FPGA implementation of high performance digital down converter for software defined radio

Author(s):  
Debarshi Datta ◽  
Partha Mitra ◽  
Himadri Sekhar Dutta
2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Indranil Hatai ◽  
Indrajit Chakrabarti

This paper deals with an FPGA implementation of a high performance FM modulator and demodulator for software defined radio (SDR) system. The individual component of proposed FM modulator and demodulator has been optimized in such a way that the overall design consists of a high-speed, area optimized and low-power features. The modulator and demodulator contain an optimized direct digital frequency synthesizer (DDFS) based on quarter-wave symmetry technique for generating the carrier frequency with spurious free dynamic range (SFDR) of more than 64 dB. The FM modulator uses pipelined version of the DDFS to support the up conversion in the digital domain. The proposed FM modulator and demodulator has been implemented and tested using XC2VP30-7ff896 FPGA as a target device and can operate at a maximum frequency of 334.5 MHz and 131 MHz involving around 1.93 K and 6.4 K equivalent gates for FM modulator and FM demodulator respectively. After applying a 10 KHz triangular wave input and by setting the system clock frequency to 100 MHz using Xpower the power has been calculated. The FM modulator consumes 107.67 mW power while FM demodulator consumes 108.67 mW power for the same input running at same data rate.


Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1323 ◽  
Author(s):  
Donald L. Hall ◽  
Ram M. Narayanan ◽  
David M. Jenkins

Wireless indoor positioning systems (IPS) are ever-growing as traditional global positioning systems (GPS) are ineffective due to non-line-of-sight (NLoS) signal propagation. In this paper, we present a novel approach to learning three-dimensional (3D) multipath channel characteristics in a probabilistic manner for providing high performance indoor localization of wireless beacons. The proposed system employs a single triad dipole vector sensor (TDVS) for polarization diversity, a deep learning model deemed the denoising autoencoder to extract unique fingerprints from 3D multipath channel information, and a probabilistic k-nearest-neighbor (PkNN) to exploit the 3D multipath characteristics. The proposed system is the first to exploit 3D multipath channel characteristics for indoor wireless beacon localization via vector sensing methodologies, a software defined radio (SDR) platform, and multipath channel estimation.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4123 ◽  
Author(s):  
Alexandru Lavric ◽  
Adrian I. Petrariu ◽  
Eugen Coca ◽  
Valentin Popa

The digital revolution has changed the way we implement and use connected devices and systems by offering Internet communication capabilities to simple objects around us. The growth of information technologies, together with the concept of the Internet of Things (IoT), exponentially amplified the connectivity capabilities of devices. Up to this moment, the Long Range (LoRa) communication technology has been regarded as the perfect candidate, created to solve the issues of the IoT concept, such as scalability and the possibility of integrating a large number of sensors. The goal of this paper is to present an analysis of the communication collisions that occur through the evaluation of performance level in various scenarios for the LoRa technology. The first part addresses an empirical evaluation and the second part presents the development and validation of a LoRa traffic generator. The findings suggest that even if the packet payload increases, the communication resistance to interferences is not drastically affected, as one may expect. These results are analyzed by using a novel Software Defined Radio (SDR) technology LoRa traffic generator, that ensures a high-performance level in terms of generating a large LoRa traffic volume. Despite the use of orthogonal variable spreading factor technique, within the same communication channel, the collisions between LoRa packets may dramatically decrease the communication performance level.


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