Institutionen för systemteknik

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1 Institutionen för systemteknik Department of Electrical Engineering Examensarbete Design and Implementation of an SDR receiver for the VHF band Examensarbete utfört i Elektroniksystem vid Tekniska högskolan i Linköping av Emad Athari & Petter Lerenius LITH-ISY-EX--07/3946--SE Linköping 2007 Department of Electrical Engineering Linköpings universitet SE Linköping, Sweden Linköpings tekniska högskola Linköpings universitet Linköping

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3 Design and Implementation of an SDR receiver for the VHF band Examensarbete utfört i Elektroniksystem vid Tekniska högskolan i Linköping av Emad Athari & Petter Lerenius LITH-ISY-EX--07/3946--SE Handledare: Examinator: Per Löwenborg ISY, Linköpings universitet Jonas Nilsson Signal Processing Devices Sweden AB Per Löwenborg ISY, Linköpings universitet Linköping, 31 January, 2007

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5 Avdelning, Institution Division, Department Elektroniksystem Department of Electrical Engineering Linköpings universitet SE Linköping, Sweden Datum Date Språk Language Svenska/Swedish Engelska/English Rapporttyp Report category Licentiatavhandling Examensarbete C-uppsats D-uppsats Övrig rapport ISBN ISRN LITH-ISY-EX--07/3946--SE Serietitel och serienummer Title of series, numbering ISSN URL för elektronisk version Titel Title Design och implementation av en SDR-mottagare för VHF-bandet Design and Implementation of an SDR receiver for the VHF band Författare Author Emad Athari & Petter Lerenius Sammanfattning Abstract The purpose of this thesis work is to examine the possibility of building a softwaredefined radio (SDR) for the VHF-band. The goal is to accomplish this with as few components as possible, thus cutting down the size and the production cost. An SDR solution means that the sampling of the signal is done as close to the antenna as possible. The wide bandwidth needed in such a product is achieved by using SP Devices algorithm for time-interleaved ADCs. Two hardware prototypes and two versions of the software were designed and implemented using this technology. They were also analyzed within this thesis work. The results proved to be good, and the possibilities to produce a commercial software-defined radio receiver for the VHF-band are good. Nyckelord Keywords SDR, software-defined radio, radio, GMSK, receiver, FPGA

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7 Abstract The purpose of this thesis work is to examine the possibility of building a softwaredefined radio (SDR) for the VHF-band. The goal is to accomplish this with as few components as possible, thus cutting down the size and the production cost. An SDR solution means that the sampling of the signal is done as close to the antenna as possible. The wide bandwidth needed in such a product is achieved by using SP Devices algorithm for time-interleaved ADCs. Two hardware prototypes and two versions of the software were designed and implemented using this technology. They were also analyzed within this thesis work. The results proved to be good, and the possibilities to produce a commercial software-defined radio receiver for the VHF-band are good. Sammanfattning Syftet med det här examensarbetet är att utreda möjligheten att bygga en mjukvarudefinierad radiomottagare (SDR) för VHF-bandet. Målet är att göra detta genom att använda så få komponenter som möjligt, och därigenom minska storleken och produktionskostnaden. En SDR lösning ger att samplingen kommer att ske så nära antennen som möjligt. Den stora bandbredd som behövs för en sådan produkt uppnås genom att använda SP Devices algoritm för att tidsinterleava höghastighets ADC:er. Två hårdvaruprototyper och två versioner av mjukvaran har designats och implementerats. Analyserna har visat bra resultat, och möjligheterna att bygga en komersiell mjukvarudefinierade radiomottagare för VHF-bandet ses som goda. v

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9 Acknowledgments The completion of this thesis had not been possible without the help and support that we have received throughout this work. Therefore we would like to thank the people the persons that has made this possible. Firstly we would like to thank our supervisors Per Löwenborg, at the Division of Electronics Systems at Linköping University, and Jonas Nilsson, at SP Devices, for their enormous support and for believing in us. We would also like to thank all of the personnel at SP Devices and Peter, Christian, Marcus and Anders for great help and support. Last but not least we would like to thank our families and friends for their endless love and support. vii

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11 Abbreviations ACK AD ADC AGC BB BER BPF BW BWch DAC db dbc dbfs dbm DC DDS DSP DR EMC ENOB FFT FIR FPGA FSR GMSK HDLC IF IP3 IIP3 IMD IMD3 IQ IR LNA LO Acknowledgement Analog-to-Digital Analog-to-Digital Converter Automatic Gain Control Baseband Bit Error Rate Bandpass Filter Bandwidth Channel Bandwidth Digital-to-Analog Converter Decibel Decibel relative to the carrier Decibel relative to Full Scale Range Decibel relative to 1 mw Direct Current Direct Digital Sythesis Digital Signal Processing Dynamic Range Electromagnetic Compatibility Effective Number of Bits Fast Fourier Transform Finite length Impulse Response Field-Programmable Gate Array Full Scale Range Gaussian Minimum Shift Keying High Level Data Link Control Intermediate Frequency Third-Order Intercept Point Third-Order Input Intercept Point Intermodulation Distortion Third-Order Intermodulation Distortion In phase and Quadrature Image Rejection Low Noise Amplifier Local Oscillator ix

12 x LPF Lowpass Filter LSB Least Significant Bit MAC Multiply and Accumulate NF Noise Figure NRZ Non Return to Zero NRZI Non Return to Zero Inverted OIP3 Third-Order Output Intercept Point PER Packet Error Rate PG Process Gain RF Radio Frequency SAW Surface Acustic Wave SDR Software Defined Radio SFDR Spurious-Free Dynamic Range SNDR Signal-to-Noise and Distortion Ratio SNR Signal-to-Noise Ration SNR req SNR required v4 Xilinx virtex 4 v5 Xilinx virtex 5 VGA Variable Gain Amplifier VHF Very High Frequency

13 Contents 1 Introduction Background PurposeandMethod Prerequisites Tools Protel Matlab and Simulink Xilinx ISE Microsoft Visual Studio Restrictions Report Disposition Reading Instructions Linearizer Problems with Interleaved ADCs Gain Mismatch Offset Error Time-Skew The Solution Superheterodyne vs. SDR Introduction Traditional Superheterodyne RF Receiver Advantages Disadvantages Software-Defined Radio Receiver Advantages Disadvantages Basic RF Receiver Concepts Signal-to-Noise Ratio Receiver Noise Intermodulation Distortion & Intercept Point Dynamic Range Spurious-Free Dynamic Range xi

14 xii Contents 4.6 Effective Number of Bits Oversampling in Analog-to-Digital Converters Requirements Bandwidth Sensitivity Intermodulation Response Rejection and Blocking Adjacent Channel Selectivity Signal-to-Noise Ratio Analog Front-End Front-End Architecture Choise of Components ADC LNA and VGA Analog Filters FPGA USB-to-UART Interface DAC Crystal Oscillator and Clock Buffer Linear Voltage Regulators Theoretical Calculations SNR IMD PCB and EMC[13] Data Packets The Packet Training Sequence Start Flag Data Frame Check Sequence Bit Stuffing NRZI GMSK Gaussian filter FPGA Hardware Prerequisites DSP-slices First Attempt Linearizer First Decimation I - Q Modulation Second Decimation

15 Contents xiii Third Decimation Phase Differentiator FIFO Data Transfer DAC Controller Second attempt Linearizer IQ-modulation Decimation Phase Differentiator FIFO Serial Interface DAC Controller Calculations Scaling Word Length PC Communication Matlab Symbol Syncronization Decode NRZI Extraction of the Data Tests and Results Filter Bandwidths Board Board External LNA SNR Variable Gain - Fixed Signal Level Fixed Gain - Variable Signal Level Sensitivity Test Board Board Blocking Test Intermodulation Test AdjacentChannelSelectivity Power Consumption Conclusions and Future Work Conclusions Test Results Hardware FPGA Future Work

16 xiv Contents References 81

17 Contents xv List of Figures 2.1 Effect of problems that occur when interleaving ADCs Result of a gain error in an ADC Result of an offset error in an ADC Resultoftime-skewinanADC The block diagram of the linearizer Interleaved sequencies with missmatch, before and after linearization Superheterodyne receiver architecture Intercept Points/1-dB Compression Points The architecture of the analog front-end BPF1-1st order bandpass filter BPF2-2nd order bandpass filter BPF1-1st order bandpass filter The configuration for IMD measurements Block schematic for the modulation Apacket sdifferentcomponents The training sequence before and after NRZI encoding An example bit stream which has been bit stuffed AnexamplebitstreamencodedwithNRZI DSP48-slice in virtex DSP48E-slice in virtex System overview for the first attempt The frequency response for the first decimation filter Impulse response for the second decimation filter Impulse response for the third decimation filter System overview for the second attempt The difference between the two DDS blocks The frequency response for the complete decimation filter A zoomed in portion of the frequency response in Figure Impulse response for the first decimation filter Impulseresponseforthefilterh Impulse response for the filter h Impulseresponseforthefilterh Impulse response for the filter h Impulse response for the filter h Impulse response for the filter h Impulse response for the filter h The impulse response for the correlation filter An example output from the correlation filter Zoomed in on the detected message

18 xvi Contents 9.4 An example bit stream decoded from NRZI Frequency response for board Frequency response for board Setup for SNR test, without and with external LNA The setup for the sensitivity test for board The setup for the sensitivity test for board 1 with LNA The setup for the sensitivity test for board The setup for the sensitivity test for board 2 with LNA The setup for the blocking test Plot from the IMD3 test on board

19 List of Tables 2.1 Time-interleaved ADC matching requirements at 180 MHz clock frequency SNR requirement at different sampling frequencies Properties for the VGA Component values for the analog bandpass filters Current consumption of the first PCB Current consumption of the second PCB Packet components and their sizes L 2 -norm scaling of the decimation filters SNR for different word lengths Properties for the external LNA SNR for a -70dBm signal without and with external LNA on board SNR for a -70dBm signal without and with external LNA on board SNR for various signal levels without and with external LNA on board SNR for various signal levels without and with external LNA on board Sensitivity test using PCB SensitivitytestusingPCB1withexternalLNA Sensitivity test using PCB SensitivitytestusingPCB2withexternalLNA IMD test performed on board Results from the tests

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21 Chapter 1 Introduction 1.1 Background Signal Processing Devices Sweden AB (SP Devices) was started in 2003, with an algorithm that solves the problems that occur when time-interleaving high precision ADCs. The algorithm was a result of research done by Håkan Johansson and Per Löwenborg at Linköping University. The possibility of time-interleaving ADCs opens up many new fields for digitalization. For example, with two 14-bit time-interleaved ADCs, sampling speeds of above 400 MSps can be achieved. This means that the Nyquist criterion can be met for a 200 MHz bandwidth. The field of software-defined radios (SDR) is a big research area. The SDR can revolutionize the market of radio receivers. They are much more flexible and in some cases cheaper to produce than todays receivers. The goal with this thesis is to show that SP Devices algorithm applied on two ADCs can be used to build a software-defined radio receiver for the VHFband ( MHz) with as few components as possible. This thesis work was conducted at SP Devices in Linköping. 1.2 Purpose and Method The purpose of this thesis is to design, implement and analyze a prototype of a software-defined radio for the VHF frequencies MHz from idea all the way to a working prototype. The SDR architechture will be compared with the superheterodyne receiver architechture, which is commonly used today. During this work an incremental method of development will be used. By improving the design in small steps, the work will advance in steps that are easily controlled. This will be achieved by first building a model of the SDR in Matlab and then implement it as a prototype in two steps. Two versions of both the hardware and the software will be completed during the thesis. This will make it possible to make an attempt and then refine it 1

22 2 Introduction and correct possible errors. The two versions are analyzed and their performance measured and compared. 1.3 Prerequisites To grasp this thesis the reader should have some previous knowledge of electronics and concepts like field-programmable gate arrays (FPGAs). Also some understanding of digital signal processing and radio technology could be useful. 1.4 Tools During the work of this thesis some software tools have been used to complete the tasks of building a prototype. Here follows a description of the programs used and a description of their purpose Protel Protel is a CAD program for designing printed circuit boards (PCB) and it also provides the possibility to do simulations on schematic level. The schematic of the front-end architechture was drawn and simulated before the PCB was designed. The PCB was then routed by hand before it was sent for manufacturing at Elprint Matlab and Simulink Matlab and Simulink was used to make a model of the system and to predict its behavior. Matlab is convenient to use when dealing with simulations of digital processing. For simulations of the analog parts it is better to use Protel. Matlab was also used for the decoding process and to present the results during the performance tests Xilinx ISE Xilinx ISE is an integrated development environment (IDE) for Xilinx FPGAs. It translates, synthesizes and routes the Verilog or VHDL code onto the designated FPGA. In this project only Verilog was used. ISE is easy to work with and allows code modules to be in different files, which makes the development process much easier. It is free if developing for Xilinx Virtex 4 FPGAs, but needs a license when using a Xilinx Virtex Microsoft Visual Studio C code was written to produce a dynamically linked library (dll) file used by matlab to fetch data from the usb port. It was written and compiled in the 1

23 1.5 Restrictions 3 Microsoft Visual Studio environment. Visual Studio is Microsoft s IDE for C, C++ and many more languages. 1.5 Restrictions This thesis work will produce a prototype for decoding a specific kind of digital messages that are modulated with GMSK. No other modulations will be treated or discussed. This report analyzes the prototypes designed and it will not cover any other solutions. 1.6 Report Disposition This report will present the work performed during this thesis and its results. The first chapters cover the more theoretical parts while the later chapters describe the work and the results. Chapter 2 explains the problems that come up when time-interleaving ADCs, and the solution that SP Devices has developed. Chapter 3 will explain more about how SDR works and what the advantages are compared to the common superheterodyne receivers that are commonly used today. It is followed by Chapter 4 that discusses the parameters of a receiver performance, while Chapter 5 presents the requirements for this project. The work performed in this thesis will then be presented. It starts with the PCB and its analog front-end in Chapter 6. The data packages that are used for testing the receivers performance is explained in Chapter 7. It is followed by the description of the digital signal processing performed in the FPGA in Chapter 8 and the PC in Chapter 9. The tests and their results are described in Chapter 10. Finally the conclusions made in this thesis are presented in Chapter 11 together with some ideas of how to continue with this work. 1.7 Reading Instructions Those who have good knowledge in electronics and radio technologies could skip the first theoretical chapters, except for Chapter 5 which could be good to have read to understand the decisions made in Chapter 6. The most interesting chapter is probably Chapter 10 where the results are presented.

24 4 Introduction

25 Chapter 2 Linearizer To achieve high speed analog-to-digital conversion, time-interleaving multiple ADCs seems to be a good solution. This has been used for low resolution ADCs since 1980, but higher resolutions matching problems deteriorate the quality of the signal. An 8-bit system that provides a dynamic range of 50 db can tolerate a gain mismatch of 0.25% and a clock-skew error of 5 ps. This accuracy can be met by traditional methods like, matching the physical channel layouts, using common ADC reference voltages, prescreening devices, and active analog trimming, but this is not enough for higher resolutions[10]. The problems that need to be considered when ADCs are interleaved are shown in figure 2.1 were four ADCs have been time interleaved. In this chapter the problems caused by interleaving will be discussed and then SP Devices algorithm for solving these problems will be presented. Desired digital signal Resulting digital signal Figure 2.1. Effect of problems that occur when interleaving ADCs. 2.1 Problems with Interleaved ADCs There are three main categories of problems that arise when ADCs are interleaved. They all come from the fact that it is impossible to manufacture two silicon chips 5

26 6 Linearizer that are identical. The surrounding environment also affects how well the ADCs match, e.g., if they have different temperature. This results in differences in gain, offset and timing, which affects the output in a way depicted by the Figure 2.1. For narrowband signals, there will be unwanted spurious frequencies in the output signal, called spurs. ( Ge ) IS gain(db) = 20log(IS gain )=20log (2.1) 2 G e = gain error ratio = 1 V FSA V FSB (2.2) ( ) θep IS phase(db) = 20log(IS phase )=20log (2.3) 2 θ ep = ω a t e (radians) (2.4) ω a = analog input frequency (2.5) t e = clock skew error (2.6) ) IS tot(db) = 20log ( (IS gain ) 2 +(IS phase ) 2 (2.7) From equations it is possible deduce that even very small divergences between the ADCs will result in large spurs that will deteriorate the dynamic range. Table 2.1 shows the matching requirements for a time-interleaved system[10]. Number of bits SFDR Gain Matching Aperture Matching (dbc) (%) (fs) Table 2.1. Time-interleaved ADC matching requirements at 180 MHz clock frequency Gain Mismatch The gain error cause the ADC to affect the output by changing the signal amplitude. As seen in Figure 2.2, this would not affect the signal noticeably if only one ADC was used, but when two ADCs are interleaved it will result in aliasing distortion. The differences in gain between two ADCs affects the output even if it is as small as 0.01%, as shown in equations 2.1 and 2.2. The spurs deteriorate the signal quality, or destroy the wanted signal if they coincide.

27 2.1 Problems with Interleaved ADCs 7 Gain error Figure 2.2. ResultofagainerrorinanADC Offset Error An ADC has a small DC offset in its output, and when using two ADCs they will have different offsets. When two ADCs are time-interleaved different offsets will result in a spur at π. The figure 2.3 shows an exaggerated offset error. Offset error Offset Figure 2.3. Result of an offset error in an ADC Time-Skew Time-skew errors, or phase errors, arise when the ADC s samples are taken at the wrong instants in time. When more than one ADC samples the signal the timeskew will be experienced as a phase error. This will cause aliasing distortion that coincide with the gain error[10]. The time-skew is depicted in Figure 2.4, where the samples are taken with a delay in time.

28 8 Linearizer Time skew Figure 2.4. Result of time-skew in an ADC. 2.2 The Solution SP Devices has developed a clever algorithm, called linearizer, that corrects these errors by filtering the digital result. Figure 2.5 shows a block diagram of the linearizer. Linearizer ADC 1 ADC 2 Reconstructor Estimator Monitor & Control Figure 2.5. The block diagram of the linearizer The linearizer is purely digital and uses advanced signal processing algorithms to correct the errors mentioned in the previous section. Since the correction is done digitally it can function with any ADC. The linearizer could also be used to increase the resolution while maintaining the speed. The estimator uses a batch of data to estimate the different errors. These estimates are used for calculating the filter coefficient values. The coefficients are then passed on to the reconstructor. The reconstructor block consists of a filter that corrects the errors from the differencies in the ADCs in real time. By using the linearizer, as depicted in Figure 2.6 it is possible to construct very fast ADCs with high performance, that opens up many new possibilities in fields previously not conceivable. The software-defined radio developed in this thesis is

29 2.2 The Solution 9 ADC ADC ADC ADC L i n e a r i z e r Figure 2.6. Interleaved sequencies with missmatch, before and after linearization. just one example made possible by the linearizer.

30 10 Linearizer

31 Chapter 3 Superheterodyne vs. SDR 3.1 Introduction This chapter will explain the pros and cons of the commonly used superheterodyne radio frequency (RF) receiver and a software-defined radio (SDR) receiver. It also covers the differences between the two types and why the SDR receiver together with SP Devices technology is preferred in a broadband RF receiver where small area, low power consumption and low cost are the main requirements. 3.2 Traditional Superheterodyne RF Receiver One of the most common RF receiver architecture types used in radio applications for the last century and today is the superheterodyne receiver. This receiver type is often preferred because of its great performance regarding receiver characteristics such as sensitivity and selectivity. A simple description of the traditional superheterodyne architecture can be seen in the block diagram in Figure 3.1. LO RF Filter LNA BPF IF Amp BPF AGC Amp IQdemodulator Rx IQ Figure 3.1. Superheterodyne receiver architecture The first block after the antenna is an RF bandpass filter (BPF) which attenuates the undesired out-of-band frequencies. The signal is then amplified in a low noise amplifier (LNA) which amplifies the signal with relatively low noise contribution. This device is the most crucial part of the receiver chain because of the many system requirements depending on it. After the amplification and bandpass filtering the signal is down-converted by a mixer. This process is the principle of 11

32 12 Superheterodyne vs. SDR heterodyning which is the generation of an intermediate frequency by mixing (multiplying) the incoming high frequency signal with another high frequency signal generated by a local oscillator (LO). The mixer circuit has significant requirements on linearity and noise and can cause severe DC-offset problems in the receiver. The generated IF-signal is amplified in the IF-amplifier before selection of the desired channel in the last BPF. In the last stage the signal amplitude is adjusted by the automatic gain control (AGC) to fit the dynamic range of the analog-todigital converter(s) (ADC) Advantages A major advantage of the superheterodyne receiver is that by mixing down the signal to lower frequencies the cost of the components reduces. Generally for RF components, such as filters and mixers, cost is proportional to frequency[4]. This is due to the fact that low frequency components are less complex and easier to find/build. The down-conversion to IF gives the receiver high selectivity i.e. high ability of sorting out the desired signal by supressing the undesired signals. This is because the requirements on the filters are relaxed when operating at lower frequencies (IF), which makes it easier to build more effective selective filters with much narrower passband Disadvantages One of the biggest cons of the superheterodyne receiver is the amount of external components. The wider frequency spectrum the harder it is to find or build narrow-passband filters to a reasonable cost, if not impossible. More components means higher cost, higher power consumption, larger area and higher architecture complexity. The complexity mentioned above leads to another problem which is the low achievable level of integration. This also depends on the fact that the high performance of discrete components is hard to achieve in an integrated solution. Another problem in this architecture is the mixer and local oscillator stages. One problem that is associated with mixer circuits, besides the cost, is the so called LO-leakage. This leakage can get mixed with the oscillator itself and/or get picked up by the antenna and get amplified in the LNA producing a spur. The wanted channel is predefined by hardware. Each channel require a separate receiver which increases the need of hardware if multiple channels are desired.

33 3.3 Software-Defined Radio Receiver Software-Defined Radio Receiver One of the newest and most interesting concepts in radio architecture development is software-defined radio (SDR). In this thesis project only the receiver part is discussed. The basic idea of the SDR receiver is to digitalize the incoming analog RF signal as close to the antenna as possible and then do the signal processing digitally. In an ideal SDR receiver the ADC(s) would be attached directly to the antenna sending the samples to some kind of processor (FPGA, DSP etc.) where the data would be transformed/shaped as desired by software. The sampling frequency (f s )would have to be greater than twice the signal bandwidth to be able to reconstruct the signal from the digital samples (Nyquist theorem)[11]. In practice this is hard to achieve due to the fact that todays ADC:s with the required resolution, are yet too slow to receive radio signals at higher frequencies. In current commercial software receivers the problem mentioned above is solved by mixing down the radio signal to a lower frequency using local oscillators, as mentioned above in Section 3.2. This will not be the case here hence the main goal is to significantly reduce the use of analog hardware. Instead the problem is approached by taking advantage of time-interleaving. As it was described in Chapter 2, interleaving allows faster f s than the specified f s of the ADC. By interleaving N ADCs the f s could be N times the f s of a single ADC. Also described in Chapter 2 was that SP Devices algorithm makes it possible to interleave high-speed ADC:s without degrading the resolution. This technology allows high enough sampling frequency for sampling the signal without requiring down-conversion, i.e. no mixers or local oscillators are needed. The hardware architecture used in this project is further explained in Chapter Advantages The SDR receiver has the ability to receive different modulation types while using the same hardware platform. Its funcionality can be changed by downloading and running new software whenever desired, without any change of hardware. Reduction/elimination of the use of analog hardware which means lower cost, lower power consumption, smaller area needed and lower architecture complexity. The channel is not predefined by hardware which means that any channel within the bandwidth can be chosen by software. It is even possible to receive several channels in parallel Disadvantages Finding the right components, such as amplifiers, for a flexible front-end can be rather hard due to problems like linearity, dymanic range, noise figure.

34 14 Superheterodyne vs. SDR Filters are expensive and hard to design for such broadband applications. Writing software for different applications can be quite complex.

35 Chapter 4 Basic RF Receiver Concepts 4.1 Signal-to-Noise Ratio Signal-to-noise ratio (SNR) is the ratio between the power of the desired signal and the average power of the noise in the system. In other words, the higher SNR the less noise in the system and the clearer signal. SNR is calculated using Equation 4.1[11]. ( ) Psignal SNR =10log (4.1) P noise In the process of choosing components for the receiver it must be considered how much a specific component affects the overall SNR, due to its noise contribution. This means that in order to do an approximate calculation of the systems SNR for a specific signal level the total receiver noise must be calculated. The section below shows the equations used for noise calculation. The SNR calulations for this system are done in Section Receiver Noise In order to do a calculation of the receiver noise the thermal noise at the antenna must be calculated by using Equation 4.3[21] is Boltzmann s constant, T is absolute temperature in kelvins and B is the Nyquist bandwidth, f s /2. Usually in receiver noise calculations T is chosen to be 290K and gives 10log kt = -174 dbm. dbm is a representation of a power level in db relative to 1 mw. This representation gives a clue of how much stronger the measured signal is in comparison with 1mW. N th = ktb (4.2) N th (dbm) = 10logkT +10logB = = 174dBm +10logB (4.3) 15

36 16 Basic RF Receiver Concepts After the calculation of the thermal noise the noise and gain contribution of all parts in the receiver are added, as shown in Equations N in is the total noise power of the receiver before the A/D-conversion. F i = N i 1 + N i =1+ N i N i 1 N i 1 N i = F i 1 (4.4) N i 1 N in = G 1 G 2 ktb + G 1 G 2 [F 1-1]kTB+ G 2 [F 2-1]kTB= = G 1 G 2 [F 1 + F 2 1 ]ktb = G 1 = G sys F sys ktb[w] (4.5) Equation 4.5 represents the noise in a system containing two gain and/or noise contributing devices. F i is the noise factor of the i:th device after the antenna and G i is the gain factor of ditto. As shown in Equation 4.5, the noise factor of a device is divided by the gain factor of all previous devices. This means that devices that are placed far from the antenna contributes less to the overall noise than the ones closer to the antenna. Notice that all noise and gain factors for the cascaded parts are linear values not logarithmic. Usually in the devices data sheets the noise is represented as noise figure (NF). NF is the common logarithm of the noise factor. 4.3 Intermodulation Distortion & Intercept Point Intermodulation distortion (IMD) occurs when two or more different input frequencies exist in a device, resulting in production of undesired output signals (intermodulation products) at other frequencies. This is a problem in all amplifiers and mixers but also in passive components. In this project only amplifiers and passives are taken into account because of the absence of mixers. These intermodulation products (IMD products) are produced at the sum and difference of integer multiples of the existing frequencies. Equation 4.6 expresses the output frequency components when two different input frequencies exist in the device, which results in two-tone intermodulation distortion. IMD = m f1 ± n f2 (4.6) The sum of the integers m and n in Equation 4.6 defines the order of the IMD product. Most of these products are either too weak to be detected or too far away to interfere with the desired frequencies. Generally in RF systems, and in the case of this project, the third-order products (IMD3: 2f 1 + f 2, 2f 1 f 2, 2f 2 f 1, 2f 2 + f 1 ) are of great concern, since the probability of them falling inband and interfere with the desired frequency is high[21]. Intermodulation rejection raito is the ratio between the desired signal and the highest IMD 3 product. It is an

37 4.3 Intermodulation Distortion & Intercept Point 17 imortant parameter which describes the receivers ability to handle strong IMD products. Commonly IMD 3 products are specified in terms of third-order intercept point (IP 3 ). This is a measure of the devices tolerance against interfering signals outside the desired passband. In Figure 4.1[7] the output power is plotted versus the input power, both in logarithmic scale. It is shown that both the output signal and the IMD 3 product increase linearly with increased input signal. For every 1-dB of signal increase the IMD 3 product amplitude increases 3 db because of increased distortion in the device. At a certain level of input signal strength the wanted signal and the IMD 3 product will be equal. This point is called the IP3 which usually is referenced to either the input or the output of the device. IIP 3 is the input power at the IP 3 and OIP 3 is the output power at the IP 3. The relationship between the two is OIP 3 = IIP 3 + system gain. Figure 4.1. Definition of Intercept Points and 1-dB Compression Points for Amplifiers Also seen in Figure 4.1 is the 1-dB compression point which shows the input signal level at which the receiver begins to get a non-linear amplitude response. This means that the device is linear up to a certain input signal level after which the output becomes saturerad and stop increasing with increased input signal. Both IP3 and 1-dB compression point are important parameters in the choice of amplifiers and most often one or both these values are given in the devices data sheet. The power of an intermodulation product is calculated using Equation 4.7[5]. P IMout is the power of the IMD product at the output of the device and P out is the signal power at the output. P IMout =3 P out 2 OIP 3 (4.7)

38 18 Basic RF Receiver Concepts This equation will be used in Section to calculate a theoretical value of the total P IM generated in the chosen system configuration. 4.4 Dynamic Range Dynamic Range (DR) is the ratio between the maximum and the minimum signal that a receiver is designed to handle simultaneously. This measure is used for describing the limits of receivers. DR is of great concern in SDR solutions because of the wide frequency band of interest where signal levels can differ significantly. 4.5 Spurious-Free Dynamic Range Spurious-free dynamic range (SFDR) measures the ratio between the root-meansquare (rms) level of the desired signal and the rms level of the highest spur in the spectrum. It is an important parameter in cases where harmonic distortion and spurious signals are undesirable. One example of these cases is analog-to-digital converters (ADCs) in which noise and harmonics limit the dynamic range. 4.6 Effective Number of Bits The ADC resolution is defined as the number of bits at its output, i.e. the size of the binary word which represents the sampled analog signal. An alternative definition is the size of the least significant bit (LSB), Equation It should be noted that it is not a measure of the conversion quality. There are different error sources in an ADC degrading its performance. When all sources are included, the resolution is usually lower than the specified number of bits of the converter[11]. That is why the effective number of bits (ENOB) of an ADC is such an important parameter and represents the noise-free bits. ENOB is a measure of the ADCs accuracy at a specific input frequency. It is calculated using Equation 4.9[11]. As seen in the equation the value of SNDR is needed for the calculation of ENOB. SNDR is signal-to-noise-and-distortion ratio and is defined similarly as SNR except it also includes distortion. See Equation 4.8[11] P signal SNDR = 10log P noise + P distortion (4.8) ENOB = SNDR 1, (4.9) 4.7 Oversampling in Analog-to-Digital Converters As mentioned earlier in Section 3.3, in order to reconstruct a signal from its digital samples it must be sampled at a frequency that is greater than twice the bandwidth

39 4.7 Oversampling in Analog-to-Digital Converters 19 i.e. Nyquist s criterion. If f s /2 is higher than the Nyquist frequency the ADC is considered to be oversampled. By oversampling the ADC(s) the overall SNR is increased. The reason of this is explained below. Quantization noise is introduced in the ADC when the continuous analog signal is quantized to discrete values[11]. This quantization noise is a fixed power and is independent of the input signal, as shown in eq 4.11[21] This noise is spread out over the Nyquist bandwidth, which is dc up to f s /2. If the ADC is oversampled the noise is spread out over a wider range of frequencies. So the wider f s the lower noise floor, i.e. higer SNR. This improvement of the SNR is called oversampling gain or process gain, see Equation V lsb = V p p 2 N (4.10) P qn = V lsb 2 (4.11) 12R ( ) fs /2 process gain = 10log (4.12) BW

40 20 Basic RF Receiver Concepts

41 Chapter 5 Requirements Several requirements regarding the receiver s performance are set up for this project. These requirements will be presented in this chapter. Also some basic RF receiver concepts will be explained in order to make the understanding of the requirements easier. 5.1 Bandwidth The bandwidth (BW) of the receiver in this project is desired to be between MHz. This wide BW of 62 MHz sets major requirements on the analog filters in the receiver. The filter requirements and problems caused by the wide BW are explained in Section Sensitivity Receiver sensitivity is the lowest signal level that is detectable by the receiver. The requirements regarding sensitivity in this project is that the receiver must be able to decode a modulated message at 162 MHz with a signal level of -107 dbm. A packet error rate (PER) of 20% is allowed. The modulation type of the signal is discussed in Chapter 7. The highest detectable signal is required to be -7 dbm. The number of uncorrectly received messages at this level should not differ by more than 10 from those received at -77 dbm. These boundary values of the signal level give a span of 100 db. It should be kept under consideration that all the components used in the analog front-end must have proper performance at all levels of the 100 db interval. 21

42 22 Requirements 5.3 Intermodulation Response Rejection and Blocking Intermodulation response rejection is the receivers ability to supress IMD products caused by two or more undesired signals. The frequencies of these signals have a specific relationship to the desired signal frequency. A blocker on the other hand is a strong out-of-band interferer that sets requirement on the receivers DR. The blocker signal sets limitation on the maximum allowed receiver gain. In this project the receiver must be able to decode messages with 20% PER at a level of -101 dbm in presence of two IMD products at -27 dbm and a blocker signal at -15 dbm. One of the IMD products is adjusted 500 khz below or above the wanted frequency and the other is adjusted 1000 khz below or above it. The blocker signal is adjusted 5MHz below the wanted frequency. The input desired signal is adjusted to the same frequency as the previous test. This test is considered to simulate the worst case scenario. 5.4 Adjacent Channel Selectivity The adjacent channel selectivity is the receivers ability to receive desired signals in presence of an undesired interfering signal at the frequency of the channel directly above that of the desired signal. The requirment on the adjacent channel selectivity of the receiver is that it shall not be less than 70 db. 5.5 Signal-to-Noise Ratio As mentioned in Section 5.3 the receiver must be able to operate despite the existence of a blocker signal and two IMD products. In this worst case scenario it is possible that the mentioned signals interfere with each other, hence their amplitudes will be added together, creating an amplitude even higher than the amplitude of the blocker signal alone. This amplitude is calculated by using the equations below. A = P dbm/10, conversion of dbm to V (5.1) P = A2 R (5.2) A tot = A sig + A blocker + A IMD1 + A IMD2 (5.3) ( ) A 2 P tot,dbm = 10log tot R 10 3 (5.4) DR = P tot,dbm P signal (5.5) The resistor value R in Equation 5.2 is 50 Ω and is the antennas load resistance. In this case the signal caused by the mentioned interference is at a level of dbm. The difference between this level and the desired signal level at -101 db

43 5.5 Signal-to-Noise Ratio 23 gives a DR of 89.5 db. The decoder that is used for decoding the received messages requires an SNR of 12 db. This means that the receiver need an overall SNR of at least = dbfs to be able to decode a received message. dbfs is a representaion of the ratio between a signal and the full-scale signal of a system. For the sensitivity test the required SNR is different from above due to the receiver gain which is decided by the gain in the amplifiers and possibly the filters. Thus the SNR of this test will be presented after the components has been chosen, see Chapter 6.

44 24 Requirements

45 Chapter 6 Analog Front-End This chapter covers the chosen architecture of the analog front-end and motivates the choice of components for both PCB versions. Also both PCB designs are presented together with the measures taken to prevent EMC problems. 6.1 Front-End Architecture As mentioned earlier the main goal of this project is to build an RF receiver for the required frequency band containing as few analog parts as possible. This achievement is possible due to the concept of SDR together with SP Devices technology. As was mentioned in Section 3.3 this technology makes it possible to build a so called direct sampling receiver witout using mixer circuits and local oscillators for frequency down-conversion. Despite this fact the ADCs can not be directly attached to the antenna due to a couple of reasons. One reason is that without some attenuating bandpass filters strong undesired signals could saturate the ADCs. Another reason is that without amplification the weakest signals would never get strong enough to get sampled properly by the ADC. The closer a signal is to the ADC s input voltage range the more bits of the ADC are used. Figure 6.1 shows the chosen architecture for the analog front-end. DAC F P BPF1 LNA BPF2 AGC ADC1 ADC2 G A Figure 6.1. The architecture of the analog front-end. The first bandpass filter (BPF1) is intended to attenuate undesired out-of-band frequencies. The signal is then differentiated passing through a 1:1 transformer. 25

46 26 Analog Front-End The reason for differentiating the signal path is to reduce the sensitivity of disturbance in the transmission lines. This is further explained in Section 6.4. After the first filter the signal is amplified in a low noise amplifier (LNA), which is the most crucial part of this design due to the noise and IMD requirements depending on it, see Section The second bandpass filter (BPF2) is meant to filter out the wanted signal further before its amplitude is adjusted by the variable gain amplifier (VGA). The VGA is controlled to either amplify the signal or attenuate it, depending on the signal level. This is called automatic gain control (AGC) and is intended to push the signal amplitude as close as possible to the ADC:s input voltage range. The last stage of the front-end is the A/D-conversion. Here the two interleaved ADCs digitalize the received signal and feeds it through to a field-programmable gate array (FPGA) where the data is processed. The data processing in the FPGA is explained in Chapter 8. This front-end architecture is used on both PCB:s. The only difference is that in the first case the FPGA is off-board and is placed on a development board. On the second PCB the FPGA is placed on-board. 6.2 Choise of Components In this section the chosen components are presented together with the motivation of why they were chosen. Choosing and finding the right components for the analog front-end is very challenging. The choice of the different parts of the receiver must be done in parallel, because the properties of all parts depend on each other. In this project the ADC is chosen to be the starting point. The components used in the front-end alone do not differ between the two boards. The major difference is that the FPGA is mounted on-board in the second attempt while in the first case an external development board handled the signal processing ADC The analog-to-digital conversion is usually the part that limits the performance of the receiver. The most important parameters in choosing this component are resolution, sampling frequency, SNR and SFDR. SNR and f s Some calculations were done on the some of the ADC parameters, mentioned in Chapter 4, at different sampling frequencies, see Equations As it is shown, the channel bandwidth is chosen to be 25 khz which is usually the case in the VHF band[14]. The results of the calculations can be seen in table 6.1. The ADC resolution is defined as the number of bits at its output, i.e. the size of the binary word which represents the sampled analog signal. An alternative definition is the size of the least significant bit (LSB), Equation It should be noted that it is not a measure of the conversion quality. There are different error