Resolving SINR Queries in a Dynamic Setting

We consider a set of transmitters broadcasting simultaneously on the same frequency under the SINR model. Transmission power may vary from one transmitter to another, and a signal\u27s strength decreases (path loss or path attenuation) by some constant power alpha of the distance traveled. Roughly, a receiver at a given location can hear a specific transmitter only if the transmitter\u27s signal is stronger than the signal of all other transmitters, combined. An SINR query is to determine whether a receiver at a given location can hear any transmitter, and if yes, which one. An approximate answer to an SINR query is such that one gets a definite yes or definite no, when the ratio between the strongest signal and all other signals combined is well above or well below the reception threshold, while the answer in the intermediate range is allowed to be either yes or no. We describe several compact data structures that support approximate SINR queries in the plane in a dynamic context, i.e., where both queries and updates (insertion or deletion of a transmitter) can be performed efficiently

User grouping and power allocation in NOMA systems: a novel semi-supervised reinforcement learning-based solution

Author's accepted manuscriptIn this paper, we present a pioneering solution to the problem of user grouping and power allocation in non-orthogonal multiple access (NOMA) systems. The problem is highly pertinent because NOMA is a well-recognized technique for future mobile radio systems. The salient and difcult issues associated with NOMA systems involve the task of grouping users together into the prespecifed time slots, which are augmented with the question of determining how much power should be allocated to the respective users. This problem is, in and of itself, NP-hard. Our solution is the frst reported reinforcement learning (RL)-based solution, which attempts to resolve parts of this issue. In particular, we invoke the object migration automaton (OMA) and one of its variants to resolve the grouping in NOMA systems. Furthermore, unlike the solutions reported in the literature, we do not assume prior knowledge of the channels’ distributions, nor of their coefcients, to achieve the grouping/partitioning. Thereafter, we use the consequent groupings to heuristically infer the power allocation. The simulation results that we have obtained confrm that our learning scheme can follow the dynamics of the channel coefcients efciently, and that the solution is able to resolve the issue dynamicallyacceptedVersio

Airborne Directional Networking: Topology Control Protocol Design

This research identifies and evaluates the impact of several architectural design choices in relation to airborne networking in contested environments related to autonomous topology control. Using simulation, we evaluate topology reconfiguration effectiveness using classical performance metrics for different point-to-point communication architectures. Our attention is focused on the design choices which have the greatest impact on reliability, scalability, and performance. In this work, we discuss the impact of several practical considerations of airborne networking in contested environments related to autonomous topology control modeling. Using simulation, we derive multiple classical performance metrics to evaluate topology reconfiguration effectiveness for different point-to-point communication architecture attributes for the purpose of qualifying protocol design elements

Optimizing the delivery of multimedia over mobile networks

Mención Internacional en el título de doctorThe consumption of multimedia content is moving from a residential environment to mobile phones. Mobile data traffic, driven mostly by video demand, is increasing rapidly and wireless spectrum is becoming a more and more scarce resource. This makes it highly important to operate mobile networks efficiently. To tackle this, recent developments in anticipatory networking schemes make it possible to to predict the future capacity of mobile devices and optimize the allocation of the limited wireless resources. Further, optimizing Quality of Experience—smooth, quick, and high quality playback—is more difficult in the mobile setting, due to the highly dynamic nature of wireless links. A key requirement for achieving, both anticipatory networking schemes and QoE optimization, is estimating the available bandwidth of mobile devices. Ideally, this should be done quickly and with low overhead. In summary, we propose a series of improvements to the delivery of multimedia over mobile networks. We do so, be identifying inefficiencies in the interconnection of mobile operators with the servers hosting content, propose an algorithm to opportunistically create frequent capacity estimations suitable for use in resource optimization solutions and finally propose another algorithm able to estimate the bandwidth class of a device based on minimal traffic in order to identify the ideal streaming quality its connection may support before commencing playback. The main body of this thesis proposes two lightweight algorithms designed to provide bandwidth estimations under the high constraints of the mobile environment, such as and most notably the usually very limited traffic quota. To do so, we begin with providing a thorough overview of the communication path between a content server and a mobile device. We continue with analysing how accurate smartphone measurements can be and also go in depth identifying the various artifacts adding noise to the fidelity of on device measurements. Then, we first propose a novel lightweight measurement technique that can be used as a basis for advanced resource optimization algorithms to be run on mobile phones. Our main idea leverages an original packet dispersion based technique to estimate per user capacity. This allows passive measurements by just sampling the existing mobile traffic. Our technique is able to efficiently filter outliers introduced by mobile network schedulers and phone hardware. In order to asses and verify our measurement technique, we apply it to a diverse dataset generated by both extensive simulations and a week-long measurement campaign spanning two cities in two countries, different radio technologies, and covering all times of the day. The results demonstrate that our technique is effective even if it is provided only with a small fraction of the exchanged packets of a flow. The only requirement for the input data is that it should consist of a few consecutive packets that are gathered periodically. This makes the measurement algorithm a good candidate for inclusion in OS libraries to allow for advanced resource optimization and application-level traffic scheduling, based on current and predicted future user capacity. We proceed with another algorithm that takes advantage of the traffic generated by short-lived TCP connections, which form the majority of the mobile connections, to passively estimate the currently available bandwidth class. Our algorithm is able to extract useful information even if the TCP connection never exits the slow start phase. To the best of our knowledge, no other solution can operate with such constrained input. Our estimation method is able to achieve good precision despite artifacts introduced by the slow start behavior of TCP, mobile scheduler and phone hardware. We evaluate our solution against traces collected in 4 European countries. Furthermore, the small footprint of our algorithm allows its deployment on resource limited devices. Finally, in an attempt to face the rapid traffic increase, mobile application developers outsource their cloud infrastructure deployment and content delivery to cloud computing services and content delivery networks. Studying how these services, which we collectively denote Cloud Service Providers (CSPs), perform over Mobile Network Operators (MNOs) is crucial to understanding some of the performance limitations of today’s mobile apps. To that end, we perform the first empirical study of the complex dynamics between applications, MNOs and CSPs. First, we use real mobile app traffic traces that we gathered through a global crowdsourcing campaign to identify the most prevalent CSPs supporting today’s mobile Internet. Then, we investigate how well these services interconnect with major European MNOs at a topological level, and measure their performance over European MNO networks through a month-long measurement campaign on the MONROE mobile broadband testbed. We discover that the top 6 most prevalent CSPs are used by 85% of apps, and observe significant differences in their performance across different MNOs due to the nature of their services, peering relationships with MNOs, and deployment strategies. We also find that CSP performance in MNOs is affected by inflated path length, roaming, and presence of middleboxes, but not influenced by the choice of DNS resolver. We also observe that the choice of operator’s Point of Presence (PoP) may inflate by at least 20% the delay towards popular websites.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Ahmed Elmokashfi.- Secretario: Rubén Cuevas Rumín.- Vocal: Paolo Din

Traffic Steering in Radio Level Integration of LTE and Wi-Fi Networks

A smartphone generates approximately 1, 614 MB of data per month which is 48 times of the data generated by a typical basic-feature cell phone. Cisco forecasts that the mobile data traffic growth will remain to increase and reach 49 Exabytes per month by 2021. However, the telecommunication service providers/operators face many challenges in order to improve cellular network capacity to match these ever-increasing data demands due to low, almost flat Average Revenue Per User (ARPU) and low Return on Investment (RoI). Spectrum resource crunch and licensing requirement for operation in cellular bands further complicate the procedure to support and manage the network. In order to deal with the aforementioned challenges, one of the most vital solutions is to leverage the integration benefits of cellular networks with unlicensed operation of Wi-Fi networks. A closer level of cellular and Wi-Fi coupling/interworking improves Quality of Service (QoS) by unified connection management to user devices (UEs). It also offloads a significant portion of user traffic from cellular Base Station (BS) to Wi-Fi Access Point (AP). In this thesis, we have considered the cellular network to be Long Term Evolution (LTE) popularly known as 4G-LTE for interworking with Wi-Fi. Third Generation Partnership Project (3GPP) defined various LTE and Wi-Fi interworking architectures from Rel-8 to Rel-11. Because of the limitations in these legacy LTE Wi-Fi interworking solutions, 3GPP proposed Radio Level Integration (RLI) architectures to enhance flow mobility and to react fast to channel dynamics. RLI node encompasses link level connection between Small cell deployments, (ii) Meeting Guaranteed Bit Rate (GBR) requirements of the users including those experiencing poor Signal to Interference plus Noise Ratio (SINR), and (iii) Dynamic steering of the flows across LTE and Wi-Fi links to maximize the system throughput. The second important problem addressed is the uplink traffic steering. To enable efficient uplink traffic steering in LWIP system, in this thesis, Network Coordination Function (NCF) is proposed. NCF is realized at the LWIP node by implementing various uplink traffic steering algorithms. NCF encompasses four different uplink traffic steering algorithms for efficient utilization of Wi-Fi resources in LWIP system. NCF facilitates the network to take intelligent decisions rather than individual UEs deciding to steer the uplink traffic onto LTE link or Wi-Fi link. The NCF algorithms work by leveraging the availability of LTE as the anchor to improvise the channel utilization of Wi-Fi. The third most important problem is to enable packet level steering in LWIP. When data rates of LTE and Wi-Fi links are incomparable, steering packets across the links create problems for TCP traffic. When the packets are received Out-of-Order (OOO) at the TCP receiver due to variation in delay experienced on each link, it leads to the generation of DUPlicate ACKnowledgements (DUP-ACK). These unnecessary DUP-ACKs adversely affect the TCP congestion window growth and thereby lead to poor TCP performance. This thesis addresses this problem by proposing a virtual congestion control mechanism (VIrtual congeStion control wIth Boost acknowLedgEment -VISIBLE). The proposed mechanism not only improves the throughput of a flow by reducing the number of unnecessary DUPACKs delivered to the TCP sender but also sends Boost ACKs in order to rapidly grow the congestion window to reap in aggregation benefits of heterogeneous links. The fourth problem considered is the placement of LWIP nodes. In this thesis, we have addressed problems pertaining to the dense deployment of LWIP nodes. LWIP deployment can be realized in colocated and non-colocated fashion. The placement of LWIP nodes is done with the following objectives: (i) Minimizing the number of LWIP nodes deployed without any coverage holes, (ii) Maximizing SINR in every sub-region of a building, and (iii) Minimizing the energy spent by UEs and LWIP nodes. Finally, prototypes of RLI architectures are presented (i.e., LWIP and LWA testbeds). The prototypes are developed using open source LTE platform OpenAirInterface (OAI) and commercial-off-the-shelf hardware components. The developed LWIP prototype is made to work with commercial UE (Nexus 5). The LWA prototype requires modification at the UE protocol stack, hence it is realized using OAI-UE. The developed prototypes are coupled with the legacy multipath protocol such as MPTCP to investigate the coupling benefits

The relationship between choice of spectrum sensing device and secondary-user intrusion in database-driven cognitive radio systems

As radios in future wireless systems become more flexible and reconfigurable whilst available radio spectrum becomes scarce, the possibility of using TV White Space devices (WSD) as secondary users in the TV Broadcast Bands (without causing harmful interference to licensed incumbents) becomes ever more attractive. Cognitive Radio encompasses a number of technologies which enable adaptive self-programming of systems at different levels to provide more effective use of the increasingly congested radio spectrum. Cognitive Radio has the potential to use spectrum allocated to TV services, which is not actually being used by these services, without causing disruptive interference to licensed users by using channel selection aided by use of appropriate propagation modelling in TV White Spaces.The main purpose of this thesis is to explore the potential of the Cognitive Radio concept to provide additional bandwidth and improved efficiency to help accelerate the development and acceptance of Cognitive Radio technology. Specifically, firstly: three main classes of spectrum sensing techniques (Energy Detection, Matched Filtering and Cyclostationary Feature Detection) have compare in terms of time and spectrum resources consumed, required prior knowledge and complexity, ranking the three classes according to accuracy and performance. Secondly, investigate spectrum occupancy of the UHF TV band in the frequency range from 470 to 862 MHz by undertaking spectrum occupancy measurements in different locations around the Hull area in the UK, using two different receiver devices; a low cost Software-Defined Radio device and a laboratory-quality spectrum analyser. Thirdly, investigate the best propagation model among three propagation models (Extended-Hata, Davidson-Hata and Egli) for use in the TV band, whilst also finding the optimum terrain data resolution to use (1000, 100 or 30 m). it compares modelled results with the previously-mentioned practical measurements and then describe how such models can be integrated into a database-driven tool for Cognitive Radio channel selection within the TV White Space environment. Fourthly, create a flexible simulation system for creating a TV White Space database by using different propagation models. Finally, design a flexible system which uses a combination of Geolocation Database and Spectrum Sensing in the TV band, comparing the performance of two spectrum analysers (Agilent E4407B and Agilent EXA N9010A) with that of a low cost Software-Defined Radio in the real radio environment. The results shows that white space devices can be designed using SDRs based on the Realtek RTL2832U chip (RTL-SDR), combined with a geolocation database for identifying the primary user in the specific location in a cost-effective manner. Furthermore it is shown that improving the sensitivity of RTL-SDR will affect the accuracy and performance of the WSD