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

INTERFERENCE MANAGEMENT IN LTE SYSTEM AND BEYOUND

The key challenges to high throughput in cellular wireless communication system are interference, mobility and bandwidth limitation. Mobility has never been a problem until recently, bandwidth has been constantly improved upon through the evolutions in cellular wireless communication system but interference has been a constant limitation to any improvement that may have resulted from such evolution. The fundamental challenge to a system designer or a researcher is how to achieve high data rate in motion (high speed) in a cellular system that is intrinsically interference-limited. Multi-antenna is the solution to data on the move and the capacity of multi-antenna system has been demonstrated to increase proportionally with increase in the number of antennas at both transmitter and receiver for point-to-point communications and multi-user environment. However, the capacity gain in both uplink and downlink is limited in a multi-user environment like cellular system by interference, the number of antennas at the base station, complexity and space constraint particularly for a mobile terminal. This challenge in the downlink provided the motivation to investigate successive interference cancellation (SIC) as an interference management tool LTE system and beyond. The Simulation revealed that ordered successive interference (OSIC) out performs non-ordered successive interference cancellation (NSIC) and the additional complexity is justified based on the associated gain in BER performance of OSIC. The major drawback of OSIC is that it is not efficient in network environment employing power control or power allocation. Additional interference management techniques will be required to fully manage the interference.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Massive MIMO for Internet of Things (IoT) Connectivity

Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design.Comment: Submitted for publicatio

Implementação e avaliação no system generator de um sistema cooperativo para os futuros sistemas 5G

With the arrival of 5G it is expected the proliferation of services in the different fields such as healthcare, utility applications, industrial automation, 4K streaming, that the former networks can not provide. Additionally, the total number of wireless communication devices will escalate in such a manner that the already scarce available frequency bandwidth won’t be enough to pack the intended objectives. Cisco’s Annual Internet Report from 2018 predicts that by 2023 there will be nearly 30 billion devices capable of wireless communication. Due to the exponential expiation of both services and devices, the challenges upon both network data capacity and efficient radio resourse use will be greater than ever, thus the urgency for solutions is grand. Both the capacity for wireless communications and spectral efficiency are related to cell size and its users proximity to the access point. Thus, shortening the distance between the transmitter and the receiver improves both aspects of the network. This concept is what motivates the implementation of heterogeneous networks, HetNets, that are composed of many different small-cells, SCs, overlaid across the same coexisting area of a conventional macro-cell, shortening the distance between the cell users and its access point transceivers, granting a better coverage and higher data rates. However, the HetNets potential does not come without any challenges, as these networks suffer considerably from communication interference between cells. Although some interference management algorithms that allow coexistence between cells have been proposed in recent years, most of them were evaluated by software simulations and not implemented in real-time platforms. Therefore, this master thesis aims to give the first step on the implementation and evaluation of an interference mitigation technique in hardware. Specifically, it is assumed a downlink scenario composed by a macro-cell base station, a macro-cell primary user and a small cell user, with the aim of implementing an algorithm that eliminates the downlink interference that the base station may cause to the secondary users. The study was carried out using the System Generator DSP tool, which is a tool that generates code for hardware from schematics created in it. This tool also offers a wide range of blocks that help the creation, and fundamentally, the simulation and study of the system to be implemented, before being translated into hardware. The results obtained in this work are a faithful representation of the behavior of the implemented system, which can be used for a future application for FPGA.Com a chegada do 5G, espera-se a proliferação de serviços nas mais diversas áreas tal como assistência médica, automação industrial, transmissão em 4k, que não eram possíveis nas redes das gerações anteriores. Além deste fenómeno, o número total de dispositivos capazes de conexões wireless aumentará de tal maneira que a escassa largura de banda disponível não será suficiente para abranger os objetivos pretendidos. O Relatório Anual de 2018 sobre a Internet da Cisco prevê que até 2023 haverá quase 30 bilhões de dispositivos capazes de comunicação sem fio. Devido ao aumento exponencial de serviços e dispositivos, os desafios sobre a capacidade de dados da rede e o udo eficiente dos recursos de rádio serão maiores que nunca. Por estes motivos, a necessidade de soluções para estas lacunas é enorme. Tanto a capacidade da rede e o uso eficiente do espectro de frequências estão relacionados ao tamanho da célula e à proximidade dos usuários com o ponto de acesso da célula. Ao encurtar a distância entre o transmissor e o recetor ocorre um melhoramento destes dois aspetos da rede. Este é o principal conceito na implementação de redes heterogéneas, HetNets, que são compostas por diversas células pequenas que coexistem na área de uma macro célula convencional, diminuído a distância entre os utilizadores da célula e os pontos de acesso, garantindo uma melhor cobertura e taxa de dados mais elevadas. No entanto, o potencial das HatNets não vem sem nenhum custo, pois estas redes sofrem consideravelmente de interferência entre as células. Embora nos últimos anos foram propostos alguns algoritmos que permitem a coexistência das células, a maioria destes foi só testado em simulações de software e não em plataformas em tempo real. Por esse motivo, esta dissertação de mestrado visa dar o primeiro passo na implementação e a avaliação de uma técnica de mitigação de interferência em hardware. Mais especificamente no cenário de downlink entre uma estação base de uma macro célula, um utilizador primário da macro célula e um utilizador secundário de uma célula pequena, com o principal objetivo de cancelar a interferência que a estação base possa fazer ao utilizador secundário. O estudo foi realizado utilizando a ferramenta System Generator DSP, que é uma ferramenta que gera código para hardware a partir de esquemáticos criados na mesma. Esta ferramenta também oferece uma vasta gama de blocos que ajudam a criação, e fundamentalmente, a simulação e o estudo do sistema a implementar antes de ser traduzido para hardware. Os resultados obtidos neste trabalho são uma fiel representação do comportamento do sistema implementado. O quais podem ser utilizados para uma futura aplicação para FPGA.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Full-Duplex Cloud Radio Access Network: Stochastic Design and Analysis

Full-duplex (FD) has emerged as a disruptive communications paradigm for enhancing the achievable spectral efficiency (SE), thanks to the recent major breakthroughs in self-interference (SI) mitigation. The FD versus half-duplex (HD) SE gain, in cellular networks, is however largely limited by the mutual-interference (MI) between the downlink (DL) and the uplink (UL). A potential remedy for tackling the MI bottleneck is through cooperative communications. This paper provides a stochastic design and analysis of FD enabled cloud radio access network (C-RAN) under the Poisson point process (PPP)-based abstraction model of multi-antenna radio units (RUs) and user equipments (UEs). We consider different disjoint and user-centric approaches towards the formation of finite clusters in the C-RAN. Contrary to most existing studies, we explicitly take into consideration non-isotropic fading channel conditions and finite-capacity fronthaul links. Accordingly, upper-bound expressions for the C-RAN DL and UL SEs, involving the statistics of all intended and interfering signals, are derived. The performance of the FD C-RAN is investigated through the proposed theoretical framework and Monte-Carlo (MC) simulations. The results indicate that significant FD versus HD C-RAN SE gains can be achieved, particularly in the presence of sufficient-capacity fronthaul links and advanced interference cancellation capabilities

Interference mitigation using group decoding in multiantenna systems

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