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

Communications protocols for wireless sensor networks in perturbed environment

This thesis is mainly in the Smart Grid (SG) domain. SGs improve the safety of electrical networks and allow a more adapted use of electricity storage, available in a limited way. SGs also increase overall energy efficiency by reducing peak consumption. The use of this technology is the most appropriate solution because it allows more efficient energy management. In this context, manufacturers such as Hydro-Quebec deploy sensor networks in the nerve centers to control major equipment. To reduce deployment costs and cabling complexity, the option of a wireless sensor network seems the most obvious solution. However, deploying a sensor network requires in-depth knowledge of the environment. High voltages substations are strategic points in the power grid and generate impulse noise that can degrade the performance of wireless communications. The works in this thesis are focused on the development of high performance communication protocols for the profoundly disturbed environments. For this purpose, we have proposed an approach based on the concatenation of rank metric and convolutional coding with orthogonal frequency division multiplexing. This technique is very efficient in reducing the bursty nature of impulsive noise while having a quite low level of complexity. Another solution based on a multi-antenna system is also designed. We have proposed a cooperative closed-loop coded MIMO system based on rank metric code and max−dmin precoder. The second technique is also an optimal solution for both improving the reliability of the system and energy saving in wireless sensor networks

Modeling and Optimization of Next-Generation Wireless Access Networks

The ultimate goal of the next generation access networks is to provide all network users, whether they are fixed or mobile, indoor or outdoor, with high data rate connectivity, while ensuring a high quality of service. In order to realize this ambitious goal, delay, jitter, error rate and packet loss should be minimized: a goal that can only be achieved through integrating different technologies, including passive optical networks, 4th generation wireless networks, and femtocells, among others. This thesis focuses on medium access control and physical layers of future networks. In this regard, the first part of this thesis discusses techniques to improve the end-to-end quality of service in hybrid optical-wireless networks. In these hybrid networks, users are connected to a wireless base station that relays their data to the core network through an optical connection. Hence, by integrating wireless and optical parts of these networks, a smart scheduler can predict the incoming traffic to the optical network. The prediction data generated herein is then used to propose a traffic-aware dynamic bandwidth assignment algorithm for reducing the end-to-end delay. The second part of this thesis addresses the challenging problem of interference management in a two-tier macrocell/femtocell network. A high quality, high speed connection for indoor users is ensured only if the network has a high signal to noise ratio. A requirement that can be fulfilled with using femtocells in cellular networks. However, since femtocells generate harmful interference to macrocell users in proximity of them, careful analysis and realistic models should be developed to manage the introduced interference. Thus, a realistic model for femtocell interference outside suburban houses is proposed and several performance measures, e.g., signal to interference and noise ratio and outage probability are derived mathematically for further analysis. The quality of service of cellular networks can be degraded by several factors. For example, in industrial environments, simultaneous fading and strong impulsive noise significantly deteriorate the error rate performance. In the third part of this thesis, a technique to improve the bit error rate of orthogonal frequency division multiplexing systems in industrial environments is presented. This system is the most widely used technology in next-generation networks, and is very susceptible to impulsive noise, especially in fading channels. Mathematical analysis proves that the proposed method can effectively mitigate the degradation caused by impulsive noise and significantly improve signal to interference and noise ratio and bit error rate, even in frequency-selective fading channels

Coded-OFDM for PLC systems in non-Gaussian noise channels

PhD ThesisNowadays, power line communication (PLC) is a technology that uses the power line grid for communication purposes along with transmitting electrical energy, for providing broadband services to homes and offices such as high-speed data, audio, video and multimedia applications. The advantages of this technology are to eliminate the need for new wiring and AC outlet plugs by using an existing infrastructure, ease of installation and reduction of the network deployment cost. However, the power line grid is originally designed for the transmission of the electric power at low frequencies; i.e. 50/60 Hz. Therefore, the PLC channel appears as a harsh medium for low-power high-frequency communication signals. The development of PLC systems for providing high-speed communication needs precise knowledge of the channel characteristics such as the attenuation, non-Gaussian noise and selective fading. Non-Gaussian noise in PLC channels can classify into Nakagami-m background interference (BI) noise and asynchronous impulsive noise (IN) modelled by a Bernoulli-Gaussian mixture (BGM) model or Middleton class A (MCA) model. Besides the effects of the multipath PLC channel, asynchronous impulsive noise is the main reason causing performance degradation in PLC channels. Binary/non-binary low-density parity check B/NB-(LDPC) codes and turbo codes (TC) with soft iterative decoders have been proposed for Orthogonal Frequency Division Multiplexing (OFDM) system to improve the bit error rate (BER) performance degradation by exploiting frequency diversity. The performances are investigated utilizing high-order quadrature amplitude modulation (QAM) in the presence of non-Gaussian noise over multipath broadband power-line communication (BBPLC) channels. OFDM usually spreads the effect of IN over multiple sub-carriers after discrete Fourier transform (DFT) operation at the receiver, hence, it requires only a simple single-tap zero forcing (ZF) equalizer at the receiver. The thesis focuses on improving the performance of iterative decoders by deriving the effective, complex-valued, ratio distributions of the noise samples at the zeroforcing (ZF) equalizer output considering the frequency-selective multipath PLCs, background interference noise and impulsive noise, and utilizing the outcome for computing the apriori log likelihood ratios (LLRs) required for soft decoding algorithms. On the other hand, Physical-Layer Network Coding (PLNC) is introduced to help the PLC system to extend the range of operation for exchanging information between two users (devices) using an intermediate relay (hub) node in two-time slots in the presence of non-Gaussian noise over multipath PLC channels. A novel detection scheme is proposed to transform the transmit signal constellation based on the frequency-domain channel coefficients to optimize detection at the relay node with newly derived noise PDF at the relay and end nodes. Additionally, conditions for optimum detection utilizing a high-order constellation are derived. The closedform expressions of the BER and average BER upper-bound (AUB) are derived for a point-to-point system, and for a PLNC system at the end node to relay, relay to end node and at the end-to-end nodes. Moreover, the convergence behaviour of iterative decoders is evaluated using EXtrinsic Information Transfer (EXIT) chart analysis and upper bound analyses. Furthermore, an optimization of the threshold determination for clipping and blanking impulsive noise mitigation methods are derived. The proposed systems are compared in performance using simulation in MATLAB and analytical methods.Ministry of Higher Education in Ira

Enabling Millimeter Wave Communications for Use Cases of 5G and Beyond Networks

The wide bandwidth requirements of the fifth generation (5G) and beyond networks are driving the move to millimeter wave (mmWave) bands where it can provide a huge increase in the available bandwidth. Increasing the bandwidth is an effective way to improve the channel capacity with limited power. Moreover, the short wavelengths of such bands enable massive number of antennas to be integrated together in small areas. With such massive number of antennas, narrow beamwidth beams can be obtained which in turn can improve the security. Furthermore, the massive number of antennas can help in mitigating the severe path-loss at mmWave frequencies, and realize high data rate communication at reasonable distances. Nevertheless, one of the main bottlenecks of mmWave communications is the signal blockage. This is due to weak diffraction ability and severe penetration losses by many common building materials such as brick, and mortar as well as the losses due to human bodies. Thus, user mobility and/or small movements of obstacles and reflectors cause rapid channel gain variations which leads to unreliable communication links. The harsh propagation environment at such high frequencies makes it hard to provide a reliable service, hence, maintaining connectivity is one key design challenge in mmWave networks. Relays represent a promising approach to improve mmWave connectivity where they can redirect the signal to avoid the obstacles existing in the propagation environment. However, routing in mmWave networks is known to be a very challenging problem due to the inherent propagation characteristics of mmWave frequencies. Furthermore, inflexible routing technique may worsen network performance and increase scheduling overhead. As such, designing an appropriate transmission routing technique for each service is a crucial issue in mmWave networks. Indeed, multiple factors must be taken into account in the routing process, such as guaranteeing the robustness of network connectivity and providing high data rates. In this thesis, we propose an analytical framework to investigate the network reliability of mmWave relaying systems for multi-hop transmissions. We also propose a flexible routing technique for mmWave networks, namely the $n^{\rm th}$ best routing technique. The performance of the proposed routing technique is investigated using tools from stochastic geometry. The obtained results provide useful insights on adjusting the signal noise ratio (SNR) threshold for decode and forward (DF) relay according to the order of the best relay, blockage and relay densities in order to improve spectral efficiency. We also propose a novel mathematical framework to investigate the performance of two appropriate routing techniques for mmWave networks, namely minimum hop count (MHC) and nearest LoS relay to the destination with MHC (NLR-MHC) to support wide range of use cases for 5G and beyond networks. Analytical models are provided to evaluate the performance of the proposed techniques using tools from stochastic geometry. In doing so, we model the distribution of hop count using phase-type distribution, and then we use this distribution to derive analytical results for the coverage probability and spectral efficiency. Capitalizing on the derived results, we introduce a comprehensive study of the effects of different system parameters on the performance of multi-hop mmWave systems. These findings provide important insights for designing multi-hop mmWave networks with better performance. Furthermore, we adapt the proposed relay selection technique for IoT devices in mmWave relaying systems to prolong the IoT device’s battery life. The obtained results reveal the trade-off between the network connectivity and the energy consumption of IoT devices. Lastly, we have exploited the enormous bandwidth available in the mmWave band to support reliable fronthaul links for cell-free (CF) massive multiple-input multiple-output (MIMO). We provide a comprehensive investigation of different system parameters on the uplink (UL) performance of mmWave fronthaul-based CF mMIMO systems. Results reveal that increasing the access point (AP) density beyond a certain limit would not achieve further improvement in the UL data rates. Also, the higher number of antennas per AP may even cause UL data rates degradation

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

An Investigation into Trust and Reputation Frameworks for Autonomous Underwater Vehicles

As Autonomous Underwater Vehicles (AUVs) become more technically capable and economically feasible, they are being increasingly used in a great many areas of defence, commercial and environmental applications. These applications are tending towards using independent, autonomous, ad-hoc, collaborative behaviour of teams or fleets of these AUV platforms. This convergence of research experiences in the Underwater Acoustic Network (UAN) and Mobile Ad-hoc Network (MANET) fields, along with the increasing Level of Automation (LOA) of such platforms, creates unique challenges to secure the operation and communication of these networks. The question of security and reliability of operation in networked systems has usually been resolved by having a centralised coordinating agent to manage shared secrets and monitor for misbehaviour. However, in the sparse, noisy and constrained communications environment of UANs, the communications overheads and single-point-of-failure risk of this model is challenged (particularly when faced with capable attackers). As such, more lightweight, distributed, experience based systems of “Trust” have been proposed to dynamically model and evaluate the “trustworthiness” of nodes within a MANET across the network to prevent or isolate the impact of malicious, selfish, or faulty misbehaviour. Previously, these models have monitored actions purely within the communications domain. Moreover, the vast majority rely on only one type of observation (metric) to evaluate trust; successful packet forwarding. In these cases, motivated actors may use this limited scope of observation to either perform unfairly without repercussions in other domains/metrics, or to make another, fair, node appear to be operating unfairly. This thesis is primarily concerned with the use of terrestrial-MANET trust frameworks to the UAN space. Considering the massive theoretical and practical difference in the communications environment, these frameworks must be reassessed for suitability to the marine realm. We find that current single-metric Trust Management Frameworks (TMFs) do not perform well in a best-case scaling of the marine network, due to sparse and noisy observation metrics, and while basic multi-metric communications-only frameworks perform better than their single-metric forms, this performance is still not at a reliable level. We propose, demonstrate (through simulation) and integrate the use of physical observational metrics for trust assessment, in tandem with metrics from the communications realm, improving the safety, security, reliability and integrity of autonomous UANs. Three main novelties are demonstrated in this work: Trust evaluation using metrics from the physical domain (movement/distribution/etc.), demonstration of the failings of Communications-based Trust evaluation in sparse, noisy, delayful and non-linear UAN environments, and the deployment of trust assessment across multiple domains, e.g. the physical and communications domains. The latter contribution includes the generation and optimisation of cross-domain metric composition or“synthetic domains” as a performance improvement method