Interference mitigation in cognitive femtocell networks

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.Femtocells have been introduced as a solution to poor indoor coverage in cellular communication which has hugely attracted network operators and stakeholders. However, femtocells are designed to co-exist alongside macrocells providing improved spatial frequency reuse and higher spectrum efficiency to name a few. Therefore, when deployed in the two-tier architecture with macrocells, it is necessary to mitigate the inherent co-tier and cross-tier interference. The integration of cognitive radio (CR) in femtocells introduces the ability of femtocells to dynamically adapt to varying network conditions through learning and reasoning. This research work focuses on the exploitation of cognitive radio in femtocells to mitigate the mutual interference caused in the two-tier architecture. The research work presents original contributions in mitigating interference in femtocells by introducing practical approaches which comprises a power control scheme where femtocells adaptively controls its transmit power levels to reduce the interference it causes in a network. This is especially useful since femtocells are user deployed as this seeks to mitigate interference based on their blind placement in an indoor environment. Hybrid interference mitigation schemes which combine power control and resource/scheduling are also implemented. In a joint threshold power based admittance and contention free resource allocation scheme, the mutual interference between a Femtocell Access Point (FAP) and close-by User Equipments (UE) is mitigated based on admittance. Also, a hybrid scheme where FAPs opportunistically use Resource Blocks (RB) of Macrocell User Equipments (MUE) based on its traffic load use is also employed. Simulation analysis present improvements when these schemes are applied with emphasis in Long Term Evolution (LTE) networks especially in terms of Signal to Interference plus Noise Ratio (SINR)

Técnicas de igualização adaptativas com estimativas imperfeitas do canal para os futuros sistemas 5G

Wireless communication networks have been continuously experiencing an exponential growth since their inception. The overwhelming demand for high data rates, support of a large number of users while mitigating disruptive interference are the constant research focus and it has led to the creation of new technologies and efficient techniques. Orthogonal frequency division multiplexing (OFDM) is the most common example of a technology that has come to the fore in this past decade as it provided a simple and generally ideal platform for wireless data transmission. It’s drawback of a rather high peak-to-average power ratio (PAPR) and sensitivity to phase noise, which in turn led to the adoption of alternative techniques, such as the single carrier systems with frequency domain equalization (SC-FDE) or the multi carrier systems with code division multiple access (MC-CDMA), but the nonlinear Frequency Domain Equalizers (FDE) have been of special note due to their improved performance. From these, the Iterative Block Decision Feedback Equalizer (IB-DFE) has proven itself especially promising due to its compatibility with space diversity, MIMO systems and CDMA schemes. However, the IB-DFE requires the system to have constant knowledge of the communication channel properties, that is, to have constantly perfect Channel State Information (CSI), which is both unrealistic and impractical to implement. In this dissertation we shall design an altered IB-DFE receiver that is able to properly detect signals from SC-FDMA based transmitters, even with constantly erroneous channel states. The results shall demonstrate that the proposed equalization scheme is robust to imperfect CSI (I-CSI) situations, since its performance is constantly close to the perfect CSI case, within just a few iterations.Redes sem fios têm crescido de maneira contínua e exponencial desde a sua incepção. A tremenda exigência para altas taxas de dados e o suporte para um elevado número de utilizadores sem aumentar a interferência disruptiva originada por estes são alguns dos focos que levaram ao desenvolvimento de técnicas de compensação e novas tecnologias. “Orthogonal frequency division multiplexing” (OFDM) é um dos exemplos de tecnologias que se destacaram nesta última década, visto ter fornecido uma plataforma para transmissão de dados sem-fio eficaz e simples. O seu maior problema é a alta “peak-to-average power ratio” (PAPR) e a sua sensibilidade a ruído de fase que deram motivo à adoção de técnicas alternativas, tais como os sistemas “single carrier” com “frequency domain equalization” (SC-FDE) ou os sistemas “multi-carrier” com “code division multiple access” (MC-CDMA), mas equalizadores não lineares no domínio de frequência têm sido alvo de especial atenção devido ao seu melhor desempenho. Destes, o “iterative block decision feedback equalizer” (IB-DFE) tem-se provado especialmente promissor devido à sua compatibilidade com técnicas de diversidade no espaço, sistemas MIMO e esquemas CDMA. No entanto, IB-DFE requer que o sistema tenha constante conhecimento das propriedades dos canais usados, ou seja, necessita de ter perfeito “channel state information” (CSI) constantemente, o que é tanto irrealista como impossível de implementar. Nesta dissertação iremos projetar um recetor IB-DFE alterado de forma a conseguir detetar sinais dum transmissor baseado em tecnologia SC-FDMA, mesmo com a informação de estado de canal errada. Os resultados irão então demonstrar que o novo esquema de equalização proposto é robusto para situações de CSI imperfeito (I-CSI), visto que o seu desempenho se mantém próximo dos valores esperados para CSI perfeito, em apenas algumas iterações.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Digital Pre-distortion for Interference Reduction in Dynamic Spectrum Access Networks

Given the ever increasing reliance of today’s society on ubiquitous wireless access, the paradigm of dynamic spectrum access (DSA) as been proposed and implemented for utilizing the limited wireless spectrum more efficiently. Orthogonal frequency division multiplexing (OFDM) is growing in popularity for adoption into wireless services employing DSA frame- work, due to its high bandwidth efficiency and resiliency to multipath fading. While these advantages have been proven for many wireless applications, including LTE-Advanced and numerous IEEE wireless standards, one potential drawback of OFDM or its non-contiguous variant, NC-OFDM, is that it exhibits high peak-to-average power ratios (PAPR), which can induce in-band and out-of-band (OOB) distortions when the peaks of the waveform enter the compression region of the transmitter power amplifier (PA). Such OOB emissions can interfere with existing neighboring transmissions, and thereby severely deteriorate the reliability of the DSA network. A performance-enhancing digital pre-distortion (DPD) technique compensating for PA and in-phase/quadrature (I/Q) modulator distortions is proposed in this dissertation. Al- though substantial research efforts into designing DPD schemes have already been presented in the open literature, there still exists numerous opportunities to further improve upon the performance of OOB suppression for NC-OFDM transmission in the presence of RF front-end impairments. A set of orthogonal polynomial basis functions is proposed in this dissertation together with a simplified joint DPD structure. A performance analysis is presented to show that the OOB emissions is reduced to approximately 50 dBc with proposed algorithms employed during NC-OFDM transmission. Furthermore, a novel and intuitive DPD solution that can minimize the power regrowth at any pre-specified frequency in the spurious domain is proposed in this dissertation. Conventional DPD methods have been proven to be able to effectively reduce the OOB emissions that fall on top of adjacent channels. However more spectral emissions in more distant frequency ranges are generated by employing such DPD solutions, which are potentially in violation of the spurious emission limit. At the same time, the emissions in adjacent channel must be kept under the OOB limit. To the best of the author’s knowledge, there has not been extensive research conducted on this topic. Mathematical derivation procedures of the proposed algorithm are provided for both memoryless nonlinear model and memory-based nonlinear model. Simulation results show that the proposed method is able to provide a good balance of OOB emissions and emissions in the far out spurious domain, by reducing the spurious emissions by 4-5 dB while maintaining the adjacent channel leakage ratio (ACLR) improvement by at least 10 dB, comparing to the PA output spectrum without any DPD

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

Efficient and Virtualized Scheduling for OFDM-Based High Mobility Wireless Communications Objects

Services providers (SPs) in the radio platform technology standard long term evolution (LTE) systems are enduring many challenges in order to accommodate the rapid expansion of mobile data usage. The modern technologies demonstrate new challenges to SPs, for example, reducing the cost of the capital and operating expenditures while supporting high data throughput per customer, extending battery life-per-charge of the cell phone devices, and supporting high mobility communications with fast and seamless handover (HO) networking architecture. In this thesis, a variety of optimized techniques aimed at providing innovative solutions for such challenges are explored. The thesis is divided into three parts. The first part outlines the benefits and challenges of deploying virtualized resource sharing concept. Wherein, SPs achieving a different schedulers policy are sharing evolved network B, allowing SPs to customize their efforts and provide service requirements; as a promising solution for reducing operational and capital expenditures, leading to potential energy savings, and supporting higher peak rates. The second part, formulates the optimized power allocation problem in a virtualized scheme in LTE uplink systems, aiming to extend the mobile devices’ battery utilization time per charge. While, the third part extrapolates a proposed hybrid-HO (HY-HO) technique, that can enhance the system performance in terms of latency and HO reliability at cell boundary for high mobility objects (up to 350 km/hr; wherein, HO will occur more frequent). The main contributions of this thesis are in designing optimal binary integer programmingbased and suboptimal heuristic (with complexity reduction) scheduling algorithms subject to exclusive and contiguous allocation, maximum transmission power, and rate constraints. Moreover, designing the HY-HO based on the combination of soft and hard HO was able to enhance the system performance in term of latency, interruption time and reliability during HO. The results prove that the proposed solutions effectively contribute in addressing the challenges caused by the demand for high data rates and power transmission in mobile networks especially in virtualized resources sharing scenarios that can support high data rates with improving quality of services (QoSs)

Security-Enhanced SC-FDMA Transmissions Using Temporal Artificial-Noise and Secret Key Aided Schemes

We investigate the physical-layer security of uplink single-carrier frequency-division multiple-access (SC-FDMA) systems. Multiple users, Alices, send confidential messages to a common legitimate base-station, Bob, in the presence of an eavesdropper, Eve. To secure the legitimate transmissions, each user superimposes an artificial noise (AN) signal on the time-domain SC-FDMA data symbol. We reduce the computational and storage requirements at Bob's receiver by assuming simple per-sub-channel detectors. We assume that Eve has global channel knowledge of all links in addition to high computational capabilities, where she adopts high-complexity detectors such as single-user maximum likelihood (ML), multi-user minimum-mean-square-error, and multi-user ML. We analyze the correlation properties of the time-domain AN signal and illustrate how Eve can exploit them to reduce the AN effects. We prove that the number of useful AN streams that can degrade Eve's signal-to-noise ratio is dependent on the channel memories of Alices-Bob and Alices-Eve links. Furthermore, we enhance the system security for the case of partial Alices-Bob channel knowledge at Eve, where Eve only knows the precoding matrices of the data and AN signals instead of knowing the entire Alices-Bob channel matrices, and propose a hybrid security scheme that integrates temporal AN with channel-based secret key extraction. - 2019 IEEE.This work was supported by the Qatar National Research Fund (a member of the Qatar Foundation) through NPRP under Grant 8-627-2-260. The statements made herein are solely the responsibility of the authors.Scopu