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farrow SRC
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Transcript of farrow SRC
INTRODUCTION
FPGA-based Implementation of Efficient Sample Rate Conversion for Software Defined Radios
Software Radio (SR) is a communication device in whichall the signal processing aspects are implemented as softwarecomponents. New standards, protocols and services can besupported by simply upgrading the software of the device [1].
A fundamental problem relating to SR design isthe complexity of the component (software module)immediately following the Analog to Digital converter (ADC).The main constituent blocks of the SR thus include (i) theanalog Radio Frequency (RF) front end, (ii) the digital IF stageand (iii) the baseband processor as shown in Fig. 1(DIGITAL IF BASED SR)
Most radios are hardware defined with little or no software control; they are fixed in function, have a short life and are designed to be discarded and replaced. To support multiple air interfaces it needs a dedicated hardware for each air interface, which increase the cost. Software defined radio (SDR) uses programmable digital devices to perform the signal processing necessary to transmit and receive baseband information at radio frequency, devices such as field programmable gate arrays (FPGAs) use software to provide the required signal processing functionality. This technology offers greater flexibility and potentially longer product life, since the radio can be upgraded very cost effectively with software. The SR has to support multiple standards, each requiring a different sampling clock. Hardware constraints limit a SR to only a single clock pulse, which in turn has to support multiple data rates. An efficient approach for sample rate conversion employing joint Cascaded Integrator Comb (CIC) compensation filter along with polynomial interpolation using the Farrow structure is proposed in [3]. This paper presents an innovative implementation of a SRC
architecture for multi-standard SR receivers, using a rapid
development and prototyping approach. The prime focus of
this paper is the hardware implementation and analysis of the
abovementioned architecture. The design has been
implemented and tested using ModelSim SE 6.5 and Xilinx
ISE Project Navigator, with top level simulations being done in
MATLAB. The architecture has been captured using VHDL.
DIGITAL UP CONVERTERFROM ALTERA Accelerating DUC & DDC System Designs for WiMAX
A digital up converter (DUC) provides the link between the digital
baseband and analog RF front end and is required on the transmitter of a
generic transceiver. The sampling frequency of the baseband data stream
is increased before it is modulated onto a high frequency carrier.
The algorithm consists ofthree stages shown in Figure 2:
1. Channel Filter – Applies pulse shaping to ensure that the spectral
mask and restrictions imposed by the regulatory body are not
violated.
2. Interpolation – The sampling frequency of the baseband samples are
increased. Filtering is required to mask spectral images that appear
as part of the interpolation process.
3. Mixer/Combiner – A numerically controlled oscillator (NCO)
generates two orthogonal sinusoids at the carrier frequency and
these are mixed with the I and Q streams. Finally the outputs of the
mixers are added together before being passed on to the digital-toanalog converter (DAC).
FROM Design and implementation of low power digital up converter for power line communication systems
The Digital up Converter is a digital circuit which implements
the conversion of a complex digital baseband signal to a real
passband signal. The input complex baseband signal is sampled at a
relatively low sampling rate, typically the digital modulation symbol
rate. The baseband signal is filtered and converted to a higher
sampling rate before being modulated onto a direct digitally
synthesized (DDS) carrier frequency.
WCDMA DUC shown in Figure 2 converts the complex
input chip-rate baseband signal d (j) to a real pass band signal s
(n). The baseband signal is filtered and converted to a higher
sampling rate before being modulated onto a DDS carrier c (n).
Radio Standard GSM
900
CDMA 2000 UMTS
Intermediate frequency (MHz) 80 80 80
Sampling Frequency (MSps) 160 160 160
Single channel Bandwidth (MHz) 0.2 1.25 5
Input Data rate (MSps) 0.270 1.2288 3.84
Sample Rate Conversion Ratio 590.77 130.02 41.66
A block diagram of the Digital up Converter is shown in Figure
1. Spectral shaping of the complex input signal is performed by the
PFIR filter. Typically this filter would be performing a Nyquist transmit
filter operation with a rate-change of 2. Bias-free convergent
rounding or truncation is employed between each processing stage
to limit the bit growth through the DUC
Output from each of the PFIR filters is input to each of the
CFIR filters, which is used to compensate for the droop within the
CIC filter and performs the second rate-change. The CFIR also
performs a rate-change of 2. The CFIR filter’s output drives the input
to the interpolating CIC filter, which is used for high sample rate
change of 4. The complex data stream from the CIC filter is mixed
with a local oscillator generated by the DDS. Results from the mixers
are combined, forming the final DUC result. The DUCresult is often
used as the input to a digital-to-analog converter (DAC) to generate
an intermediate frequency analog signal.
DUC DESIGN
1) WCDMA Channel Filter Design: The transmitted pulse shaper is an RRC filter with roll-off α = 0.22. The RRC filter needs to be designed to meet the Spectral Mask Requirements. It was found that a 45-tap symmetric RRC filter with
Chebyshev windowing (side lobe parameter set to 27 dB) met all of the filter objectives.The Chebyshev windowing provides better side lobe suppression than a rectangular window. Also, it is
a type of adjustable window that requires lower filter order to achieve similar performance than various windows.
Figure 4: Magnitude Response of RRC Filter