The following table compares various SDR design methods based on various parameters such as execution, power efficiency, cost, throughput, and cost, among others. This table aids in the selection of the best method for SDR designs. SDR technology aims to reduce costs in providing end-users with seamless wireless communications — enabling them to connect with whomever they want, whenever they want to, and in whatever manner is necessary. From end users to business travelers to soldiers on the front lines, SDR technology benefits everyone.
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Obtain comprehensive insights on the Software Defined Radio Industry. COVID has impacted all businesses across the globe. Check Out. The novel coronavirus has affected all businesses across the globe Click Here. All You Need to Know About Software Defined Radio Software defined radio technology has followed a course that is strikingly close to that of computers. Princy A. J May 13, About the Author s. Recent Post. January 11, What is a Pet Insurance and What does it Cover?
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You're going to remove this assignment. Are you sure? Yes No. Professor in Dept. Additional information Data set: ieee. Publisher IEEE. You have to log in to notify your friend by e-mail Login or register account. In Section III, details of the receiver are discussed, including all computational units for signal processing. Implementation results are addressed in Section V.
Conclusion is made in Section VI. It is worth mentioning that no prior knowledge of HDL coding is required since all the units are designed in Simulink or Matlab code. Data generated from the host computer are fed into the FPGA and then get processed.
These units are optimized for HDL code generation and perform baseband signal processing to transform the source data to baseband waveform. Convolutional Coding Figure 2 shows the architecture of convolutional encoder. When source data, including both pilot and payload, come in this module, the valid signal and data are split first.
As an example, the polynomial of the convolutional encoder is , Considering that the convolutional encoder doubles the data rate of payload, the rate of pilot also needs to be doubled.
Both the pilot and payload pre-QPSK formation module pair two sequential bits into an unsigned two-bit output, which is the input format expected by the symbol mapping component. Symbol Mapping Gray mapping is a multilevel modulation scheme in which there is only one bit change between two successive values. Gray codes are widely utilized to facilitate error correction by combining with forward error correction FEC codes.
Due to the special mapping method, a receiver could recovery the original constellation point which drifts into the area of an adjacent point. Pulse Shaping In digital communications, pulse shaping filters are designed to remove the impact of intersymbol interference ISI on transmission process. Thus, the filters must have some special requirements : frequency response with sufficient selectivity and attenuation to suppress noise and interference in adjacent channels.
Raised cosine RC filters are a family of responses that achieves the required zero ISI minimizing the occupied. Figure 3. The structure of receiver computation units in FPGA. To make the transmitted signal fit in frequency band, the pulse shaping module adopts an FIR interpolation filter with a root raised cosine impulse response.
In this module, the raised cosine transmit filter block performs root raised cosine pulse shaping with a roll off factor of 0. The desired roll off factor ranges from 0. In order to make the pulse shaping equally distributed between the transmitter and receiver, transmitter side pulse shaping is often combined with matched filter on the receiver side.
In this case, the two filters can achieve optimal tolerance for noise. The detailed receiver design is given in this section, including coarse and fine frequency compensation, timing recovery with fixed-rate resampling, frame synchronization, demodulation and data decoding.
The structure of computational units of receiver is shown in Figure 3. In our demonstration, we choose the baseband sampling rate of Considering the fact that the FPGA can process much faster than that, we buffer each frame of received data first before feed it to the FPGA processing unit.
Similarly, the receiver output from the FPGA are also buffered and sent to the host PC to be translated from bits to readable message. This is to accommodate the high speed processing at the FPGA. After going through all the computational processes implemented on FPGA, invalid data are removed and valid data are translated and printed on the screen. The message printed on screen is expected to be a repeated sequence of Hello World , where are 3 digits increasing from to Automatic Gain Control The stability of the signal amplitude at the inputs of the carrier and timing recovery loops must be considered in the receiver design.
The automatic gain control AGC is an adaptive subsystem and accounts for maintaining the amplitude and strength of the received signal. The structure of AGC is shown in Figure 4. The product of the input signal and the value from the loop gain generates the output signals. The error signal comes from the difference between a reference value and the product of value from the loop gain and the modulus of the input.
Once received signal is fed in, AGC is performed to guarantee the accuracy of all the operations. Thus, the equivalent gains of the phase and timing error detectors can keep nearly constant over time. Figure 4. Automatic gain control module in receiver. Coarse Frequency Compensation The coarse frequency compensation is designed to roughly estimate and compensate the frequency offset of the received signal.
Figure 5 shows the coarse frequency compensation module. This power-raising operation is implemented by two product blocks. This algorithm is based on autocorrelation method, which is implemented by an FIR filter and an accumulator. Actually, the filter is an autocorrelator in the structure of an FIR filter, which calculates autocorrelation value.
Compared with an FFT method, this algorithm uses much less hardware resources. In addition, pipeline registers are used in the autocorrelation path to improve the speed. However, even if the coarse frequency compensation module estimates the major frequency offset, there is still a residual frequency offset. Usually the remaining frequency offset causes a rotation of the constellation. Fine Frequency Compensation Fine frequency compensation needs to be implemented after coarse frequency compensation.
The fine frequency compensation module is shown in Figure 6, which further estimates the residual frequency offset. Figure 5. Coarse frequency compensation module in receiver.
Therefore a maximum likelihood PED is placed to estimate the phase difference between the current signal and the expected one. The phase difference is fed into a tunable proportional-plus-integral loop filter where the normalized loop bandwidth and damping factor are usually tuned as 0. This configuration ensures that signal can quickly be locked to the expected phase while introducing little phase noise.
The NCO block takes the loop filter output as input and acts as a complex exponential signal generator and therefore compensates the residual frequency offset. Figure 6. Fine frequency compensation module in receiver. Timing Recovery The timing recovery module calculates and compensates the timing error. The timing recovery subsystem is designed to choose the instants at which the incoming signals are sampled in the receiver.
The timing recovery module is shown in Figure 7. It is also implemented with a PLL, which includes an interpolation filter, a zero-crossing timing error detector ZCTED , a loop filter and an interpolation control module [19] [20]. The ZCTED detects the timing errors with the interpolants generated from the interpolation filter, cascaded by a tunable proportional-plus-integral loop filter [19] [21], whose normalized loop bandwidth is set to 0.
The purpose of the interpolation control block is to provide the interpolators with the basepoint index and fractional interval for each desired interpolant. The underflow signal will be activated and indicates one extra or missing interpolant when the timing error reaches symbol boundaries. The interpolation control block also updates the timing difference for the interpolation filter and generates the interpolants at the optimum sampling time.
The interpolation filter is a farrow parabolic filter and is simplified with special parameters [19]. When the signal is fed into timing recovery module, the interpolation filter interpolates the signal according to the estimated timing error and corrects it. Figure 7. Timing recovery module in receiver. Frame Synchronization and Demodulation Figure 8 shows the frame synchronization and demodulation module.
This module is designed to find the header of a frame so that the data can be located and demodulated. In this work, a bit Barker code is adopted as the pilot [22]. With the characteristics of the Barker code, auto-correlation function is executed in the matched filter block to correlate the Barker code against the received signal [23].
Then the modulus of the matched filter output is compared with a threshold. The threshold value has an important influence on miss probability and frame synchronization accuracy. Usually a larger value increases the miss probability whereas a smaller value may result less accurate frame alignment. Thus, it is a trade-off especially at lower signal to noise ratio SNR. For high SNR, a larger threshold value can be used. In our design, the threshold is set to 16, which is a compromised value between miss probability and accuracy for the consideration of both low and high SNR cases.
Once the output value of modulus block exceeds the threshold, it is indicated that a frame is detected and therefore its pilot and payload can be accurately located. The frame control block is also enabled, which splits a frame into two parts: pilot and payload.
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