A Powerful Optimization Approach for the Multi Channel Dissemination Networks

In the wireless environment, dissemination techniques may improve data access for the users. In this paper, we show a description of dissemination architecture that fits the overall telecommunication network. This architecture is designed to provide efficient data access and power saving for the mobile units. A concurrency control approach, MCD, is suggested for data consistency and conflict checking. A performance study shows that the power consumption, space overhead, and response time associated with MCD is far less than other previous techniques.Comment: 9 Pages, IJCNC Journal 201

Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

Distributed environmental monitoring

With increasingly ubiquitous use of web-based technologies in society today, autonomous sensor networks represent the future in large-scale information acquisition for applications ranging from environmental monitoring to in vivo sensing. This chapter presents a range of on-going projects with an emphasis on environmental sensing; relevant literature pertaining to sensor networks is reviewed, validated sensing applications are described and the contribution of high-resolution temporal data to better decision-making is discussed

A Systematic Review of LPWAN and Short-Range Network using AI to Enhance Internet of Things

Artificial intelligence (AI) has recently been used frequently, especially concerning the Internet of Things (IoT). However, IoT devices cannot work alone, assisted by Low Power Wide Area Network (LPWAN) for long-distance communication and Short-Range Network for a short distance. However, few reviews about AI can help LPWAN and Short-Range Network. Therefore, the author took the opportunity to do this review. This study aims to review LPWAN and Short-Range Networks AI papers in systematically enhancing IoT performance. Reviews are also used to systematically maximize LPWAN systems and Short-Range networks to enhance IoT quality and discuss results that can be applied to a specific scope. The author utilizes selected reporting items for systematic review and meta-analysis (PRISMA). The authors conducted a systematic review of all study results in support of the authors' objectives. Also, the authors identify development and related study opportunities. The author found 79 suitable papers in this systematic review, so a discussion of the presented papers was carried out. Several technologies are widely used, such as LPWAN in general, with several papers originating from China. Many reports from conferences last year and papers related to this matter were from 2020-2021. The study is expected to inspire experimental studies in finding relevant scientific papers and become another review

Portable Waveform Development for Software Defined Radios

This work focuses on the question: "How can we build waveforms that can be moved from one platform to another?\u27\u27 Therefore an approach based on the Model Driven Architecture was evaluated. Furthermore, a proof of concept is given with the port of a TETRA waveform from a USRP platform to an SFF SDR platform

Interference Mitigation in Frequency Hopping Ad Hoc Networks

Radio systems today exhibit a degree of flexibility that was unheard of only a few years ago. Software-defined radio architectures have emerged that are able to service large swathes of spectrum, covering up to several GHz in the UHF bands. This dissertation investigates interference mitigation techniques in frequency hopping ad hoc networks that are capable of exploiting the frequency agility of software-defined radio platforms

BASEBAND RADIO MODEM DESIGN USING GRAPHICS PROCESSING UNITS

A modern radio or wireless communications transceiver is programmed via software and firmware to change its functionalities at the baseband. However, the actual implementation of the radio circuits relies on dedicated hardware, and the design and implementation of such devices are time consuming and challenging. Due to the need for real-time operation, dedicated hardware is preferred in order to meet stringent requirements on throughput and latency. With increasing need for higher throughput and shorter latency, while supporting increasing bandwidth across a fragmented spectrum, dedicated subsystems are developed in order to service individual frequency bands and specifications. Such a dedicated-hardware-intensive approach leads to high resource costs, including costs due to multiple instantiations of mixers, filters, and samplers. Such increases in hardware requirements in turn increases device size, power consumption, weight, and financial cost. If it can meet the required real-time constraints, a more flexible and reconfigurable design approach, such as a software-based solution, is often more desirable over a dedicated hardware solution. However, significant challenges must be overcome in order to meet constraints on throughput and latency while servicing different frequency bands and bandwidths. Graphics processing unit (GPU) technology provides a promising class of platforms for addressing these challenges. GPUs, which were originally designed for rendering images and video sequences, have been adapted as general purpose high-throughput computation engines for a wide variety of application areas beyond their original target domains. Linear algebra and signal processing acceleration are examples of such application areas. In this thesis, we apply GPUs as software-based, baseband radios and demonstrate novel, software-based implementations of key subsystems in modern wireless transceivers. In our work, we develop novel implementation techniques that allow communication system designers to use GPUs as accelerators for baseband processing functions, including real-time filtering and signal transformations. More specifically, we apply GPUs to accelerate several computationally-intensive, frontend radio subsystems, including filtering, signal mixing, sample rate conversion, and synchronization. These are critical subsystems that must operate in real-time to reliably receive waveforms. The contributions of this thesis can be broadly organized into 3 major areas: (1) channelization, (2) arbitrary resampling, and (3) synchronization. 1. Channelization: a wideband signal is shared between different users and channels, and a channelizer is used to separate the components of the shared signal in the different channels. A channelizer is often used as a pre-processing step in selecting a specific channel-of-interest. A typical channelization process involves signal conversion, resampling, and filtering to reject adjacent channels. We investigate GPU acceleration for a particularly efficient form of channelizer called a polyphase filterbank channelizer, and demonstrate a real-time implementation of our novel channelizer design. 2. Arbitrary resampling: following a channelization process, a signal is often resampled to at least twice the data rate in order to further condition the signal. Since different communication standards require different resampling ratios, it is desirable for a resampling subsystem to support a variety of different ratios. We investigate optimized, GPU-based methods for resampling using polyphase filter structures that are mapped efficiently into GPU hardware. We investigate these GPU implementation techniques in the context of interpolation (integer-factor increases in sampling rate), decimation (integer-factor decreases in sampling rate), and rational resampling. Finally, we demonstrate an efficient implementation of arbitrary resampling using GPUs. This implementation exploits specialized hardware units within the GPU to enable efficient and accurate resampling processes involving arbitrary changes in sample rate. 3. Synchronization: incoming signals in a wireless communications transceiver must be synchronized in order to recover the transmitted data properly from complex channel effects such as thermal noise, fading, and multipath propagation. We investigate timing recovery in GPUs to accelerate the most computationally intensive part of the synchronization process, and correctly align the incoming data symbols in the receiver. Furthermore, we implement fully-parallel timing error detection to accelerate maximum likelihood estimation

Context Aware Routing Management Architecture for Airborne Networks

This thesis advocates the use of Kalman filters in conjunction with network topology information derived from the Air Tasking Order (ATO) during the planning phase for military missions. This approach is the basis for an algorithm that implements network controls that optimize network performance for Mobile Ad hoc Networks (MANET). The trajectories of relevant nodes (airborne platforms) participating in the MANET can be forecasted by parsing key information contained in the ATO. This information is used to develop optimum network routes that can significantly improve MANET performance. Improved MANET performance in the battlefield enables decision makers to access information from several sensors that can summarize mission execution status real-time. In one simulated test case there was a 25% percent improvement of network throughput, and 23% reduction on dropped packets. Using this technique we can selectively preserve the Quality of Service (QoS) by establishing network controls that drops low priority packets when necessary. The algorithm improves the overall MANET throughput while minimizing the packets dropped due to network congestion