Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

On implementation aspects of decode and forward and compress and forward relay protocols

In this work, the common relay protocols Decode-and-Forward and Compress-and-Forward (CF) are investigated from a practical point of view: This involves on the one hand the impact of imperfections like channel and carrier phase stimation errors and on the other hand, the question of how to implement relay protocol specific signal processing like quantization for CF which is modeled in information theory simply by additive quantizer noise. To evaluate the performance, achievable rates are determined either numerically with the help of the Max-Flow Min-Cut theorem or by link level simulations.Diese Arbeit untersucht die Relay-Protokolle Decode-and-Forward und Compress-and-Forward (CF) mit dem Fokus auf einer praktischen Umsetzung. Es werden sowohl Störeinflüsse wie Kanal- und Phasenschätzfehler betrachtet als auch spezielle Kompressionsverfahren für das CF Protokoll implementiert. Von großer Bedeutung ist hier die Kompression in Form der Quantisierung, weil diese in der Informationstheorie lediglich durch Quantisierungsrauschen modelliert wird. Zur Auswertung der Leistungsfähigkeit der Protokolle werden die erzielbaren Raten entweder numerisch oder durch Simulation bestimmt

Medium Access Control Layer Implementation on Field Programmable Gate Array Board for Wireless Networks

Triple play services are playing an important role in modern telecommunications systems. Nowadays, more researchers are engaged in investigating the most efficient approaches to integrate these services at a reduced level of operation costs. Field Programmable Gate Array (FPGA) boards have been found as the most suitable platform to test new protocols as they offer high levels of flexibility and customization. This thesis focuses on implementing a framework for the Triple Play Time Division Multiple Access (TP-TDMA) protocol using the Xilinx FPGA Virtex-5 board. This flexible framework design offers network systems engineers a reconfigiirable platform for triple-play systems development. In this work, MicorBlaze is used to perform memory and connectivity tests aiming to ensure the establishment of the connectivity as well as board’s processor stability. Two different approaches are followed to achieve TP-TDMA implementa­tion: systematic and conceptual. In the systematic approach, a bottom-to-top design is chosen where four subsystems are built with various components. Each component is then tested individually to investigate its response. On the other hand, the concep­tual approach is designed with only two components, in which one of them is created with the help of Xilinx Integrated Software Environment (ISE) Core Generator. The system is integrated and then tested to check its overall response. In summary, the work of this thesis is divided into three sections. The first section presents a testing method for Virtex-5 board using MicroBlaze soft processor. The following two sections concentrate on implementing the TP-TDMA protocol on the board by using two design approaches: one based on designing each component from scratch, while the other one focuses more on the system’s broader picture

Leveraging Kubernetes in Edge-Native Cable Access Convergence

Public clouds provide infrastructure services and deployment frameworks for modern cloud-native applications. As the cloud-native paradigm has matured, containerization, orchestration and Kubernetes have become its fundamental building blocks. For the next step of cloud-native, an interest to extend it to the edge computing is emerging. Primary reasons for this are low-latency use cases and the desire to have uniformity in cloud-edge continuum. Cable access networks as specialized type of edge networks are not exception here. As the cable industry transitions to distributed architectures and plans the next steps to virtualize its on-premise network functions, there are opportunities to achieve synergy advantages from convergence of access technologies and services. Distributed cable networks deploy resource-constrained devices like RPDs and RMDs deep in the edge networks. These devices can be redesigned to support more than one access technology and to provide computing services for other edge tenants with MEC-like architectures. Both of these cases benefit from virtualization. It is here where cable access convergence and cloud-native transition to edge-native intersect. However, adapting cloud-native in the edge presents a challenge, since cloud-native container runtimes and native Kubernetes are not optimal solutions in diverse edge environments. Therefore, this thesis takes as its goal to describe current landscape of lightweight cloud-native runtimes and tools targeting the edge. While edge-native as a concept is taking its first steps, tools like KubeEdge, K3s and Virtual Kubelet can be seen as the most mature reference projects for edge-compatible solution types. Furthermore, as the container runtimes are not yet fully edge-ready, WebAssembly seems like a promising alternative runtime for lightweight, portable and secure Kubernetes compatible workloads

The Family of MapReduce and Large Scale Data Processing Systems

In the last two decades, the continuous increase of computational power has produced an overwhelming flow of data which has called for a paradigm shift in the computing architecture and large scale data processing mechanisms. MapReduce is a simple and powerful programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. It isolates the application from the details of running a distributed program such as issues on data distribution, scheduling and fault tolerance. However, the original implementation of the MapReduce framework had some limitations that have been tackled by many research efforts in several followup works after its introduction. This article provides a comprehensive survey for a family of approaches and mechanisms of large scale data processing mechanisms that have been implemented based on the original idea of the MapReduce framework and are currently gaining a lot of momentum in both research and industrial communities. We also cover a set of introduced systems that have been implemented to provide declarative programming interfaces on top of the MapReduce framework. In addition, we review several large scale data processing systems that resemble some of the ideas of the MapReduce framework for different purposes and application scenarios. Finally, we discuss some of the future research directions for implementing the next generation of MapReduce-like solutions.Comment: arXiv admin note: text overlap with arXiv:1105.4252 by other author