Spektrin Havainnointi Kognitiivisissa Matkaviestinlaitteissa

Radio spectrum is becoming a scarce resource as increasing number of wireless devices attempt to access it. As a solution to this issue, spectrum sensing based cognitive radios have been proposed. However, significant part of them are mobile, consumer-grade devices that have strict price and form-factor limitations. This works aims to address the issues related to mobile spectrum sensing by characterizing the non-idealities with a spectrum sensor prototype. Two efficient sensing algorithms and a coarse-fine controller, which aims to minimize the energy consumption and run time of an individual sensor, are implemented on an FPGA. Functionality of the implementations is verified by laboratory and field measurements. Finally, a spatial interpolation method, Kriging, is applied to the non-ideal measurement data to create a uniform radio environment map.Langattomien laitteiden yleistyminen kasvattaa radiospektrin käyttöastetta ylärajaa kohti. Ratkaisuksi ongelmaan on kehitetty spektrin havainnointiin perustuvat kognitiiviset radiot. Näistä valtaosa on kuitenkin kuluttajatason matkaviestinlaitteita, joilla on tiukat rajoitteet muun muassa hinnan ja fyysisen rakenteen suhteen. Tässä työssä perehdytään spektrin havainnoinnin haasteisiin tutkimalla havainnoinnin epäideaalisuuksia spektrisensoriprototyypillä. Työssä on toteutettu FPGA:lle kaksi energiatehokasta havainnointialgoritmia sekä karkea-herkkä -ohjain, joka pyrkii minimoimaan yksittäisen spektrisensorin energiakulutusta sekä havainnointiaikaa. Toteutettujen algoritmien toiminta ja suorituskyky verifioidaan laboratorio- sekä kenttämittauksilla. Lopuksi esitellään avaruudellinen interpolaatiomenetelmä, Kriging, jota sovelletaan epäideaaliseen kenttämittausdataan kattavan radiopeitekartan luomiseksi

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

SMARAD - Centre of Excellence in Smart Radios and Wireless Research - Activity Report 2011 - 2013

Centre of Excellence in Smart Radios and Wireless Research (SMARAD), originally established with the name Smart and Novel Radios Research Unit, is aiming at world-class research and education in Future radio and antenna systems, Cognitive radio, Millimetre wave and THz techniques, Sensors, and Materials and energy, using its expertise in RF, microwave and millimeter wave engineering, in integrated circuit design for multi-standard radios as well as in wireless communications. SMARAD has the Centre of Excellence in Research status from the Academy of Finland since 2002 (2002-2007 and 2008-2013). Currently SMARAD consists of five research groups from three departments, namely the Department of Radio Science and Engineering, Department of Micro and Nanosciences, and Department of Signal Processing and Acoustics, all within the Aalto University School of Electrical Engineering. The total number of employees within the research unit is about 100 including 8 professors, about 30 senior scientists and about 40 graduate students and several undergraduate students working on their Master thesis. The relevance of SMARAD to the Finnish society is very high considering the high national income from exports of telecommunications and electronics products. The unit conducts basic research but at the same time maintains close co-operation with industry. Novel ideas are applied in design of new communication circuits and platforms, transmission techniques and antenna structures. SMARAD has a well-established network of co-operating partners in industry, research institutes and academia worldwide. It coordinates a few EU projects. The funding sources of SMARAD are diverse including the Academy of Finland, EU, ESA, Tekes, and Finnish and foreign telecommunications and semiconductor industry. As a by-product of this research SMARAD provides highest-level education and supervision to graduate students in the areas of radio engineering, circuit design and communications through Aalto University and Finnish graduate schools. During years 2011 – 2013, 18 doctor degrees were awarded to the students of SMARAD. In the same period, the SMARAD researchers published 197 refereed journal articles and 360 conference papers