• Journal of electromagnetic engineering and science
• /
• v.11 no.4
• /
• pp.250-256
• /
• 2011

This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology. At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance. In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.

• Journal of Communications and Networks
• /
• v.14 no.2
• /
• pp.188-194
• /
• 2012

Cognitive networks (CNs) are capable of enabling dynamic spectrum allocation, and thus constitute a promising technology for future wireless communication. Whereas, the implementation of CN will lead to the requirement of an increased energy-arrival rate, which is a significant parameter in energy harvesting design of a cognitive user (CU) device. A well-designed spectrum-sensing scheme will lower the energy-arrival rate that is required and enable CNs to self-sustain, which will also help alleviate global warming. In this paper, spectrum sensing in a multi-user cognitive ad hoc network with a wide-band spectrum is considered. Based on the prospective spectrum sensing, we classify CN operation into two modes: Distributed and centralized. In a distributed network, each CU conducts spectrum sensing for its own data transmission, while in a centralized network, there is only one cognitive cluster header which performs spectrum sensing and broadcasts its sensing results to other CUs. Thus, a wide-band spectrum that is divided into multiple sub-channels can be sensed simultaneously in a distributed manner or sequentially in a centralized manner. We consider the energy consumption for spectrum sensing only of an analog-to-digital convertor (ADC). By formulating energy consumption for spectrum sensing in terms of the sub-channel sampling rate and whole-band sensing time, the sampling rate and whole-band sensing time that are optimal for minimizing the total energy consumption within sensing reliability constraints are obtained. A power dissipation model of an ADC, which plays an important role in formulating the energy efficiency problem, is presented. Using AD9051 as an ADC example, our numerical results show that the optimal sensing parameters will achieve a reduction in the energy-arrival rate of up to 97.7% and 50% in a distributed and a centralized network, respectively, when comparing the optimal and worst-case energy consumption for given system settings.

• Korean Journal of Soil Science and Fertilizer
• /
• v.36 no.2
• /
• pp.92-103
• /
• 2003

Research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. Reflectance in specific visible and near-infrared regions of the electromagnetic spectrum have proved useful in detection of nutrient deficiencies. Especially crop canopy sensors as a ground remote sensing measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and is in contrast to aircraft or satellite platforms that generate photographs or various types of digital images. Multi-spectral vegetation indices derived from crop canopy reflectance in relatively wide wave band can be used to monitor the growth response of plants in relation to environmental factors. The normalized difference vegetation index (NDVI), where NDVI = (NIR-Red)/(NIR+Red), was originally proposed as a means of estimating green biomass. The basis of this relationship is the strong absorption (low reflectance) of red light by chlorophyll and low absorption (high reflectance and transmittance) in the near infrared (NIR) by green leaves. Thereafter many researchers have proposed the other indices for assessing crop vegetation due to confounding soil background effects in the measurement. The green normalized difference vegetation index (GNDVI), where the green band is substituted for the red band in the NDVI equation, was proved to be more useful for assessing canopy variation in green crop biomass related to nitrogen fertility in soils. Consequently ground remote sensing as a non destructive real-time assessment of nitrogen status in plant was thought to be useful tool for site specific crop nitrogen management providing both spatial and temporal information.

• International journal of advanced smart convergence
• /
• v.7 no.3
• /
• pp.23-36
• /
• 2018

In wireless communication, efficient spectrum usage is an issue that has been an attractive research area for many technologies. Recently new technologies innovations allow compact radios to transmit with power efficient communication over very long distances. For example, Low-Power Wide Area Networks (LPWANs) are an attractive emerging platform to connect the Internet-of-Things (IoT). Especially, LoRa is one of LPWAN technologies and considered as an infrastructure solution for IoT. End-devices use LoRa protocol across a single wireless hop to communicate to gateway(s) connected to the internet which acts as a bridge and relays message between these LoRa end-devices to a central network server. The use of the (ISM) spectrum sharing for such long-range networking motivates us to implement spectrum sensing testbed for cognitive radio network based on LoRa and GNU radio. In cognitive radio (CR), secondary users (SUs) are able to sense and use this information to opportunistically access the licensed spectrum band in absence of the primary users (PUs). In general, PUs have not been very receptive of the idea of opportunistic spectrum sharing. That is, CR will harmfully interfere with operations of PUs. Subsequently, there is a need for experimenting with different techniques in a real system. In this paper, we implemented spectrum sensing for cognitive radio networks based on LoRa and GNU Radio, and further analyzed corresponding performances of the implemented systems. The implementation is done using Microchip LoRa evolution kits, USRPs, and GNU radio.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.7
• /
• pp.22-31
• /
• 2008

Cognitive radio should imply a proper sensing technique for detecting the presence of licensed users to identify the unused spectrum holes. Besides this, this information should also be used to opportunistically provide communication among secondary users. At the same time the performance of the primary user should not be declined by the secondary users. The detection of licensed users may be significantly difficult for shadowing effect. To prevail over this problem cooperative spectrum sensing, In which the combined observation information gained by multiple secondary users is employed to achieve higher performance of detection, has been inspected. However, the primary challenge of cooperative sensing lays in its ability to detect the presence of licensed user quickly and accurately. In this paper, we have used UltraWideBand (UWB) to detect the presence of licensed users and transmit the sensing information among the nodes of the network. UWB has the capability of transmitting data at a very high rate. It is unique in co-existence capability with narrow band systems. Here, we have shown that the detection probability of licensed user is improved by means of transmitting the spectrum sensing information via UWB. We also have analyzed the throughput of the proposed technique and compared the result with existing sensing method.

• ETRI Journal
• /
• v.32 no.2
• /
• pp.214-221
• /
• 2010

Radio frequency (RF) subsampling can be used by radio receivers to directly down-convert and digitize RF signals. A goal of a cognitive radio/software defined ratio (CR/SDR) receiver design is to place the analog-to-digital converter (ADC) as near the antenna as possible. Based on this, a band-pass sampling (BPS) frontend for CR/SDR is proposed and verified. We present a receiver architecture based second-order BPS and signal processing techniques for a digital RF frontend. This paper is focused on the benefits of the second-order BPS architecture in spectrum sensing over a wide frequency band range and in multiband receiving without modification of the RF hardware. Methods to manipulate the spectra are described, and reconstruction filter designs are provided. On the basis of this concept, second-order BPS frontends for CR/SDR systems are designed and verified using a hardware platform.

• Journal of Satellite, Information and Communications
• /
• v.2 no.2
• /
• pp.53-58
• /
• 2007

The Satellite Mobile Communication System holds several advantages, such as wide coverage that guarantees the communication in a huge area. It is suitable in the ocean and forest and especially in emergency situation. However, the licensed frequency is not always occupied within all coverage and all the time. The actual utilization rate is relatively low compared to other wireless communications such as cellular systems. There are a large amount of white spaces in its coverage. Therefore, it is necessary to consider introducing additional services such as data communication, in order to increase the spectrum utilization as well as the revenue of the Satellite service provider. In this paper, we first analyze the possibility to implement new services in the licensed band of satellite mobile phone by its provider. Then we address the most significant issue for the implementation of current service, which is how to accurately detect the satellite mobile terminals. Finally, we suggest two new possible solutions namely, eigenvalue detection based methods to find out the existence of transmitted signal from the satellite mobile terminals.

• Korean Journal of Remote Sensing
• /
• v.35 no.3
• /
• pp.375-387
• /
• 2019

The use of drone-based hyperspectral image offers considerable advantages in high resolution remote sensing applications. The primary objective of this study was to select the optimal bands based on hyperspectral image for the estimation yield of the chinese cabbage. The hyperspectral narrow bands were acquired over 403.36 to 995.19 nm using a 3.97 nm wide, 150 bands, drone-based hyperspectral imaging sensor. Fresh weight data were obtained from 2,031 sample for each field survey. Normalized difference vegetation indices were computed using red, red-edge and near-infrared bands and their relationship with quantitative each fresh weights were established and compared. As a result, predominant proportion of fresh weights are best estimated using data from three narrow bands, in order of importance, centered around 697.29 nm (red band), 717.15 nm (red-edge band) and 808.51 nm (near-infrared band). The study determined three spectral bands that provide optimal chinese cabbage productivity in the visible and near-infrared portion of the spectrum.

• Journal of IKEEE
• /
• v.26 no.4
• /
• pp.568-576
• /
• 2022

Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.447-460
• /
• 2022

It is well known that satellite synthetic aperture radar interferometry (InSAR) has been widely used for the observation of surface displacement owing to earthquakes, volcanoes, and subsidence very precisely. In wetlands where vegetation exists on the surface of the water, it is possible to create a water level change map with high spatial resolution over a wide area using the InSAR technique. Currently, a number of imaging radar satellites are in operation, and most of them support a ScanSAR mode observation to gather information over a large area at once. The Cienaga Grande de Santa Marta (CGSM) wetland, located in northern Colombia, is a vast wetland developed along the Caribbean coast. The CGSM wetlands face serious environmental threats from human activities such as reclamation for agricultural uses and residential purposes as well as natural causes such as sea level rise owing to climate change. Various restoration and protection plans have been conducted to conserve these invaluable environments in recognition of the ecological importance of the CGSM wetlands. Monitoring of water level changes in wetland is very important resources to understand the hydrologic characteristics and the in-situ water level gauge stations are usually utilized to measure the water level. Although it can provide very good temporal resolution of water level information, it is limited to fully understand flow pattern owing to its very coarse spatial resolution. In this study, we evaluate the L-band ALOS-2 PALSAR-2 ScanSAR mode to observe the water level change over the wide wetland area using the radar interferometric technique. In order to assess the quality of the interferometric product in the aspect of spatial resolution and coherence, we also utilized ALOS-2 PALSAR-2 stripmap high-resolution mode observations.