Error models for digital channels and applications to wireless communication systems

Digital wireless channels are extremely prone to errors that appear in bursts or clusters. Error models characterise the statistical behaviour of bursty profiles derived from digital wireless channels. Generative error models also utilise those bursty profiles in order to create alternatives, which are more efficient for experimental purposes. Error models have a tremendous value for wireless systems. They are useful for the design and performance evaluation of error control schemes, in addition to higher layer protocols in which the statistical properties of the bursty profiles are greatly functional. Furthermore, underlying wireless digital channels can be substituted by generated error profiles. Consequently, computational load and simulation time can be significantly reduced when executing experiments and performing evaluation simulations for higher layer communications protocols and error control strategies. The burst error statistics are the characterisation metrics of error models. These statistics include: error-free run distribution; error-free burst distribution; error burst distribution; error cluster distribution; gap distribution; block error probability distribution; block burst probability distribution; bit error correlation function; normalised covariance function; gap correlation function; and multigap distribution. These burst error statistics scrutinise the error models and differentiate between them, with regards to accuracy. Moreover, some of them are advantageous for the design of digital components in wireless communication systems. This PhD thesis aims to develop accurate and efficient error models and to find applications for them. A thorough investigation has been conducted on the burst error statistics. A breakdown of this thesis is presented as follows. Firstly, an understanding of the different types of generative error models, namely, Markovian based generative models, context-free grammars based generative models, chaotic models, and deterministic process based generative models, has been presented. The most widely used models amongst the generative models have been compared with each other consulting the majority of burst error statistics. In order to study generative error models, error burst profiles were obtained mainly from the Enhanced General Packet Radio Service (EGPRS) system and also the Long Term Evolution (LTE) system. Secondly, more accurate and efficient generative error models have been proposed. Double embedded processes based hidden Markov model and three-layered processes based hidden Markov model have been developed. The two types of error profiles, particularly the bit-level and packet-level error profiles were considered. Thirdly, the deterministic process based generative models’ parameters have been tuned or modified in order to generate packet error sequences rather than only bit error sequences. Moreover, a modification procedure has been introduced to the same models to enhance their generation process and to make them more desirable. Fourthly, adaptive generative error models have been built in order to accommodate widely used generative error models to different digital wireless channels with different channel conditions. Only a few reference error profiles have been required in order to produce additional error profiles in various conditions that are beneficial for the design and performance evaluation of error control schemes and higher layer protocols. Finally, the impact of the Hybrid Automatic Repeat reQuest (HARQ) on the burst error statistics of physical layer error profiles has been studied. Moreover, a model that can generate predicted error sequences with burst error statistics similar to those of error profiles when HARQ is included has been proposed. This model is constructive in predicting the behaviour of the HARQ in terms of a set of higher order statistics rather than only predicting a first order statistic. Moreover, the whole physical layer is replaced by adaptively generated error profiles in order to check the performance of the HARQ protocol. The developed generative error models as well as the developed adaptive generative error models are expected to benefit future research towards the testing of many digital components in the physical layer as well as the wireless protocols of the link and transport layers for many existing and emerging systems in the field of wireless communications

5G無線通信における誤り訂正符号化方式の評価に関する研究

早大学位記番号:新8267早稲田大

An Integrated Approach for Jammer Detection using Software Defined Radio

AbstractDue to shared nature of wireless communication any malicious user can easily monitored communication between two devices and emits false message to block communication. Nowadays increased use of software defined radio (SDR) technology makes any types of jammer device using same hardware with little modification in software. A jammer transmits radio signal to block legitimate communication either overlapping signal with more power or reducing signal to noise ratio. In this paper we have survey different jammer detection methods for efficient detection of jammers presence in system. Existing jammer detection methods like packet delivery ratio (PDR), packet send ratio (PSR), bad packet ratio (BPR) and signal to noise ratio (SNR) can effectively detects jammer, here we have proposed novel method for jammer detection using communication parameter used in SDR like synchronization indicator, iteration and adaptive signal to jammer plus noise ratio (ASNJR). This system uses that parameter which is readily available in system so computation has been reduced and ASNJR also has been adaptively updated with and without presence of jammer. Experimental result show that this system based on SDR effectively detects presence of jammer

Contributions to modelling of internet traffic by fractal renewal processes.

The principle of parsimonious modelling of Internet traffic states that a minimal number of descriptors should be used for its characterization. Until early 1990s, the conventional Markovian models for voice traffic had been considered suitable and parsimonious for data traffic as well. Later with the discovery of strong correlations and increased burstiness in Internet traffic, various self-similar count models have been proposed. But, in fact, such models are strictly mono-fractal and applicable at coarse time scales, whereas Internet traffic modelling is about modelling traffic at fine and coarse time scales; modelling traffic which can be mono and multi-fractal; modelling traffic at interarrival time and count levels; modelling traffic at access and core tiers; and modelling all the three structural components of Internet traffic, that is, packets, flows and sessions. The philosophy of this thesis can be described as: “the renewal of renewal theory in Internet traffic modelling”. Renewal theory has a great potential in modelling statistical characteristics of Internet traffic belonging to individual users, access and core networks. In this thesis, we develop an Internet traffic modelling framework based on fractal renewal processes, that is, renewal processes with underlying distribution of interarrival times being heavy-tailed. The proposed renewal framework covers packets, flows and sessions as structural components of Internet traffic and is applicable for modelling the traffic at fine and coarse time scales. The properties of superposition of renewal processes can be used to model traffic in higher tiers of the Internet hierarchy. As the framework is based on renewal processes, therefore, Internet traffic can be modelled at both interarrival times and count levels

Reliable Web Service Consumption Through Mobile Cloud Computing

The mobile intermittent wireless connectivity limits the evolution of the mobile landscape. Achieving web service reliability results in low communication overhead and correct retrieval of the appropriate state response. In this chapter, we discuss and analyze two approaches based on middleware approach, Reliable Service Architecture using Middleware (RSAM), and Reliable Approach using Middleware and WebSocket (RAMWS). These approaches achieve the reliability of web services consumed by mobile devices and propose an enhanced architecture that achieves the reliability under various conditions with minimum communication data overhead. In these experiments, we covered several cases to prove the achievement of reliability. Results also show that the request size was found to be constant, the response size is identical to the traditional architecture, and the increase in the consumption time was less than 5% with the different response sizes

Solutions for large scale, efficient, and secure Internet of Things

The design of a general architecture for the Internet of Things (IoT) is a complex task, due to the heterogeneity of devices, communication technologies, and applications that are part of such systems. Therefore, there are significant opportunities to improve the state of the art, whether to better the performance of the system, or to solve actual issues in current systems. This thesis focuses, in particular, on three aspects of the IoT. First, issues of cyber-physical systems are analysed. In these systems, IoT technologies are widely used to monitor, control, and act on physical entities. One of the most important issue in these scenarios are related to the communication layer, which must be characterized by high reliability, low latency, and high energy efficiency. Some solutions for the channel access scheme of such systems are proposed, each tailored to different specific scenarios. These solutions, which exploit the capabilities of state of the art radio transceivers, prove effective in improving the performance of the considered systems. Positioning services for cyber-physical systems are also investigated, in order to improve the accuracy of such services. Next, the focus moves to network and service optimization for traffic intensive applications, such as video streaming. This type of traffic is common amongst non-constrained devices, like smartphones and augmented/virtual reality headsets, which form an integral part of the IoT ecosystem. The proposed solutions are able to increase the video Quality of Experience while wasting less bandwidth than state of the art strategies. Finally, the security of IoT systems is investigated. While often overlooked, this aspect is fundamental to enable the ubiquitous deployment of IoT. Therefore, security issues of commonly used IoT protocols are presented, together with a proposal for an authentication mechanism based on physical channel features. This authentication strategy proved to be effective as a standalone mechanism or as an additional security layer to improve the security level of legacy systems

DESIGN OF RELIABLE AND SUSTAINABLE WIRELESS SENSOR NETWORKS: CHALLENGES, PROTOCOLS AND CASE STUDIES

Integrated with the function of sensing, processing, and wireless communication, wireless sensors are attracting strong interest for a variety of monitoring and control applications. Wireless sensor networks (WSNs) have been deployed for industrial and remote monitoring purposes. As energy shortage is a worldwide problem, more attention has been placed on incorporating energy harvesting devices in WSNs. The main objective of this research is to systematically study the design principles and technical approaches to address three key challenges in designing reliable and sustainable WSNs; namely, communication reliability, operation with extremely low and dynamic power sources, and multi-tier network architecture. Mathematical throughput models, sustainable WSN communication strategies, and multi-tier network architecture are studied in this research to address these challenges, leading to protocols for reliable communication, energy-efficient operation, and network planning for specific application requirements. To account for realistic operating conditions, the study has implemented three distinct WSN testbeds: a WSN attached to the high-speed rotating spindle of a turning lathe, a WSN powered by a microbial fuel cell based energy harvesting system, and a WSN with a multi-tier network architecture. With each testbed, models and protocols are extracted, verified and analyzed. Extensive research has studied low power WSNs and energy harvesting capabilities. Despite these efforts, some important questions have not been well understood. This dissertation addresses the following three dimensions of the challenge. First, for reliable communication protocol design, mathematical throughput or energy efficiency estimation models are essential, yet have not been investigated accounting for specific application environment characteristics and requirements. Second, for WSNs with energy harvesting power sources, most current networking protocols do not work efficiently with the systems considered in this dissertation, such as those powered by extremely low and dynamic energy sources. Third, for multi-tier wireless network system design, routing protocols that are adaptive to real-world network conditions have not been studied. This dissertation focuses on these questions and explores experimentally derived mathematical models for designing protocols to meet specific application requirements. The main contributions of this research are 1) for industrial wireless sensor systems with fast-changing but repetitive mobile conditions, understand the performance and optimal choice of reliable wireless sensor data transmission methods, 2) for ultra-low energy harvesting wireless sensor devices, design an energy neutral communication protocol, and 3) for distributed rural wireless sensor systems, understand the efficiency of realistic routing in a multi-tier wireless network. Altogether, knowledge derived from study of the systems, models, and protocols in this work fuels the establishment of a useful framework for designing future WSNs