Cognitive radio transmitter with a broadband clean frequency spectrum

The tremendous increase in wireless communication over the last few decades has led to a congestion of the radio frequency (RF) spectrum. As suitable RF spectrum is scarce, attempts are being made to use the RF spectrum in a more intelligent efficient way. A Cognitive Radio (CR) addresses this problem by Dynamic Spectrum Access, i.e. measure which spectrum is temporarily locally free and then use it. The CR transmitter needs to be flexible to be able to transmit where ever there is free spectrum available.\ud Conventional transmitters not only produce the desired upconverted information signal but also many unwanted harmonics of the local oscillator (LO) and distortion products related to the baseband signal. These unwanted products have been usually suppressed using dedicated RF filters which are narrowband and inflexible. For CR transmitters flexibility is a key requirement, and hence other techniques are wanted to suppress unwanted products, without using the inflexible filters.\ud Previous research has shown that polyphase multipath circuits can in principle cancel a large number of harmonics and distortion products. However, the upconversion was done using a large number of paths which is not very power efficient. In this work a less complex and more power efficient implementation of this technique is proposed. The proposal is actually based on a combination of three techniques, namely: 1) 8-path polyphase upconversion, 2) Tuning of the LO duty cycle ratio to close to 7/16 and 3) Tunable first order RF filter.\ud To verify the functionality of the proposed techniques, a flexible 8-path transmitter chip was fabricated in a 160 nanometer CMOS technology. The transmitter works over 3 octaves in frequency from 100MHz to 800MHz. Measurements show that the frequency agile transmitter achieves a broadband clean output spectrum where all unwanted products are at least 40dB below the wanted transmit signal. This is the first polyphase multi-path transmitter combining the baseband multi-phase generation and RF circuit on one chip. Compared to other harmonic rejection transmitter designs with similar frequency range, it is more power efficient and has better LO leakage and image rejection. This chip suppresses ALL LO harmonics and distortion products for ALL frequencies, without any external filters

Towards suppression of all harmonics in a polyphase multipath transmitter

This work proposes a direct conversion transmitter architecture intended for cognitive radio applications. The architecture is based on the poly-phase multipath technique, which has been shown to cancel out many of the harmonics, sidebands and nonlinearity contributions of a power up-converter using a large number of signal paths. This work proposes a design only using 8 paths which is able to achieve <−40dBc harmonic suppression for all harmonics, including the dominant 7th and 9th harmonic. This is done with a combination of duty cycle control of the Local Oscillator (LO) waveform and tunable filtering with only a first order roll-off

A 100 – 800MHz 8-Path polyphase transmitter with mixer duty-cycle control achieving

Radio transceivers capable of dynamic spectrum access require frequency agile transmitters with a clean output spectrum. High-Q filters are difficult to implement on chip and have limited tuning range. Transmitters with high linearity and broadband harmonic rejection can be more flexible and require less filtering. However, traditional Harmonic Rejection mixers suppress only a few harmonics. This paper presents an 8-path poly-phase transmitter, which exploits mixer-LO duty-cycle control and a tunable first-order RC low-pass filter to suppress ALL harmonics to below -40dBc. The optimum duty-cycle theoretically is 43.65% and a resolution of better than 0.1% is required to keep the spread in harmonic rejection within 1dB. We propose a simple monotonic duty-cycle control circuit and show by design equations and measurements that it achieves the required resolution over 3 octaves of frequency range. Also, analysis indicates that LO duty-cycle reduction compared to 50% improves power upconverter efficiency. A transmitter realized in 0.16￭m CMOS works from 100-800MHz at a maximum single tone output power of 10.8dBm with an efficiency of 8.7%, outperforming previous designs. The OIP3 is >21dBm, while the LO leakage and image rejection is better than -45dBc

A 100&#x2013;800 MHz 8-Path Polyphase Transmitter With Mixer Duty-Cycle Control Achieving <formula formulatype="inline"><tex Notation="TeX"><-</tex></formula>40 dBc for ALL Harmonics

Radio transceivers capable of dynamic spectrum access require frequency agile transmitters with a clean output spectrum. High-Q filters are difficult to implement on chip and have limited tuning range. Transmitters with high linearity and broadband harmonic rejection can be more flexible and require less filtering. However, traditional Harmonic Rejection mixers suppress only a few harmonics. This paper presents an 8-path poly-phase transmitter, which exploits mixer-LO duty-cycle control and a tunable first-order RC low-pass filter to suppress ALL harmonics to below -40dBc. The optimum duty-cycle theoretically is 43.65% and a resolution of better than 0.1% is required to keep the spread in harmonic rejection within 1dB. We propose a simple monotonic duty-cycle control circuit and show by design equations and measurements that it achieves the required resolution over 3 octaves of frequency range. Also, analysis indicates that LO duty-cycle reduction compared to 50% improves power upconverter efficiency. A transmitter realized in 0.16￭m CMOS works from 100-800MHz at a maximum single tone output power of 10.8dBm with an efficiency of 8.7%, outperforming previous designs. The OIP3 is >21dBm, while the LO leakage and image rejection is better than -45dBc

An Insight into the Machine-Learning-Based Fileless Malware Detection

In recent years, massive development in the malware industry changed the entire landscape for malware development. Therefore, cybercriminals became more sophisticated by advancing their development techniques from file-based to fileless malware. As file-based malware depends on files to spread itself, on the other hand, fileless malware does not require a traditional file system and uses benign processes to carry out its malicious intent. Therefore, it evades conventional detection techniques and remains stealthy. This paper briefly explains fileless malware, its life cycle, and its infection chain. Moreover, it proposes a detection technique based on feature analysis using machine learning for fileless malware detection. The virtual machine acquired the memory dumps upon executing the malicious and non-malicious samples. Then the necessary features are extracted using the Volatility memory forensics tool, which is then analyzed using machine learning classification algorithms. After that, the best algorithm is selected based on the k-fold cross-validation score. Experimental evaluation has shown that Random Forest outperforms other machine learning classifiers (Decision Tree, Support Vector Machine, Logistic Regression, K-Nearest Neighbor, XGBoost, and Gradient Boosting). It achieved an overall accuracy of 93.33% with a True Positive Rate (TPR) of 87.5% at zeroFalse Positive Rate (FPR) for fileless malware collected from five widely used datasets (VirusShare, AnyRun, PolySwarm, HatchingTriage, and JoESadbox)

Linear Discriminant Analysis-Based Dynamic Indoor Localization Using Bluetooth Low Energy (BLE)

Due to recent advances in wireless gadgets and mobile computing, the location-based services have attracted the attention of computing and telecommunication industries to launch location-based fast and accurate localization systems for tracking, monitoring and navigation. Traditional lateration-based techniques have limitations, such as localization error, and modeling of distance estimates from received signals. Fingerprinting based tracking solutions are also environment dependent. On the other side, machine learning-based techniques are currently attracting industries for developing tracking applications. In this paper we have modeled a machine learning method known as Linear Discriminant Analysis (LDA) for real time dynamic object localization. The experimental results are based on real time trajectories, which validated the effectiveness of our proposed system in terms of accuracy compared to naive Bayes, k-nearest neighbors, a support vector machine and a decision tree

Getting Smarter about Smart Cities: Improving Data Security and Privacy through Compliance

Smart cities assure the masses a higher quality of life through digital interconnectivity, leading to increased efficiency and accessibility in cities. In addition, a huge amount of data is being exchanged through smart devices, networks, cloud infrastructure, big data analysis and Internet of Things (IoT) applications in the various private and public sectors, such as critical infrastructures, financial sectors, healthcare, and Small and Medium Enterprises (SMEs). However, these sectors require maintaining certain security mechanisms to ensure the confidentiality and integrity of personal and critical information. However, unfortunately, organizations fail to maintain their security posture in terms of security mechanisms and controls, which leads to data breach incidents either intentionally or inadvertently due to the vulnerabilities in their information management systems that either malicious insiders or attackers exploit. In this paper, we highlight the importance of data breaches and issues related to information leakage incidents. In particular, the impact of data breaching incidents and the reasons contributing to such incidents affect the citizens’ well-being. In addition, this paper also discusses various preventive measures such as security mechanisms, laws, standards, procedures, and best practices, including follow-up mitigation strategies

Carbohydrate Partitioning, Growth and Ionic Compartmentalisation of Wheat Grown under Boron Toxic and Salt Degraded Land

Cultivation of crops in salt-affected soils is a major challenge for growers. Despite the use of multiple amendments, salinity stresses adversely affect the crops to some extent. On the other hand, imbalance in the use of boron (B) as a nutrient also creates toxicity. Mismanagement of B fertilizer application decreases the growth and yield of crops. It is necessary to study in depth the adverse effects of salinity and B toxicity. This is why the current research work was conducted in a glass house at Murdoch University, Perth, Australia. The aim of study was to investigate the influence of salinity and B toxicity on carbohydrate partitioning, growth, and ionic composition of two Australian wheat varieties. There were four treatments, i.e., control, high B (15 kg ha−1), salinity (15 dS m−1), and B + salinity. The results showed that the salt-tolerant Halberd (HB) variety accumulated more Na+, B, and Cl− in their leaf sheath and kept the leaf blades free of these toxic ions as compared to the sensitive variety Westonia (WS). Water-soluble carbohydrate (WSC; i.e., glucose, sucrose, fructose, and fructans) concentration increased in response to individual as well as combined constrains of soil salinity and toxic B in the leaf blade of both tolerant and sensitive wheat varieties, but the increase was higher in the tolerant variety as compared to the sensitive one. The concentration of WSCs in leaf sheath of the salt-tolerant wheat variety was increased in response to stress conditions, but those remained low in salt-sensitive ones. Therefore, the salt-tolerant HB genotype was found to be a good source for future wheat breeding programs or to be grown by farmers in B toxic, saline, and B toxic–saline conditions