State of the Art and Challenges of Radio Spectrum Monitoring in China

Wireless signal recognition is becoming increasingly more significant for spectrum monitoring, spectrum management, and secure communications. Consequently, it will become a key enabler with the emerging fifth-generation (5G) and beyond 5G communications, Internet of Things networks, among others. State-of-the-art studies in wireless signal recognition have only focused on a single task which in many cases is insufficient information for a system to act on. In this work, for the first time in the wireless communication domain, we exploit the potential of deep neural networks in conjunction with multi-task learning (MTL) framework to simultaneously learn modulation and signal classification tasks. The proposed MTL architecture benefits from the mutual relation between the two tasks in improving the classification accuracy as well as the learning efficiency with a lightweight neural network model. Additionally, we consider the problem of heterogeneous wireless signals such as radar and communication signals in the electromagnetic spectrum. Accordingly, we have shown how the proposed MTL model outperforms several state-of-the-art single-task learning classifiers while maintaining a lighter architecture and performing two signal characterization tasks simultaneously. Finally, we also release the only known open heterogeneous wireless signals dataset that comprises of radar and communication signals with multiple labels.

Download Full-text

The Nature of Radio Interference and Some Lines of Defense

International Astronomical Union Colloquium ◽

10.1017/s0252921100004061 ◽

1991 ◽

Vol 112 ◽

pp. 240-248

Author(s):

J. Richard Fisher

Keyword(s):

Radio Astronomy ◽

Dynamic Range ◽

State Of The Art ◽

High Dynamic Range ◽

Radio Spectrum ◽

The State ◽

Radio Interference ◽

Frequency Bands ◽

High Dynamic ◽

Technical Effort

ABSTRACTAs competition for radio spectrum space continues to increase, radio astronomers can expect to put more technical effort into ways of observing in the presence of interference. Much of the spectrum outside of exclusive radio astronomy frequency bands will continue to be available to the science if receivers and antennas are designed to make efficient use of times, frequencies, directions, and coherence envelopes that do not contain sources of interference. The paper outlines the state of the art in antenna sidelobe reduction, high dynamic range spectrometers, and receiver designs for handling large signals. Techniques for excising pulsed interference on very short timescales and a few thoughts on signal canceling techniques are discussed.

Download Full-text

USRP: A Flexible Platform for Spectrum Monitoring

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.610.233 ◽

2014 ◽

Vol 610 ◽

pp. 233-240 ◽

Cited By ~ 1

Author(s):

Jing Jing Yang ◽

Ming Huang ◽

Jiang Yu ◽

Lin Li ◽

Ling Li

Keyword(s):

Signal Processing ◽

Software Defined Radio ◽

Time Spectrum ◽

Radio Spectrum ◽

Complex Signal ◽

Radio Communication ◽

Spectrum Monitoring ◽

Processing Procedure ◽

Radio Communication System ◽

Web Publishing

Software-defined radio (SDR) is a kind of radio communication system which attempts to place much or most of the complex signal handling involved in receivers and transmitters into the digital style. As wireless technologies become ubiquitous, SDR are gaining popularity. In this work, we introduce the SDR platform USRP with emphasizes on hardware components, signal processing procedure and the supporting software. A radio spectrum monitoring system based on USRP and LabVIEW is designed and implemented, and web publishing of the real time spectrum is realized.

Download Full-text

Multi-task Learning Approach for Automatic Modulation and Wireless Signal Classification

10.36227/techrxiv.15156978 ◽

2021 ◽

Cited By ~ 1

Author(s):

Anu Jagannath ◽

Jithin Jagannath

Keyword(s):

State Of The Art ◽

Spectrum Management ◽

Signal Classification ◽

Electromagnetic Spectrum ◽

Signal Recognition ◽

Single Task ◽

Communication Signals ◽

Spectrum Monitoring ◽

Task Learning ◽

Wireless Signal

Wireless signal recognition is becoming increasingly more significant for spectrum monitoring, spectrum management, and secure communications. Consequently, it will become a key enabler with the emerging fifth-generation (5G) and beyond 5G communications, Internet of Things networks, among others. State-of-the-art studies in wireless signal recognition have only focused on a single task which in many cases is insufficient information for a system to act on. In this work, for the first time in the wireless communication domain, we exploit the potential of deep neural networks in conjunction with multi-task learning (MTL) framework to simultaneously learn modulation and signal classification tasks. The proposed MTL architecture benefits from the mutual relation between the two tasks in improving the classification accuracy as well as the learning efficiency with a lightweight neural network model. Additionally, we consider the problem of heterogeneous wireless signals such as radar and communication signals in the electromagnetic spectrum. Accordingly, we have shown how the proposed MTL model outperforms several state-of-the-art single-task learning classifiers while maintaining a lighter architecture and performing two signal characterization tasks simultaneously. Finally, we also release the only known open heterogeneous wireless signals dataset that comprises of radar and communication signals with multiple labels.

Download Full-text

Energy budget and methods for determining coordinates for a radiomonitoring system based on a small spacecraft

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v21.i2.pp945-956 ◽

2021 ◽

Vol 21 (2) ◽

pp. 945

Author(s):

Altay Aitmagambetov ◽

Yuri Butuzov ◽

Valery Tikhvinskiy ◽

...

Keyword(s):

Radio Emission ◽

Energy Budget ◽

Radio Spectrum ◽

Monitoring Systems ◽

Emission Sources ◽

Radio Lines ◽

Spectrum Monitoring ◽

Small Spacecraft ◽

Radio Monitoring ◽

The Republic

The existing ground-based radio monitoring systems do not allow performing the functions and tasks of radio spectrum monitoring in a quality manner. Therefore, to improve the efficiency of the radio spectrum monitoring systems for countries with a large territory, such as the Republic of Kazakhstan, it is proposed to use low-orbit small spacecrafts as radio monitoring stations. The analysis of the energy budget of radio lines on the basis of existing radio electronic means on the territory of the Republic of Kazakhstan, carried out in this work, showed the possibility of using low-orbit small spacecrafts for performing the functions and tasks of radio monitoring. The paper proposes and develops a method for determining the coordinates of radio emission sources based on the goniometric method using scanning antennas on board of one spacecraft. The ranges of the antenna scanning angles are substantiated, and the estimates of the coordinates determination errors are made. Algorithms have been developed and computer programs have been compiled to determine the coordinates of the radio emission sources, which will make it possible to use this method at the initial stages of developing a radio spectrum monitoring system based on one small spacecraft.

Download Full-text

State-of-the-Art in Policy and Regulation of Radio Spectrum

Signals and Communication Technology - Cognitive Radio Policy and Regulation ◽

10.1007/978-3-319-04022-6_1 ◽

2014 ◽

pp. 1-48 ◽

Cited By ~ 3

Author(s):

Arturas Medeisis ◽

Oliver Holland

Keyword(s):

State Of The Art ◽

Radio Spectrum

Download Full-text

Radio Spectrum Monitoring and Surveillance System in the VHF/UHF Frequency Band

10.1109/telfor52709.2021.9653314 ◽

2021 ◽

Author(s):

Verica B. Marinkovic-Nedelicki ◽

Jovan D. Radivojevic ◽

Predrag M. Petrovic ◽

Aleksandar V. Lebl

Keyword(s):

Frequency Band ◽

Surveillance System ◽

Radio Spectrum ◽

Spectrum Monitoring ◽

Monitoring And Surveillance

Download Full-text

Strength of Crowd (SOC)—Defeating a Reactive Jammer in IoT with Decoy Messages

Sensors ◽

10.3390/s18103492 ◽

2018 ◽

Vol 18 (10) ◽

pp. 3492 ◽

Cited By ~ 5

Author(s):

Savio Sciancalepore ◽

Gabriele Oligeri ◽

Roberto Di Pietro

Keyword(s):

Ieee 802.15.4 ◽

State Of The Art ◽

Mac Protocol ◽

Radio Spectrum ◽

Wireless Sensor ◽

Protocol Stack ◽

Network Nodes ◽

Extensive Simulation ◽

Experimental Platform ◽

Experimental Campaign

We propose Strength of Crowd (SoC), a distributed Internet of Things (IoT) protocol that guarantees message broadcast from an initiator to all network nodes in the presence of either a reactive or a proactive jammer, that targets a variable portion of the radio spectrum. SoC exploits a simple, yet innovative and effective idea: nodes not (currently) involved in the broadcast process transmit decoy messages that cannot be distinguished (by the jammer) from the real ones. Therefore, the jammer has to implement a best-effort strategy to jam all the concurrent communications up to its frequency/energy budget. SoC exploits the inherent parallelism that stems from the massive deployments of IoT nodes to guarantee a high number of concurrent communications, exhausting the jammer capabilities and hence leaving a subset of the communications not jammed. It is worth noting that SoC could be adopted in several wireless scenarios; however, we focus on its application to the Wireless Sensor Networks (WSN) domain, including IoT, Machine-to-Machine (M2M), Device-to-Device (D2D), to name a few. In this framework, we provide several contributions: firstly, we show the details of the SoC protocol, as well as its integration with the IEEE 802.15.4-2015 MAC protocol; secondly, we study the broadcast delay to deliver the message to all the nodes in the network; and finally, we run an extensive simulation and experimental campaign to test our solution. We consider the state-of-the-art OpenMote-B experimental platform, adopting the OpenWSN open-source protocol stack. Experimental results confirm the quality and viability of our solution.

Download Full-text