Empirical Bayes methodology for estimating equipment failure rates with application to power generation plants

Many reliability databases pool event data for equipment across different plants. Pooling may occur both within and between organizations with the intention of sharing data across common items within similar operating environments to provide better estimates of reliability and availability. Frequentist estimation methods can be poor when few, or no, events occur even when equipment operate for long periods. An alternative approach based upon empirical Bayes estimation is proposed. The new method is applied to failure data analysis in power generation plants and found to provide credible insights. A statistical comparison between the proposed and frequentist methods shows that empirical Bayes is capable of generating more accurate estimates

A Survey on Fundamental Limits of Integrated Sensing and Communication

The integrated sensing and communication (ISAC), in which the sensing and communication share the same frequency band and hardware, has emerged as a key technology in future wireless systems due to two main reasons. First, many important application scenarios in fifth generation (5G) and beyond, such as autonomous vehicles, Wi-Fi sensing and extended reality, requires both high-performance sensing and wireless communications. Second, with millimeter wave and massive multiple-input multiple-output (MIMO) technologies widely employed in 5G and beyond, the future communication signals tend to have high-resolution in both time and angular domain, opening up the possibility for ISAC. As such, ISAC has attracted tremendous research interest and attentions in both academia and industry. Early works on ISAC have been focused on the design, analysis and optimization of practical ISAC technologies for various ISAC systems. While this line of works are necessary, it is equally important to study the fundamental limits of ISAC in order to understand the gap between the current state-of-the-art technologies and the performance limits, and provide useful insights and guidance for the development of better ISAC technologies that can approach the performance limits. In this paper, we aim to provide a comprehensive survey for the current research progress on the fundamental limits of ISAC. Particularly, we first propose a systematic classification method for both traditional radio sensing (such as radar sensing and wireless localization) and ISAC so that they can be naturally incorporated into a unified framework. Then we summarize the major performance metrics and bounds used in sensing, communications and ISAC, respectively. After that, we present the current research progresses on fundamental limits of each class of the traditional sensing and ISAC systems. Finally, the open problems and future research directions are discussed

Robust wireless sensor network for smart grid communication : modeling and performance evaluation

Our planet is gradually heading towards an energy famine due to growing population and industrialization. Hence, increasing electricity consumption and prices, diminishing fossil fuels and lack significantly in environment-friendliness due to their emission of greenhouse gasses, and inefficient usage of existing energy supplies have caused serious network congestion problems in many countries in recent years. In addition to this overstressed situation, nowadays, the electric power system is facing many challenges, such as high maintenance cost, aging equipment, lack of effective fault diagnostics, power supply reliability, etc., which further increase the possibility of system breakdown. Furthermore, the adaptation of the new renewable energy sources with the existing power plants to provide an alternative way for electricity production transformed it in a very large and complex scale, which increases new issues. To address these challenges, a new concept of next generation electric power system, called the "smart grid", has emerged in which Information and Communication Technologies (ICTs) are playing the key role. For a reliable smart grid, monitoring and control of power system parameters in the transmission and distribution segments are crucial. This necessitates the deployment of a robust communication network within the power grid. Traditionally, power grid communications are realized through wired communications, including power line communication (PLC). However, the cost of its installation might be expensive especially for remote control and monitoring applications. More recently, plenty of research interests have been drawn to the wireless communications for smart grid applications. In this regard, the most promising methods of smart grid monitoring explored in the literature is based on wireless sensor network (WSN). Indeed, the collaborative nature of WSN brings significant advantages over the traditional wireless networks, including low-cost, wider coverage, self-organization, and rapid deployment. Unfortunately, harsh and hostile electric power system environments pose great challenges in the reliability of sensor node communications because of strong RF interference and noise called impulsive noise. On account of the fundamental of WSN-based smart grid communications and the possible impacts of impulsive noise on the reliability of sensor node communications, this dissertation is supposed to further fill the lacking of the existing research outcomes. To be specific, the contributions of this dissertation can be summarized as three fold: (i) investigation and performance analysis of impulsive noise mitigation techniques for point-to-point single-carrier communication systems impaired by bursty impulsive noise; (ii) design and performance analysis of collaborative WSN for smart grid communication by considering the RF noise model in the designing process, a particular intension is given to how the time-correlation among the noise samples can be taken into account; (iii) optimal minimum mean square error (MMSE)estimation of physical phenomenon like temperature, current, voltage, etc., typically modeled by a Gaussian source in the presence of impulsive noise. In the first part, we compare and analyze the widely used non-linear methods such as clipping, blanking, and combined clipping-blanking to mitigate the noxious effects of bursty impulsive noise for point-to-point communication systems with low-density parity-check (LDPC) coded single-carrier transmission. While, the performance of these mitigation techniques are widely investigated for multi-carrier communication systems using orthogonal frequency division multiplexing (OFDM) transmission under the effect of memoryless impulsive noise, we note that OFDM is outperformed by its single-carrier counterpart when the impulses are very strong and/or they occur frequently, which likely exists in contemporary communication systems including smart grid communications. Likewise, the assumption of memoryless noise model is not valid for many communication scenarios. Moreover, we propose log-likelihood ratio (LLR)-based impulsive noise mitigation for the considered scenario. We show that the memory property of the noise can be exploited in the LLR calculation through maximum a posteriori (MAP) detection. In this context, provided simulation results highlight the superiority of the LLR-based mitigation scheme over the simple clipping/blanking schemes. The second contribution can be divided into two aspects: (i) we consider the performance analysis of a single-relay decode-and-forward (DF) cooperative relaying scheme over channels impaired by bursty impulsive noise. For this channel, the bit error rate (BER) performances of direct transmission and a DF relaying scheme using M-PSK modulation in the presence of Rayleigh fading with a MAP receiver are derived; (ii) as a continuation of single-relay collaborative WSN scheme, we propose a novel relay selection protocol for a multi-relay DF collaborative WSN taking into account the bursty impulsive noise. The proposed protocol chooses the N’th best relay considering both the channel gains and the states of the impulsive noise of the source-relay and relay-destination links. To analyze the performance of the proposed protocol, we first derive closed-form expressions for the probability density function (PDF) of the received SNR. Then, these PDFs are used to derive closed-form expressions for the BER and the outage probability. Finally, we also derive the asymptotic BER and outage expressions to quantify the diversity benefits. From the obtained results, it is seen that the proposed receivers based on the MAP detection criterion is the most suitable one for bursty impulsive noise environments as it has been designed according to the statistical behavior of the noise. Different from the aforementioned contributions, talked about the reliable detection of finite alphabets in the presence of bursty impulsive noise, in the thrid part, we investigate the optimal MMSE estimation for a scalar Gaussian source impaired by impulsive noise. In Chapter 5, the MMSE optimal Bayesian estimation for a scalar Gaussian source, in the presence of bursty impulsive noise is considered. On the other hand, in Chapter 6, we investigate the distributed estimation of a scalar Gaussian source in WSNs in the presence of Middleton class-A noise. From the obtained results we conclude that the proposed optimal MMSE estimator outperforms the linear MMSE estimator developed for Gaussian channel

Error rate performance metrics for digital communications systems.

In this thesis, novel error rate performance metrics and transmission solutions are investigated for delay limited communication systems and for co-channel interference scenarios. The following four research problems in particular were considered. The first research problem is devoted to analysis of the higher order ergodic moments of error rates for digital communication systems with time- unlimited ergodic transmissions and the statistics of the conditional error rates of digital modulations over fading channels are considered. The probability density function and the higher order moments of the conditional error rates are obtained. Non-monotonic behavior of the moments of the conditional bit error rates versus some channel model parameters is observed for a Ricean distributed channel fading amplitude at the detector input. Properties and possible applications of the second central moments are proposed. The second research problem is the non-ergodic error rate analysis and signaling design for communication systems processing a single finite length received sequence. A framework to analyze the error rate properties of non-ergodic transmissions is established. The Bayesian credible intervals are used to estimate the instantaneous bit error rate. A novel degree of ergodicity measure is introduced using the credible interval estimates to quantify the level of ergodicity of the received sequence with respect to the instantaneous bit error rate and to describe the transition of the data detector from the non-ergodic to ergodic zone of operation. The developed non-ergodic analysis is used to define adaptive forward error correction control and adaptive power control policies that can guarantee, with a given probability, the worst case instantaneous bit error rate performance of the detector in its transition fi'om the non-ergodic to ergodic zone of operation. In the third research problem, novel retransmission schemes are developed for delay-limited retransmissions. The proposed scheme relies on a reliable reverse link for the error-free feedback message delivery. Unlike the conventional automatic repeat request schemes, the proposed scheme does not require the use of cyclic redundancy check bits for error detection. In the proposed scheme, random permutations are exploited to locate the bits for retransmission in the predefined window within the packet. The retransmitted bits are combined using the maximal-ratio combining. The complexity-performance trade-offs of the proposed scheme is investigated by mathematical analysis as well as computer simulations. The bit error rate of the proposed scheme is independent of the packet length while the throughput is dependent on the packet length. Three practical techniques suitable for implementation are proposed. The performance of the proposed retransmission scheme was compared to the block repetition code corresponding to a conventional ARQ retransmission strategy. It was shown that, for the same number of retransmissions, and the same packet length, the proposed scheme always outperforms such repetition coding, and, in some scenarios, the performance improvement is found to be significant. Most of our analysis has been done for the case of AWGN channel, however, the case of a slow Rayleigh block fading channel was also investigated. The proposed scheme appears to provide the throughput and the BER reduction gains only for the medium to large SNR values. Finally, the last research problem investigates the link error rate performance with a single co-channel interference. A novel metric to assess whether the standard Gaussian approximation of a single interferer underestimates or overestimates the link bit error rate is derived. This metric is a function of the interference channel fading statistics. However, it is otherwise independent of the statistics of the desired signal. The key step in derivation of the proposed metric is to construct the standard Gaussian approximation of the interference by a non-linear transformation. A closed form expression of the metric is obtained for a Nakagami distributed interference fading amplitude. Numerical results for the case of Nakagami and lognormal distributed interference fading amplitude confirm the validity of the proposed metric. The higher moments, interval estimators and non-linear transformations were investigated to evaluate the error rate performance for different wireless communication scenarios. The synchronization channel is also used jointly with the communication link to form a transmission diversity and subsequently, to improve the error rate performance

Distributed estimation in wireless sensor networks under a semi-orthogonal multiple access technique

This thesis is concerned with distributed estimation in a wireless sensor network (WSN) with analog transmission. For a scenario in which a large number of sensors are deployed under a limited bandwidth constraint, a semi-orthogonal multiple-access channelization (MAC) approach is proposed to provide transmission of observations from K sensors to a fusion center (FC) via N orthogonal channels, where K≥N. The proposed semi-orthogonal MAC can be implemented with either fixed sensor grouping or adaptive sensor grouping. The mean squared error (MSE) is adopted as the performance criterion and it is first studied under equal power allocation. The MSE can be expressed in terms of two indicators: the channel noise suppression capability and the observation noise suppression capability. The fixed version of the semi-orthogonal MAC is shown to have the same channel noise suppression capability and two times the observation noise suppression capability when compared to the orthogonal MAC under the same bandwidth resource. For the adaptive version, the performance improvement of the semi-orthogonal MAC over the orthogonal MAC is even more significant. In fact, the semi-orthogonal MAC with adaptive sensor grouping is shown to perform very close to that of the hybrid MAC, while requiring a much smaller amount of feedback. Another contribution of this thesis is an analysis of the behavior of the average MSE in terms of the number of sensors, namely the scaling law, under equal power allocation. It is shown that the proposed semi-orthogonal MAC with adaptive sensor grouping can achieve the optimal scaling law of the analog WSN studied in this thesis. Finally, improved power allocations for the proposed semi-orthogonal MAC are investigated. First, the improved power allocations in each sensor group for different scenarios are provided. Then an optimal solution of power allocation among sensor groups is obtained by the convex optimization theory, and shown to outperform equal power allocation. The issue of balancing between the performance improvement and extra feedback required by the improved power allocation is also thoroughly discussed