Electrical and Electronic Engineering - Research Publications
Permanent URI for this collection
Search Results
1 - 10 of 30
-
ItemNo Preview AvailableLeast-square Fitting on the Circle using Optimal Control(Elsevier BV, 2023-07-01)
-
ItemNo Preview AvailableEstimating and detecting random processes on the unit circle(Elsevier BV, 2023-01-01)
-
ItemNo Preview AvailableFrequency Permutations for Joint Radar and Communications(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022-11)
-
ItemNo Preview AvailableDetection and Estimation of Randomly Phase Modulated Signals(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
-
ItemNo Preview AvailableCombined Radar and Communications With Phase-Modulated Frequency Permutations(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)
-
ItemNo Preview AvailableSystematic upper limits on the size of missing pulsar glitches in the first UTMOST open data release(OXFORD UNIV PRESS, 2022-03-22)ABSTRACT A systematic, semi-automated search for pulsar glitches in the first UTMOST public data release is presented. The search is carried out using a hidden Markov model which incorporates both glitches and timing noise into the model of the assumed phase evolution of the pulsar. Glitches are detected through Bayesian model selection between models with and without glitches present with minimal human intervention. Nine glitches are detected among seven objects, all of which have been previously reported. No new glitches were detected. Injection studies are used to place 90 per cent frequentist upper limits on the size of undetected glitches in each of the 282 objects searched. The mean upper limit obtained is $\Delta f^{90{{\%}}}/f = 1.9 \times 10^{-8}$, with a range of $4.1 \times 10^{-11} \le \Delta f^{90{{\%}}}/f \le 2.7 \times 10^{-7}$, assuming step events with no post-glitch recoveries. It is demonstrated that including glitch recovery has a mild effect, in most cases increasing the upper limit by a factor of ≲5 conservatively assuming complete recovery on a time-scale of $100\ \mathrm{d}$.
-
ItemBayesian Detection of a Sinusoidal Signal With Randomly Varying Frequency(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022)
-
ItemTesting for a Random Walk Structure in the Frequency Evolution of a Tone in Noise(MDPI, 2022-08)Inference and hypothesis testing are typically constructed on the basis that a specific model holds for the data. To determine the veracity of conclusions drawn from such data analyses, one must be able to identify the presence of the assumed structure within the data. In this paper, a model verification test is developed for the presence of a random walk-like structure in the variations in the frequency of complex-valued sinusoidal signals measured in additive Gaussian noise. This test evaluates the joint inference of the random walk hypothesis tests found in economics literature that seek random walk behaviours in time series data, with an additional test to account for how the random walk behaves in frequency space.
-
ItemDynamic scheduling algorithm for LTE uplink with smart-metering traffic(WILEY, 2017-10)Abstract Long‐term evolution (LTE) is a promising last mile access candidate technology for the smart‐metering communication architecture. However, when the mobile LTE network is used to support smart meters (SMs), the quality‐of‐service (QoS) requirements of the smart‐metering traffic as well as all the other typical mobile network traffic need to be ensured. This becomes problematic when the network users generate diverse traffic types that have different QoS requirements. Therefore, in this paper, we propose a dynamic bandwidth scheduling algorithm to ensure the required QoS of various traffic types arising from both SMs and mobile users. Our proposed dynamic bandwidth allocation algorithm integrates two schedulers that are designed for periodic and emergency SM traffic situations that have different SM traffic intensities and QoS requirements. Designing of two schedulers provides the advantages of leveraging the particular traffic characteristics of these two diverse operational situations and achieving the maximum use of resources to ensure QoS requirements. In addition, to alleviate potential problems created by simultaneous emergency SM traffic, we also propose a method that deploys a random delay for SM packet transmissions. We analyse the delay and packet drop ratio of diverse traffic types when both the LTE base station scheduler and the SMs deploy our proposed methods under either periodic or emergency SM traffic conditions in the smart grid. Our results show that our proposed mechanisms are capable of satisfying the QoS requirements of both mobile users and SMs under diverse traffic conditions.
-
ItemNo Preview Available