0000000000207912
AUTHOR
Thomas Jordbru
showing 6 related works from this author
Experimental validation for spectrum cartography using adaptive multi-kernels
2017
This paper validates the functionality of an algorithm for spectrum cartography, generating a radio environment map (REM) using adaptive radial basis functions (RBF) based on a limited number of measurements. The power at all locations is estimated as a linear combination of different RBFs without assuming any prior information about either power spectral densities (PSD) of the transmitters or their locations. The RBFs are represented as centroids at optimized locations, using machine learning to jointly optimize their positions, weights and Gaussian decaying parameters. Optimization is performed using expectation maximization with a least squares loss function and a quadratic regularizer. …
Design and implementation of a long-range low-power wake-up radio for IoT devices
2019
In this paper, we present the design and implementation of an on-demand wake-up radio (WuR) for long-range wireless IoT devices to reduce the power consumption, thereby increasing the life time of the devices. A custom narrow-band (NB) low noise amplifier is designed and implemented for WuR. The low-noise amplifier achieves a gain of 31 dB at 1 mA current consumption from a 6 V power supply. The WuR achieves a sensivity of -80 dBm by consuming just 1 mA, thereby optimizing the energy consumption of battery powered long-range IoT devices, hence reducing the power consumption and overall costs when deployed in large scale.
Implementation of a two stage fully-blind self-adapted spectrum sensing algorithm
2017
In this paper, an experimental validation of a combined two-stage detector called 2EMC is carried out. The detector is proposed in [1]. The 2EMC is composed of energy detector as a primary stage and maximum-minimum eigenvalue detector as a secondary stage. The 2EMC outperforms the two individual detectors in terms of the probability of detection for the same probability of false alarm. Regarding the complexity measured in the sensing time, the 2EMC sensing time is bounded by the sensing times of the two individual detectors. 2EMC incorporates noise estimation that is used by the energy detector, which makes it fully-blind and self-adapted detector. The noise estimator performance is express…
Radio measurements on a customized software defined radio module: A case study of energy detection spectrum sensing
2017
In this paper, we developed a software defined radio (SDR) system for implementing energy detection spectrum sensing. The SDR module can be used for a wide range of applications. The use of the SDR module is motivated by its high interoperability, availability for relatively cheaper prices and being software independent. Energy detection for cognitive radios is chosen for its simplicity and popularity. However, it is chosen as a representative for a very wide range of measurements and algorithms that can be implemented in the SDR. We have used probabilities of detection and false alarm with the receiver operating characteristics (ROC) curves as performance metrics for the implemented energy…
Spectrum cartography using adaptive radial basis functions: Experimental validation
2017
In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The perfor…
UDP flows in Cognitive Radios with Channel Aggregation and Fragmentation: A Test-bed Based Evaluation
2018
Channel aggregation (CA) and channel fragmentation (CF) have been studied extensively in cognitive radios (CRs) for many years. However, a test-bed evaluation for such techniques at flow level is still open. In this study, employing National Instruments devices, a test-bed is set up to evaluate the performance of UDP flows for CRs with CA and CF, considering the aspects of blocking, preemption, and throughput in probability. The measurements clearly show that there are performance improvements in applying CA and CF in CRs for UDP flows.