Design and Analysis of Medium Access Control Protocols for Broadband Wireless Networks

The next-generation wireless networks are expected to integrate diverse network architectures and various wireless access technologies to provide a robust solution for ubiquitous broadband wireless access, such as wireless local area networks (WLANs), Ultra-Wideband (UWB), and millimeter-wave (mmWave) based wireless personal area networks (WPANs), etc. To enhance the spectral efficiency and link reliability, smart antenna systems have been proposed as a promising candidate for future broadband access networks. To effectively exploit the increased capabilities of the emerging wireless networks, the different network characteristics and the underlying physical layer features need to be considered in the medium access control (MAC) design, which plays a critical role in providing efficient and fair resource sharing among multiple users. In this thesis, we comprehensively investigate the MAC design in both single- and multi-hop broadband wireless networks, with and without infrastructure support. We first develop mathematical models to identify the performance bottlenecks and constraints in the design and operation of existing MAC. We then use a cross-layer approach to mitigate the identified bottleneck problems. Finally, by evaluating the performance of the proposed protocols with analytical models and extensive simulations, we determine the optimal protocol parameters to maximize the network performance. In specific, a generic analytical framework is developed for capacity study of an IEEE 802.11 WLAN in support of non-persistent asymmetric traffic flows. The analysis can be applied for effective admission control to guarantee the quality of service (QoS) performance of multimedia applications. As the access point (AP) becomes the bottleneck in an infrastructure based WLAN, we explore the multiple-input multiple-output (MIMO) capability in the future IEEE 802.11n WLANs and propose a MIMO-aware multi-user (MU) MAC. By exploiting the multi-user degree of freedom in a MIMO system to allow the AP to communicate with multiple users in the downlink simultaneously, the proposed MU MAC can minimize the AP-bottleneck effect and significantly improve the network capacity. Other enhanced MAC mechanisms, e.g., frame aggregation and bidirectional transmissions, are also studied. Furthermore, different from a narrowband system where simultaneous transmissions by nearby neighbors collide with each other, wideband system can support multiple concurrent transmissions if the multi-user interference can be properly managed. Taking advantage of the salient features of UWB and mmWave communications, we propose an exclusive region (ER) based MAC protocol to exploit the spatial multiplexing gain of centralized UWB and mmWave based wireless networks. Moreover, instead of studying the asymptotic capacity bounds of arbitrary networks which may be too loose to be useful in realistic networks, we derive the expected capacity or transport capacity of UWB and mmWave based networks with random topology. The analysis reveals the main factors affecting the network (transport) capacity, and how to determine the best protocol parameters to maximize the network capacity. In addition, due to limited transmission range, multi-hop relay is necessary to extend the communication coverage of UWB networks. A simple, scalable, and distributed UWB MAC protocol is crucial for efficiently utilizing the large bandwidth of UWB channels and enabling numerous new applications cost-effectively. To address this issue, we further design a distributed asynchronous ER based MAC for multi-hop UWB networks and derive the optimal ER size towards the maximum network throughput. The proposed MAC can significantly improve both network throughput and fairness performance, while the throughput and fairness are usually treated as a tradeoff in other MAC protocols

The Future of the Operating Room: Surgical Preplanning and Navigation using High Accuracy Ultra-Wideband Positioning and Advanced Bone Measurement

This dissertation embodies the diversity and creativity of my research, of which much has been peer-reviewed, published in archival quality journals, and presented nationally and internationally. Portions of the work described herein have been published in the fields of image processing, forensic anthropology, physical anthropology, biomedical engineering, clinical orthopedics, and microwave engineering. The problem studied is primarily that of developing the tools and technologies for a next-generation surgical navigation system. The discussion focuses on the underlying technologies of a novel microwave positioning subsystem and a bone analysis subsystem. The methodologies behind each of these technologies are presented in the context of the overall system with the salient results helping to elucidate the difficult facets of the problem. The microwave positioning system is currently the highest accuracy wireless ultra-wideband positioning system that can be found in the literature. The challenges in producing a system with these capabilities are many, and the research and development in solving these problems should further the art of high accuracy pulse-based positioning

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine

Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm

Resource allocation (RA) techniques should be made efficient and optimized in order to enhance the QoS (power & bit, capacity, scalability) of high-speed networking data applications. This research attempts to further increase the efficiency towards near-optimal performance. RA’s problem involves assignment of subcarriers, power and bit amounts for each user efficiently. Several studies conducted by the Federal Communication Commission have proven that conventional RA approaches are becoming insufficient for rapid demand in networking resulted in spectrum underutilization, low capacity and convergence, also low performance of bit error rate, delay of channel feedback, weak scalability as well as computational complexity make real-time solutions intractable. Mainly due to sophisticated, restrictive constraints, multi-objectives, unfairness, channel noise, also unrealistic when assume perfect channel state is available. The main goal of this work is to develop a conceptual framework and mathematical model for resource allocation using Shuffled Frog-Leap Algorithm (SFLA). Thus, a modified SFLA is introduced and integrated in Orthogonal Frequency Division Multiplexing (OFDM) system. Then SFLA generated random population of solutions (power, bit), the fitness of each solution is calculated and improved for each subcarrier and user. The solution is numerically validated and verified by simulation-based powerline channel. The system performance was compared to similar research works in terms of the system’s capacity, scalability, allocated rate/power, and convergence. The resources allocated are constantly optimized and the capacity obtained is constantly higher as compared to Root-finding, Linear, and Hybrid evolutionary algorithms. The proposed algorithm managed to offer fastest convergence given that the number of iterations required to get to the 0.001% error of the global optimum is 75 compared to 92 in the conventional techniques. Finally, joint allocation models for selection of optima resource values are introduced; adaptive power and bit allocators in OFDM system-based Powerline and using modified SFLA-based TLBO and PSO are propose

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

On Efficient Signal Processing Algorithms for Signal Detection and PAPR Reduction in OFDM Systems

The driving force of the study is susceptibility of LS algorithm to noise. As LS algorithm is simple to implement, hence it’s performance improvement can contribute a lot to the wireless technology that are especially deals with high computation. Cascading of AdaBoost algorithm with LS greatly influences the OFDM system performance. Performance of Adaptive Boosting based symbol recovery was investigated on the performance of LS, MMSE, BLUE were also compared with the performance of AdaBoost algorithm and MMSE has been found the higher computational complexity. Furthermore, MMSE also requires apriori channel statistics and computational complexity O(5N3) of the MMSE increases exponentially as the number of carrier increases. For the Adaboost case the computational complexity calculation is little different.Therefore, in the training stage of the AdaBoost algorithm, the computational complexity is only O(nT M) Furthermore, as it is a classification algorithm so in the receiver side we will require a separate de-mapper (or decoder) to get the desired data bits, i.e., a. SAS aided DCT based PAPR reduction 1326 and b. SAS aided DCT based PAPR reduction. A successive addition subtraction preprocessed DCT based PAPR reduction technique was proposed. Here, the performance of proposed method was compared with other preexisting techniques like SLM and PTS and the performance of the proposed method was seen to outperform specially in low PAPR region. In the proposed PAPR reduction method, the receiver is aware of the transmitted signal processing, this enables a reverse operation at the receiver to extract the transmit data. Hence the requirement of sending extra information through extra subcarrier is eliminated. The proposed method is also seen to be spectrally efficient. In the case of PTS and SLM it is inevitable to send the side information to retrieve the transmit signal. Hence, these two methods are spectrally inefficient. Successive addition subtraction based PAPR reduction method was also applied to MIMO systems. The performance of the SAS based PAPR reduction method also showed better performance as compared to other technique. An extensive simulation of MIMO OFDM PAPR reduction was carried out by varying the number of subcarriers and number of transmitter antennas. A detailed computational complexity analysis was also carried out. BATE aided SDMA multi user detection. A detailed study of SDMA system was carried out with it’s mathematical analysis.Many linear and non linear detectors like ML, MMSE, PIC, SIC have been proposed in literature for multiuser detection of SDMA system. However, except MMSE every receivers other are computational extensive. So as to enhance the performance of the MMSE MUD a meta heuristic Bat algorithm was incorporated in cascade with MMSE