Digital Signal Processing Techniques Applied to Radio over Fiber Systems

The dissertation aims to analyze different Radio over Fiber systems for the front-haul applications. Particularly, analog radio over fiber (A-RoF) are simplest and suffer from nonlinearities, therefore, mitigating such nonlinearities through digital predistortion are studied. In particular for the long haul A-RoF links, direct digital predistortion technique (DPDT) is proposed which can be applied to reduce the impairments of A-RoF systems due to the combined effects of frequency chirp of the laser source and chromatic dispersion of the optical channel. Then, indirect learning architecture (ILA) based structures namely memory polynomial (MP), generalized memory polynomial (GMP) and decomposed vector rotation (DVR) models are employed to perform adaptive digital predistortion with low complexities. Distributed feedback (DFB) laser and vertical capacity surface emitting lasers (VCSELs) in combination with single mode/multi-mode fibers have been linearized with different quadrature amplitude modulation (QAM) formats for single and multichannel cases. Finally, a feedback adaptive DPD compensation is proposed. Then, there is still a possibility to exploit the other realizations of RoF namely digital radio over fiber (D-RoF) system where signal is digitized and transmits the digitized bit streams via digital optical communication links. The proposed solution is robust and immune to nonlinearities up-to 70 km of link length. Lastly, in light of disadvantages coming from A-RoF and D-RoF, it is still possible to take only the advantages from both methods and implement a more recent form knows as Sigma Delta Radio over Fiber (S-DRoF) system. Second Order Sigma Delta Modulator and Multi-stAge-noise-SHaping (MASH) based Sigma Delta Modulator are proposed. The workbench has been evaluated for 20 MHz LTE signal with 256 QAM modulation. Finally, The 6x2 GSa/s sigma delta modulators are realized on FPGA to show a real time demonstration of S-DRoF system. The demonstration shows that S-DRoF is a competitive competitor for 5G sub-6GHz band applications

Ultra Low-Power Frequency Synthesizers for Duty Cycled IoT radios

Internet of Things (IoT), which is one of the main talking points in the electronics industry today, consists of a number of highly miniaturized sensors and actuators which sense the physical environment around us and communicate that information to a central information hub for further processing. This agglomeration of miniaturized sensors helps the system to be deployed in previously impossible arenas such as healthcare (Body Area Networks - BAN), industrial automation, real-time monitoring environmental parameters and so on; thereby greatly improving the quality of life. Since the IoT devices are usually untethered, their energy sources are limited (typically battery powered or energy scavenging) and hence have to consume very low power. Today's IoT systems employ radios that use communication protocols like Bluetooth Smart; which means that they communicate at data rates of a few hundred kb/s to a few Mb/s while consuming around a few mW of power. Even though the power dissipation of these radios have been decreasing steadily over the years, they seem to have reached a lower limit in the recent times. Hence, there is a need to explore other avenues to further reduce this dissipation so as to further improve the energy autonomy of the IoT node. Duty cycling has emerged as a promising alternative in this sense since it involves radios transmitting very short bursts of data at high rates and being asleep the rest of the time. In addition, high data rates proffer the added advantage of reducing network congestion which has become a major problem in IoT owing to the increase in the number of sensor nodes as well as the volume of data they send. But, as the average power (energy) dissipated decreases due to duty cycling, the energy overhead associated with the start-up phase of the radio becomes comparable with the former. Therefore, in order to take full advantage of duty cycling, the radio should be capable of being turned ON/OFF almost instantaneously. Furthermore, the radio of the future should also be able to support easy frequency hopping to improve the system efficiency from an interference point of view. In other words, in addition to high data rate capability, the next generation radios must also be highly agile and have a low energy overhead. All these factors viz. data rate, agility and overhead are mainly dependent on the radio's frequency synthesizer and therefore emphasis needs to be laid on developing new synthesizer architectures which are also amenable to technology scaling. This thesis deals with the evolution of one such all-digital frequency synthesizer; with each step dealing with one of the aforementioned issues. In order to reduce the energy overhead of the synthesizer, FBAR resonators (which are a class of MEMS resonators) are used as the frequency reference instead of a traditional quartz crystal. The FBAR resonators aid the design of fast-startup oscillators as opposed to the long latency associated with the start-up of the crystal oscillator. In addition, the frequency stability of the FBAR lends itself to open-loop architecture which can support very high data rates. Another advantage of the open-loop architecture is the frequency agility which aids easy channel switching for multi-hop architectures, as demonstrated in this thesis

Nonlinear Distortion in Wideband Radio Receivers and Analog-to-Digital Converters: Modeling and Digital Suppression

Emerging wireless communications systems aim to flexible and efficient usage of radio spectrum in order to increase data rates. The ultimate goal in this field is a cognitive radio. It employs spectrum sensing in order to locate spatially and temporally vacant spectrum chunks that can be used for communications. In order to achieve that, flexible and reconfigurable transceivers are needed. A software-defined radio can provide these features by having a highly-integrated wideband transceiver with minimum analog components and mostly relying on digital signal processing. This is also desired from size, cost, and power consumption point of view. However, several challenges arise, from which dynamic range is one of the most important. This is especially true on receiver side where several signals can be received simultaneously through a single receiver chain. In extreme cases the weakest signal can be almost 100 dB weaker than the strongest one. Due to the limited dynamic range of the receiver, the strongest signals may cause nonlinear distortion which deteriorates spectrum sensing capabilities and also reception of the weakest signals. The nonlinearities are stemming from the analog receiver components and also from analog-to-digital converters (ADCs). This is a performance bottleneck in many wideband communications and also radar receivers. The dynamic range challenges are already encountered in current devices, such as in wideband multi-operator receiver scenarios in mobile networks, and the challenges will have even more essential role in the future.This thesis focuses on aforementioned receiver scenarios and contributes to modeling and digital suppression of nonlinear distortion. A behavioral model for direct-conversion receiver nonlinearities is derived and it jointly takes into account RF, mixer, and baseband nonlinearities together with I/Q imbalance. The model is then exploited in suppression of receiver nonlinearities. The considered method is based on adaptive digital post-processing and does not require any analog hardware modification. It is able to extract all the necessary information directly from the received waveform in order to suppress the nonlinear distortion caused by the strongest blocker signals inside the reception band.In addition, the nonlinearities of ADCs are considered. Even if the dynamic range of the analog receiver components is not limiting the performance, ADCs may cause considerable amount of nonlinear distortion. It can originate, e.g., from undeliberate variations of quantization levels. Furthermore, the received waveform may exceed the nominal voltage range of the ADC due to signal power variations. This causes unintentional signal clipping which creates severe nonlinear distortion. In this thesis, a Fourier series based model is derived for the signal clipping caused by ADCs. Furthermore, four different methods are considered for suppressing ADC nonlinearities, especially unintentional signal clipping. The methods exploit polynomial modeling, interpolation, or symbol decisions for suppressing the distortion. The common factor is that all the methods are based on digital post-processing and are able to continuously adapt to variations in the received waveform and in the receiver itself. This is a very important aspect in wideband receivers, especially in cognitive radios, when the flexibility and state-of-the-art performance is required

Observations concerning the generation of spurious tones in digital delta-sigma modulators followed by a memoryless nonlinearity

In mixed-signal systems, nonlinear distortion due to nonideal analog circuitry can act on quantized digital sequences, giving rise to spurious tones. In this brief, generation of spurious tones in digital delta-sigma modulators, followed by memoryless nonlinearity, is investigated. Inherent modulator periodicity that persists even with the use of least-significant-bit dither is identified. © 2011 IEEE

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression