicarrier waveforms such as orthogonal frequency division multiplexing (OFDM) employed in modern systems are very sensitive to the transmitter chain nonidealities due to their high peak-to-average-power-ratio (PAPR) characteristic. They are therefore affected by nonlinear transmitter components particularly the power amplifier (PA). Moreover, to enhance power efficiency, PAs typically operate near saturation region and hence become more nonlinear. Power efficiency is highly desirable especially in battery powered and portable devices as well as in base stations. Hence there is a clear need for efficient linearization algorthms which improve power efficiency while maintaining high spectral efficiency. Digital predistortion (DPD) has been recognized as one of the most effective methods in mitigating PA nonlinear distortions. The method involves the application of inverse PA nonlinear function upstream of the PA such that the overall system output has a linear amplification. The computation of the nonlinearity profile and the inversion of the PA function are particularly difficult and complicated especially when involving wideband radio access waveforms, and therefore memory effects, which are being employed in modern communication systems, such as in Long Term Evolution/Advanced (LTE/LTE-A). In the recent technical literature, different approaches which focus on the linearization of specific frequency bands or sub-bands only have been developed to alleviate this problem, thereby reducing the complexity of DPD. In this thesis, we focus on the development and characterization of a bandlimited DPD solution specifically tailored towards the linearization at and around the main carrier(s) in single carrier deployment or contiguous carrier aggregation of two or more component carriers. In terms of parameter identification, the solution is based on the reduced-complexity closed-loop decorrelation-based parameter learning principle, which is also able to track time-varying changes in the transmitter components adaptively. The proposed bandlimited solution is designed to linearize the inband and out-of-band (OOB) distortions in the immediate vicinity of the main carrier(s) while assuming the distortions more far away in the spectrum are suppressed by transmit or duplex filters. This is implemented using FIR filters to limit the bandwidth expansion during basis functions generation and to restrain the bandwidth of the feedback observation signal, thus reducing the DPD sample rates in both the main path processing and the parameter learning. The performance of the proposed bandlimited DPD solution is evaluated using comprehensive simulations involving memoryless and memory-based PA models, as well as true RF measurements using commercial LTE-A base station and mobile device PAs. The achieved results validate and demonstrate efficient suppression of inband and OOB distortions in real-world application scenarios. Furthermore, the bandlimited DPD consistently outperforms the conventional DPD solutions in the memory-based PA model and practical PA scenarios in suppressing the OOB distortion in the immediate vicinity of the main carrier(s) by approximately 1 - 2 dB. The results provide sufficient grounds for the application of the bandlimited DPD solution in the classical single carrier deployment or in contiguous carrier aggregation of two or more component carriers where conventional DPD solutions would otherwise be highly complex

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

Adaptive Nonlinear RF Cancellation for Improved Isolation in Simultaneous Transmit-Receive Systems

This paper proposes an active radio frequency (RF) cancellation solution to suppress the transmitter (TX) passband leakage signal in radio transceivers supporting simultaneous transmission and reception. The proposed technique is based on creating an opposite-phase baseband equivalent replica of the TX leakage signal in the transceiver digital front-end through adaptive nonlinear filtering of the known transmit data, to facilitate highly accurate cancellation under a nonlinear TX power amplifier (PA). The active RF cancellation is then accomplished by employing an auxiliary transmitter chain, to generate the actual RF cancellation signal, and combining it with the received signal at the receiver (RX) low noise amplifier (LNA) input. A closed-loop parameter learning approach, based on the decorrelation principle, is also developed to efficiently estimate the coefficients of the nonlinear cancellation filter in the presence of a nonlinear TX PA with memory, finite passive isolation, and a nonlinear RX LNA. The performance of the proposed cancellation technique is evaluated through comprehensive RF measurements adopting commercial LTE-Advanced transceiver hardware components. The results show that the proposed technique can provide an additional suppression of up to 54 dB for the TX passband leakage signal at the RX LNA input, even at considerably high transmit power levels and with wide transmission bandwidths. Such novel cancellation solution can therefore substantially improve the TX-RX isolation, hence reducing the requirements on passive isolation and RF component linearity, as well as increasing the efficiency and flexibility of the RF spectrum use in the emerging 5G radio networks.Comment: accepted to IEE

Scheduling based optimization in software defined radio and wireless networks

The objective of this work is to enable dynamic sharing of software-defined radio (SDR) transceivers through the concepts of hardware virtualization and real-time resource management. SDR is a way to build a digital radio that consists of a software back-end for digital signal processing (DSP) and an analog front-end transceiver for waveform generation and reception. This work proposes the use of a virtualization layer to decouple back-end SDR software from front-end transceivers. With this arrangement, front-ends are said to be virtualized, and it becomes possible to share a limited number of front-ends among many SDR back-ends through different multiplexing techniques. In the first work, the hardware/software infrastructure needed for such a system is explored. An intelligent resource management algorithm is presented that demonstrates a potential increase in the number of supported SDR back-ends. The second work presents an exploration of this system\u27s application to aircraft telemetry systems and the potential improvements to reliability. The work includes a reliability model for virtualized SDR aircraft telemetry systems as well as simulations demonstrating changes in performance as hardware fails. In the final work, an improved resource management algorithm based on Markov decision process (MDP) is proposed. This approach addresses concerns wireless regulatory agencies and standards bodies may raise regarding performance degradation caused by sharing transceivers. The process of sharing transceivers causes service disruptions to occur whenever the instantaneous demand for front-ends exceeds capacity. This MDP approach provides a feasibility test and a guarantee that all SDRs can stay within their respective wireless specifications. The proposed technique guarantees Pareto efficient distribution of resources. To make this approach possible, a connection is established between dynamic transceiver sharing and equivalent interference --Abstract, page iv