Learning Exact Topology of a Loopy Power Grid from Ambient Dynamics

Estimation of the operational topology of the power grid is necessary for optimal market settlement and reliable dynamic operation of the grid. This paper presents a novel framework for topology estimation for general power grids (loopy or radial) using time-series measurements of nodal voltage phase angles that arise from the swing dynamics. Our learning framework utilizes multivariate Wiener filtering to unravel the interaction between fluctuations in voltage angles at different nodes and identifies operational edges by considering the phase response of the elements of the multivariate Wiener filter. The performance of our learning framework is demonstrated through simulations on standard IEEE test cases.Comment: accepted as a short paper in ACM eEnergy 2017, Hong Kon

Spectrum Sensing Techniqes in Cognitive Radio: Cyclostationary Method

Cognitive Radios promise to be a major shift in wireless communications based on developing a novel approach which attempt to reduce spectrum scarcity that growing up in the past and waited to increase in the future. Since formulating stages for increasing interest in wireless application proves to be extremely challenging, it is growing rapidly. Initially this growth leads to huge demand for the radio spectrum. The novelty of this approach needs to optimize the spectrum utilization and find the efficient way for sharing the radio frequencies through spectrum sensing process. Spectrum sensing is one of the most significant tasks that allow cognitive radio functionality to implement and one of the most challenging tasks. A main challenge in sensing process arises from the fact that, detecting signals with a very low SNR in back ground of noise or severely masked by interference in specific time based on high reliability. This thesis describes the fundamental cognitive radio system aspect based on design and implementation by connecting between the theoretical and practical issue. Efficient method for sensing and detecting are studied and discussed through two fast methods of computing the spectral correlation density function, the FFT Accumulation Method and the Strip Spectral Correlation Algorithm. Several simulations have been performed to show the ability and performance of studied algorithms.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

CYCLOSTATIONARY FEATURES OF PAL TV AND WIRELESS MICROPHONE FOR COGNITIVE RADIO APPLICATIONS

Frequency spectrum being a scarce resource in communication system design, spectrum sharing seems to be the solution to an optimal utilization of frequency spectrum. The traditional fixed frequency allocation is not suitable for futuristic networks that demand more and more spectrum for new wireless services. Cognitive radio is a new emerging technology based on spectrum sharing concept. Spectrum sensing is a vital task in this emerging technology by which it is able to scan the frequency spectrum to identify the unused spectrum bands and utilize them. In this thesis, we discuss spectrum sensing in the context of IEEE 802.22 Wireless Regional Area Network (WRAN). In order to do so, we develop the co-existence scenario with three cases according to geographical positions of primary services and secondary service. In WRAN application, the SUs utilize the unused channel in TV spectrum, which means that the primary users are TV service and other FCC part 74 low power licensed devices. We focus on special case of Analog TV-PAL service and wireless microphone service as part 74 devices. Before discussing the spectrum sensing technique, we propose architecture for sensing receiver. The concept of noise uncertainty is also introduced in this context. The cyclostationarity theory is introduced and we explain the motivation behind using the theory for spectrum sensing and the reason that makes the cyclostationary features detector a powerful detection technique in cognitive radio. We obtain the cyclostationary features of these primary signals using spectral correlation function. Based on these features, we develop two algorithms for spectrum sensing and their performances are evaluated in comparison with energy detector which is considered as the standard simple detector. Given that the cyclostationary features are unique for a particular signal; these features can be used for signals classification. In our case, we use those features to decide if the licensed channel is used by TV service or wireless microphone service. This provides additional information for spectrum management and power control. Implementation issue is very important in cognitive radio generally and spectrum sensing specially, hence we discuss the implementation of cyclostationary features detector and compare its complexity with that of energy detector

Unequal error protection for power line communications over impulsive noise channels

Power line communication (PLC) has recently attracted a lot of interest with many application areas including smart grids\u27 data communication, where data (from sensors or other measurement units) with different QoS may be transmitted. Power line communications suffer from the excessive power lines\u27 impulsive noise (which can be caused by shedding loads on and off). In this thesis, we present a study of power line communications with unequal error protection for two and four data priority levels hierarchical QAM modulation and space-time block coding. We consider the two commonly used power lines\u27 impulsive noise models with Bernoulli and Poisson arrivals. In our proposed approaches, we achieve UEP on both of bit and symbol levels. Approximate closed form expressions for the error rates are derived for each priority level for both single carrier and OFDM in SISO and MIMO systems. In addition, these simpli fied expressions are used to implement a bit loading algorithm to provide UEP for frequency-selective PLC channels. For the case of MIMO PLC channels, we describe three different MIMO schemes to allow more control over the UEP levels. The three schemes are namely: maximum ratio combiner (MRC) receive diversity, Alamouti space-time block code, and a new structure for a space-time code that allows for unequal error protection at the symbol level. Finally, we apply an Eigen beamforming technique, assuming channel knowledge at transmitter, which improves the BER as compared to the other MIMO PLC schemes

A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed

Dynamic spectrum access is a must-have ingredient for future sensors that are ideally cognitive. The goal of this paper is a tutorial treatment of wideband cognitive radio and radar—a convergence of (1) algorithms survey, (2) hardware platforms survey, (3) challenges for multi-function (radar/communications) multi-GHz front end, (4) compressed sensing for multi-GHz waveforms—revolutionary A/D, (5) machine learning for cognitive radio/radar, (6) quickest detection, and (7) overlay/underlay cognitive radio waveforms. One focus of this paper is to address the multi-GHz front end, which is the challenge for the next-generation cognitive sensors. The unifying theme of this paper is to spell out the convergence for cognitive radio, radar, and anti-jamming. Moore’s law drives the system functions into digital parts. From a system viewpoint, this paper gives the first comprehensive treatment for the functions and the challenges of this multi-function (wideband) system. This paper brings together the inter-disciplinary knowledge