Browsing by Author "Rosenberg, Catherine"

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5G Fixed Wireless Access for Bridging the Rural Digital Divide
(University of Waterloo, 2021-09-22) Lappalainen, Andrew; Rosenberg, Catherine
Despite the ubiquitous level of mobile and fixed broadband (FB) connectivity that exists for many people today, the availability of high quality FB services in rural communities is generally much lower than in urban communities, which has led to a digital divide. At the same time, rural communities in Canada have a high level of 4G LTE coverage and the mobile digital divide between urban and rural communities is much smaller compared to the FB divide. Traditionally, FB and mobile services were offered over separate technologies by different operators, and evolved separately from one another. However, recently, a convergence between mobile and FB has started to emerge via 4G Fixed Wireless Access (FWA), which has made it possible to take advantage of the high level of cellular coverage in rural communities to offer (limited) FB at lower costs than traditional wired FB. To bridge the digital divide, rural FWA must be able to provide the same end-to-end experience as urban FB. In in this regard, 4G FWA has been inadequate; however, the recent emergence of 5G, which brings new spectrum, a more efficient radio interface, and multi-user massive MIMO, can make a difference. In the first half of this thesis we outline a vision for how 5G could fix the rural connectivity gap by truly enabling FWA in rural regions. We examine new and upcoming improvements to each area of the 5G network architecture and how they can benefit rural users. Despite those advancements, 5G operators will face a number of challenges in planning and operating rural FWA networks. Therefore, we also draw attention to a number of open research challenges that will need to be addressed. In the latter half of this thesis, we study the planning of a rural 5G multi-user massive MIMO FWA TDD system to offer fixed broadband service to homes. Specifically, we aim to determine the user limit, i.e., the maximum number of homes that can simultaneously receive a target minimum bit rate (MBR) on the downlink (DL) and a target MBR on the uplink (UL) given a set of network resources (e.g., bandwidth, power, antennas) and given a radius. To attain that limit, we must understand how resources should be shared between the DL and UL and how user selection (as well as stream selection since both the base-station (BS) and the homes are multi-antenna), precoding and combining, and power distribution should be performed. To simplify the problem, we use block diagonalization and propose a static user grouping strategy that organizes homes into fixed groups in the DL and UL (we use different groups for the two directions); then we develop a simple process to find the user limit by determining the amount of resources required to give groups the MBRs. We study the impact of group sizes and show that smaller groups use more streams and enable more homes to receive the MBRs when using a 3.5~GHz band. We then show how the user limit at different cell radii is impacted by the system bandwidth, the number of antennas at the BS and homes, the BS power, and the DL and UL MBRs. Lastly, we offer insight into how the network could be operated for an arbitrary number of homes.
A Comparative Study of Resource Allocation Schemes in Heterogeneous Cellular Networks on the Downlink
(University of Waterloo, 2016-04-29) Shaverdian, Ararat; Rosenberg, Catherine
Network densification through heterogeneous networks (HetNets) is considered as a promising paradigm to address the ever increasing mobile users’ data demands in 5G networks. A HetNet consists of macro cells (each with a macro base station) overlaid with a number of small cells (each with a low-power base station) and has been shown to significantly improve the network capacity when supported by carefully designed radio resource management (RRM) techniques. RRM is typically studied via a joint optimisation problem over three network processes, namely, resource allocation (RA), user association (UA) and user scheduling (US), and is the focus of this thesis. Our first objective is to characterise the optimal HetNet performance by jointly optimising these three processes through a unified framework under different channel deployment scenarios. Towards this, we focus on two RA schemes, namely, partially shared deployment (PSD) and co-channel deployment with almost blank subframes (ABS), proposed by 3GPP for future HetNets. In the first part of the thesis, we revisit a unified optimisation framework under PSD that allows us to configure the network parameters (e.g., number of channels per-cell and power per-channel) and allocate optimal throughputs to users in a fair manner. The framework under consideration is based on a snapshot model where, in each snapshot, the number of users and channel gains are assumed to be fixed and known. Although the previous study on this framework provides many interesting engineering insights, it is primarily based on two wrong assumptions in terms of channel modelling and US which we correct in our work. We also revisit a similar framework but under ABS and conduct a thorough comparative study between ABS and PSD. We first show that the U+03B1-fair scheduling problem under ABS is generally much more involved than that under PSD for U+03B1 U+2260 1. To verify whether the US complexities involved from deploying ABS are justifiable, we compare the throughput performance of the two schemes under a static setting, where the number of users in each snapshot is assumed to be fixed. Our results indicate that PSD outperforms ABS for different choices of U+03B1-fair and under different HetNet configurations. In the second part of the thesis, we further study our frameworks under a dynamic setting and continue our comparisons between the two RA schemes under different service-time models. The dynamic setting, as well as reaffirming the upper-hand of PSD, provides a number of new insights, most importantly the fact that the conventional physical-layer based UA schemes do not always work well. Motivated by this observation, we further explore the problem of UA under PSD with the objective of improving an existing online UA scheme. We show that when users are periodically triggered to re-associate (on an individual basis), the online UA scheme can significantly improve the system performance.
Hydrogel-Based Dye-sensitized Solar Cells
(University of Waterloo, 2024-04-23) Jamali, Hussain; Rosenberg, Catherine; Naahidi, Sheva
Utilizing PVA-PANI hydrogel as a quasi-solid state electrolyte in DSSC enhances device stability and efficiency. The hydrogel matrix provides mechanical robustness and facilitates ion transport, improving charge transfer kinetics. This novel approach holds promise for advancing the performance of dye-sensitized solar cells.
Impact of Mechanical and Electrical Tilting for Cellular-Connected Drones and Legacy Users
(University of Waterloo, 2025-01-23) Elleathy, Ahmad; Rosenberg, Catherine
Drones, also known as Unmanned Aerial Vehicle (UAV)s, have lately been employed for a variety of tasks in our daily lives, including surveillance, delivery, and rescue operations. High-performance, dependable two-way communication with cellular networks is necessary to expand UAV applications quickly. Supporting different UAVs into current fifth generation (5G) networks is challenging. One of these challenges comes from ground and aerial users having different channel properties. This thesis investigates how the performance of cellular-connected UAVs and legacy ground users in a cellular network can be improved by changing the antenna tilting angle or type, and we will consider mechanical, electrical, and hybrid tilting in the system. This study considers the case of single user Multiple-Input Multiple-Output (SU-MIMO) system featuring Uniform Linear Array (ULA) or Uniform Planar Array (UPA) antenna system with Third Generation Partnership Project (3GPP) parameters. This study illustrates the impact of antenna tilting in improving user throughput, making it easier to integrate UAVs into 5G and future networks. These conclusions are supported by simulation results, which also show how hybrid tilting may be used as a scalable way to enhance multi-user performance for next-generation networks.
Implementation and Comparative Analysis of Open 5G Standalone Testbeds: A Systematic Approach
(University of Waterloo, 2025-01-21) Amini, Maryam; Rosenberg, Catherine
Open-source software and commercial off-the-shelf hardware are finally paving their way into the 5G world, resulting in a proliferation of experimental 5G testbeds. Surprisingly, very few studies have been published on the comparative analysis of testbeds with different hardware and software elements. This dissertation is a comprehensive study on the implementation of experimental 5G testbeds and the challenges associated with them. We first introduce a precise nomenclature to characterize a 5G-standalone single-cell testbed based on its constituent elements and main configuration parameters. We then build 36 distinct such testbeds and systematically analyze and compare their performance with an emphasis on element interoperability, as well as the number and type of User Equipment (UE), to address the following questions: 1) How is the performance (in terms of bit rate and latency) impacted by different elements? 2) How does the number of UEs affect these results? 3) What is the impact of the user(s)' location(s) on the performance? 4) What is the impact of the UE type on these results? 5) How far does each testbed provide coverage? 6) What is the impact of the available computational resources on the performance of each open-source software? Finally, to illustrate the practical applications of such open experimental testbeds, we present a case study focused on user scheduling. Historically, most research on user scheduling has been conducted using simulations, with a strong emphasis on downlink scheduling. In contrast, our study is fully experimental, and targets enhancements to the uplink scheduler within the open-source Radio Access Network platform, srsRAN. We aim to move beyond simulation-based evaluations and explore how improvements in the uplink scheduler translate to real-world performance, specifically by measuring their impact on the user experience in a live experimental testbed.
An Implementation of 5G-AKA and a Usability Analysis of OpenLDAP Access Control Lists (ACLs)
(University of Waterloo, 2021-08-27) Punchhi, Rahul; Rosenberg, Catherine; Tripunitara, Mahesh
We address two pieces of work: (i) an implementation of the Authentication and Key Agreement protocol suite from the 5th generation cellular communications standards (5G-AKA) that we intend to make available as open-source, and, (ii) a categorization using Hierarchical Task Analysis (HTA) of errors made by human participants in a study carried out on the usability of Access Control Lists (ACLs) in the OpenLDAP directory. Our work (i) on 5G-AKA is motivated by the lack of availability of such an implementation that can then be used by researchers and practitioners for further work. We discuss design choices we have made; for example, our choice of the Java programming language and cryptographic packages, and our choice to model the three entities that communicate using 5G-AKA, the User Equipment (UE), the Serving Network (SN), and the Home Network (HN) as three distinct processes that communicate over TCP sockets. We also discuss challenges we encountered in carrying out our work, and the manner in which we plan to make our work available as open-source. Our work (ii) on error-identification in the use of ACLs in OpenLDAP is part of a broader human-subject study that, in turn, is motivated by public pronouncements of their poor usability. We discuss what HTAs are, and why they are appropriate for our work. We present our design of the HTAs, the errors we identified using them, and observe that this work helps with a prospective redesign of ACLs for OpenLDAP.
Modelling, Design, and Control of Energy Systems: A Data-Driven Approach
(University of Waterloo, 2019-09-23) Kazhamiaka, Fiodar; Keshav, Srinivasan; Rosenberg, Catherine
In 2018, nearly two-thirds of newly installed global power generation has come from renewable energy sources. Distributed installations of solar photovoltaic (PV) panels have been at the forefront of this global energy transition. In many places, the cost of solar power has dropped below the cost of fossil fuels such as coal. The main challenge in incorporating this growing source of clean and cheap energy is its high variability; it must often be used in conjunction with an expensive energy storage system to help match electricity supply and demand. Despite the growing focus on energy storage and its role in helping meet the ambitious renewable energy targets set by climate-conscious policy makers, the relatively high capital cost of combined PV-storage systems has limited their widespread adoption. The high cost of PV-storage systems may be offset by the value they provide to system owners. The combination of PV panel and energy storage components adds complexity and flexibility to an energy system where both supply and demand are stochastic and depend on many factors, and this contributes to the technical challenges of system design and operation. Practical methods for increasing the value of PV-storage systems through effective system design and operation are the focus of this dissertation. The proposed approach to solving these problems involves the use of system models and data describing the system's operating environment. Our research consists of two main components: the theoretical component, i.e., modelling, and the practical component, i.e., analysis of energy systems on the basis of models and data. In this thesis, we construct new battery models that enable simulation and optimization studies of PV-storage systems. These models are then used to develop several advanced methods for designing and operating PV-storage systems based on available solar generation and electricity consumption data. We study the problem of determining the combined sizes of PV panel and storage components to meet a given system load target at the lowest possible cost. We also study the problem of system operation, with the objective of increasing system value via minimization of operating expenses. The sizing and control methods developed in this thesis are based primarily on system simulation, mathematical programming, and neural networks, and are evaluated on datasets of PV generation and electricity consumption measurements of buildings. Among our contributions are an accurate battery model for simulation studies that can be easily calibrated. We further derive models for optimization studies with various degrees of accuracy and complexity, including a linear model with higher accuracy than existing linear models. For system sizing, we develop a novel approach for sizing a PV-storage system to reliably meet a load performance target at the lowest possible cost. For system operation, we develop a set of algorithms which achieve high performance with low information requirements, a mixed-timescale approach to reduce the online computational complexity of model predictive control, and a system controller designed to encode a deep neural network with a model predictive control policy and capable of refining its performance over time while adapting to changes in the operating environment.
Operating multi-user transmission for 5G and beyond cellular systems
(University of Waterloo, 2023-02-16) Hussein, Abdalla; Rosenberg, Catherine; Mitran, Patrick
Every decade, a new generation of cellular networks is released to keep up with the ever-growing demand for data and use cases. Traditionally, cellular networks rely on partitioning radio resources into a set of physical resource blocks (PRBs). Each PRB is used by the base-station to transmit exclusively to one user, which is referred to as single-user transmission. Recently, multi-user transmission has been introduced to enable the base-station to simultaneously serve multiple users using the same PRB. While multi-user transmission can be much more efficient than its single-user counterpart, it is significantly more challenging to operate. Thus, in this thesis we study the operation, i.e., the Radio Resource Management (RRM), for two popular multi-user transmission technologies; namely, 1) Non-Orthogonal Multiple Access (NOMA) and 2) Multi-User Multiple-Input Multiple-Output (MU-MIMO). For NOMA RRM, we study a multi-cell, multi-carrier downlink system. First, we formulate and solve a centralized proportional fair scheduling genie problem that jointly performs user selection, power allocation and power distribution, and Modulation and Coding Scheme (MCS) selection. While such a centralized schedule is practically infeasible, it upper bounds the achievable performance. Then, we propose a simple static coordinated power allocation scheme across all cells for NOMA using a simple power map that is easily calibrated offline. We find that using a simple static coordinated power allocation scheme improves performance by 80% compared to equal power allocation. Finally, we focus on online network operation and study practical schedulers that perform user-selection, power distribution, and MCS selection. We propose a family of practical scheduling algorithms, each of them exhibiting a different trade-off between complexity (i.e., run-time) and performance. The one we selected sacrifices a maximum of 10% performance while reducing the computation time by a factor of 45 with respect to the optimal user scheduler. For MU-MIMO RRM, we focus on the study of the downlink of an OFDMA massive MU-MIMO single cell assuming ZFT (Zero Forcing Transmission) precoding. An offline study is initiated with the goal of finding the best achievable performance by jointly optimizing user-selection, power distribution and MCS selection. The best performance is analyzed by using both Branch-Reduce-and-Bound (BRB) global optimization technique for upper-bounding the achievable performance and a set of different greedy searches for lower bounding the achievable performance to find good feasible solutions. The results suggest that a specific search strategy referred to as greedy-down-all-the-way (GDAW) with full-drop (FD) is quasi-optimal. Afterwards, we design a simple practical scheduler that achieves 97% of the performance to GDAW with FD and has comparable runtime to that of the state-of-the-art benchmark that selects all users, performs ZFT precoding followed by power distribution using water-filling. The proposed scheme performs a simple round robin grouping to select users, followed by ZFT precoding and joint power distribution and MCS selection via a novel greedy algorithm with a possible additional iteration to take zero-rate users into account. Our solution outperforms the benchmark by 281%.
Parameterizing Enterprise WiFi Networks: The Use of Wide Channels
(University of Waterloo, 2019-01-23) Malekmohammadi, Saber; Rosenberg, Catherine
We investigate the joint channel, power, and carrier sensing threshold allocation problem in IEEE 802.11ac enterprise networks in a single 160 MHz band and show that the current practice, which is to use narrower channels at maximum power when the network is dense, yields much worse performance than a solution using the widest possible channel (i.e., 160 MHz) with a much lower power. This finding is consistent with cellular networks which use a reuse factor of one. Based on these insights, we propose and evaluate an algorithm that allocates the widest channel to all Access Points, and finds the appropriate transmission power and carrier sensing threshold for each of them to provide an efficient and fair solution to a managed IEEE 802.11ac enterprise network. The performance gains with respect to the best of the two benchmarks that we consider range from 60% in not too dense deployments to more than 200% in dense deployments.
Resource Management in Next Generation Cellular Networks
(University of Waterloo, 2019-07-03) Ozcan, Yigit; Rosenberg, Catherine
Fifth generation of cellular networks brings new challenges to the network operators as new applications create new demands. In this thesis, we will study different topics on cellular networks, explain the challenges of each topic, and propose solutions to tackle these challenges. The topics we consider are: i) uplink scheduling in multi-cell OFDMA networks, ii) downlink scheduling in multi-cell OFDMA networks, iii) full-duplex communications in cellular networks, and iv) cellular networks with intra-cellular traffic. We begin our study with uplink scheduling in 5G networks as its importance has increased in recent years and the related literature is relatively scarce. Scheduling on the uplink is a challenging task mostly due to power and interference management. In practical scenarios, each cell schedules its own users independently from the other cells. In this case, the interference that is received from the neighboring cells cannot be known since the schedules of the other cells are not known. Therefore, interference has to be estimated in order to estimate the rate of each user. When this estimation is not done properly, it can cause resource losses or under-utilization as we show in this thesis. To avoid this problem, all the cells could be scheduled simultaneously using a cloud radio access network (C-RAN) and hence we can take the exact interference into account while scheduling. Formulating the optimal multi-cell scheduler is straightforward, but it is a very large integer problem that cannot be solved easily and fast. We transform it into a more tractable upper bounding problem and solve it with an iterative algorithm. However, it is still not fast enough to be used in real time. Hence, we focus on improving the existing uplink schedulers by proposing practical solutions for the case when there is no C-RAN and for the case when a C-RAN is present. We also propose a soft frequency reuse (SFR) based scheduler that performs much better than the existing schedulers. We then perform a similar study for downlink scheduling that carries the majority of the cellular traffic today. While downlink scheduling is easier than the uplink due to simpler interference management, it is still not trivial to achieve performance comparable to the maximum achievable performance using a practical scheduler. The main contribution of this study is to show that a well-tuned SFR-based local scheduler can perform almost as well as the centralized scheduler and hence a centralized scheme for downlink might not be necessary. We next consider a cellular network where full-duplex communications (FDC) are enabled at the base stations. The coexistence of uplink and downlink transmissions in co-channel cells create new sources of interference that have to be taken into account when studying the performance of FDC. When doing so, traffic asymmetry (TA), i.e., the fact that the traffic is in general much larger on the downlink than on the uplink, should also be considered. We will show that ignoring TA biases the results in favor of FDC. We compute the performance gain that an FDC-enabled multi-cell OFDMA network has over a regular time division duplex (TDD) system considering all sources of interference and TA by formulating a multi-cell centralized scheduling problem. We use it to analyze the impact of each new source of interference as well as of TA. Our conclusion is that, FDC does not improve performance enough in a multi-cell system to warrant its added complexity in an urban setting when TA and the interference have realistic values. The verdict is slightly better in a rural setting. Furthermore, we show that heterogeneous networks can be a better choice than the homogeneous networks to deploy FDC when it is adjusted well. We finalize our study with device-to-device (D2D) communications. With the advent of smart phones, there are many new applications that create local (intra-cellular) traffic among the users in the same network. Most work in the literature focuses on the possibility to utilize a direct link between those users to by-pass the base station. Such transmissions are called D2D mode. However, implementing D2D is not easy due to difficult interference management and not knowing the required channel gains. We face a major problem while studying D2D. We need a clear benchmark to evaluate the performance of D2D mode. To this end, we focus on designing a type-aware scheduler (a scheduler that has the information on the type of traffic, which can be downlink, uplink, or intra-cellular) in a case where direct communication between users is not enabled. This scheduler can be seen as the benchmark against D2D mode. We show that performance gain can be obtained by jointly scheduling the uplink and downlink with respect to the case where the scheduler is blind to the types. We show for a homogeneous network that when the traffic types are known to a scheduler, a significant performance gain can be achieved compared to the case where the traffic types are not known. We also analyze heterogeneous networks that consist of macro cells and small cells and show that large performance gain can be obtained by performing type-aware user association jointly with user scheduling. The main contributions of the thesis are i) to analyze the performance of existing schedulers and see if they perform well enough compared to the maximum achievable performance both on the uplink and the downlink, ii) to propose enhancements or new schedulers when the existing schedulers do not perform well enough, iii) to illustrate when FDC deployment can be useful under which scenarios, and iv) to show the importance of information of traffic types when users with different types of traffic exist.
Smart Charging of Plug-in Electric Vehicles in Distribution Systems Considering Uncertainties
(University of Waterloo, 2016-05-05) Mehboob, Nafeesa; Canizares, Claudio; Rosenberg, Catherine
Distribution feeders and equipment are designed to serve peak loads, and in the absence of Plug-in Electric Vehicle (PEV) loads, day-ahead dispatch of feeders is typically performed by optimizing feeder controls for forecasted load profiles. However, due to climate change concerns, the market share of PEVs is expected to increase, and consequently, utilities expect an increase in demand due to these loads charging from the grid. Uncontrolled charging of PEVs may lead to new peaks in distribution feeders, which would require expensive infrastructure and equipment upgrades. Furthermore, PEV loads will represent new sources of uncertainty, temporal and spatial, which will pose a challenge for the centralized control and optimal operation of the grid. In practice, these uncertainties arise as a result of variability in factors such as the number of PEVs connected to the grid for charging, the arrival and departure times of PEVs, and the initial battery State-of-Charge (SoC). Hence, the integration of PEVs into the existing distribution system, without significant infrastructure upgrades, will be possible only through smart charging of these loads, while properly accounting for these uncertainties. The elasticity of PEVs provides a level of flexibility that can be used by utilities or Local Distribution Companies (LDC) to ensure efficient feeder operation, while providing fair and efficient charging to PEV customers. This thesis presents a novel two-step approach for the fair charging of PEVs in a primary distribution feeder, accounting for the uncertainty associated with PEVs, considering the perspectives of both the LDC and the PEV customer. In the first step of the proposed approach, the mean daily feeder peak demand and corresponding hourly feeder control schedules, such as taps and switched capacitor setpoints, are determined hourly, while minimizing the daily peak demand, taking the existence of PEVs into account. As an alternative to the conventional Monte Carlo Simulations (MCS), a nonparametric Bootstrap technique is used in conjunction with a Genetic Algorithm (GA)-based optimization model, to account for variations in the arrival and departure times, and the initial battery SoC of PEVs, at each node. In the second step, the maximum possible power that can be given to the charging PEVs at each node, while maintaining the peak demand value and corresponding feeder dispatch schedules defined in the first step, is computed every few minutes and shared fairly among the PEVs. The proposed technique is validated using the IEEE 13-bus test feeder as well as the distribution feeder model of an actual primary feeder in Ontario, considering significant PEV penetration levels. The potential gain in PEV charging efficiency is quantified for the proposed Bootstrap feeder control schedule with respect to the base schedule (without PEVs). The presented optimization approach is also compared with the current industry practice in Ontario, and a sensitivity-based heuristic technique, demonstrating the advantages and feasibility of the presented technique. The results show that the proposed approach could be implemented in practice due to its reasonable computational burden, and its ability to charge PEV loads better than the current industry practice, or a popular heuristic method, while satisfying feeder and peak demand constraints.
Smart Operation of Electric Vehicles With Four-Quadrant Chargers Considering Uncertainties
(Institute of Electrical and Electronics Engineers (IEEE), 2018-03-15) Mehboob, Nafeesa; Restrepo, Mauricio; Canizares, Claudio A.; Rosenberg, Catherine; Kazerani, Mehrdad
Given the expected impact of electric vehicle (EV) charging on power grids, this paper presents a novel two-step approach for the smart operation of EVs with four-quadrant chargers in a primary distribution feeder, accounting for the uncertainties associated with EVs, and considering the perspectives of both the utility and the EV owners. In the first step of the proposed approach, the mean daily feeder peak demand and corresponding hourly feeder control schedules, such as taps and switched capacitor setpoints, considering the bidirectional active and reactive power transactions between EVs and the grid, are determined. A nonparametric bootstrap technique is used, in conjunction with a genetic algorithm-based optimization model, to account for EV uncertainties and discrete variables. In the second step, the maximum possible power that can be given to connected EVs at each node, while providing active and/or reactive power to maintain the peak demand value and corresponding feeder dispatch schedules defined in the first step, is computed every few minutes in a way which is fair to the EVs. The proposed approach is validated using the distribution feeder model of a real primary feeder in Ontario, Canada, considering significant EV penetration levels. The results show that the proposed approach could be implemented in practice to properly operate EVs, satisfying feeder, and peak demand constraints, which would be better than the business-as-usual practice or a popular heuristic method in terms of number of tap operations, system peak demand, and voltage regulation.
Smart Planning and Operation in Cellular Networks
(University of Waterloo, 2020-12-14) Ho, Jonah; Rosenberg, Catherine
Cellular networks are less and less regular as operators add base stations (BSs) to increase coverage and performance. Given these facts, we explore the network planning and operation stages of the downlink of a multi-cell Orthogonal Frequency Division Multiple Access (OFDMA)-based network. In the planning stage, which is an offline process, we look at improving expected performance while maintaining good coverage. To do so, we parameterize offline a simple power map assignment to be used by all BSs. In the operation stage, which is an online process, we look at improving performance by handling load imbalance and hotspots in the network. To do so, we propose a heuristic that modifies the power map (from the planning stage) by allocating subchannels to BSs, and specifying for each BS the transmit power to use on the subchannels. The research questions are as follows: i) Is conventional planning good enough in view of the fact that networks are less and less regular? ii) BS subchannel allocation is typically done only in the planning stage, can we (re)do it more often (i.e., during the operation stage) to improve performance? iii) How can we take load imbalance and hotspots into account when operating a network? To answer these questions, we propose and investigate one planning scheme and one simple and practical operation scheme in the downlink. We evaluate these schemes on three different network topologies (i.e., 19-cell regular, highly irregular, and lightly irregular). For each we consider both uniform and non-uniform distributions of users (i.e., hotspots). The simulations take place in a dynamic setting with arriving and departing users. The contributions are as follows: i) We propose a simple power map assignment that we parameterize to offer good performance and good coverage even in highly irregular networks, ii) We propose a heuristic based on BS coordination that allocates subchannels to BSs and specifies for each BS the transmit power to use on the subchannels to handle load imbalance and hotspots, and iii) A practical heuristic implementation that reduces BS coordination.
Smart Roaming: How Operator Cooperation Can Increase Spectrum Usage Efficiency At practically No Cost
(University of Waterloo, 2018-09-26) Venkitesh, Bharat; Rosenberg, Catherine
We propose Smart Roaming (SR), a cooperation technique between cellular telcos operating in the same region, that enables users to roam for performance reasons (instead of lack of coverage from their operator). Within a region, base-stations of different operators are seldom co-located and even when they are, the sectors are rarely aligned. SR leverages spatial diversity to enhance spectrum usage efficiency, specifically an edge user of an operator might well be a ``good user" for another one. This work answers the following research questions: i) Can significant gain be obtained with SR? ii) What are the factors that affect the gain? iii) How to deal with operator heterogeneity to avoid that a large operator cross subsidizes a smaller one? iv) How to implement SR in an online fashion? We answer the first three questions by proposing a snapshot model for the downlink that shows that SR can indeed provide significant gain without yielding cross-subsidies if done properly. We then propose two schemes to implement SR online 1) a modification of the scheduler to allow base-stations to discriminate between users of different operators (a necessity to avoid cross-subsidy) jointly with a ``free" user association (UA) whereby each user selects the best base-station irrespective of the operator it belongs to; 2) a controlled UA based on a distributed load sharing algorithm combined with the legacy scheduler. We evaluate these two schemes via extensive simulations based on two traffic scenarios and find gains in efficiency (defined as the per-operator sum-rate) above 25% and better performance for the first scheme. However, the second scheme might be easier to adopt since it does not affect the schedulers.
State Estimation in Power Distribution Systems
(University of Waterloo, 2017-12-19) Carquex, Côme; Rosenberg, Catherine
State estimation in power distribution systems is a key component for increased reliability and optimal system performance. Well understood in transmission systems, state estimation is now an area of active research in distribution networks. While several snapshot-based approaches have been used to solve this problem, few solutions have been proposed in a dynamic framework. In this thesis, a Past-Aware State Estimation (PASE) method is proposed for distribution systems that takes previous estimates into account to improve the accuracy of the current one, using an Ensemble Kalman Filter. Fewer phasor measurements units (PMU) are needed to achieve the same estimation error target than snapshot-based methods. Contrary to current methods, the proposed solution does not embed power flow equations into the estimator. A theoretical formulation is presented to compute a priori the advantages of the proposed method vis-a-vis the state-of-the-art. The proposed approach is validated considering the 33-bus distribution system and using power consumption traces from real households. Engineering insights are presented highlighting the major trade-offs in the choice of decision variables (number of PMUs, PMU accuracy, estimation time-step - i.e. elapsed time between two consecutive estimations) for the LDC: using a smaller time-step allows the LDC to relax the requirements on the PMU quality and their number.
WRR based Two-Level Slice Scheduler for 5G RAN Sharing in the context of Neutral Host
(University of Waterloo, 2022-02-11) Demirci, Yekta; Tripunitara, Mahesh; Rosenberg, Catherine
We investigate the sub-channel sharing problem in the context of Neutral Host Radio Access Network (RAN) slicing. We consider a single user Multiple Input Multiple Output system where each Virtual Network Operator (VNO) brings their own sub-channels and they use the RAN infrastructure in a common way. We assume that the power budget is constant per Physical Resource Block (PRB). We consider only the Downlink and a system made of one single cell. We assume the RAN infrastructure is operated by the Neutral Host. First, we consider the State of the Art (SOA), static sub-channel allocation where the VNOs are allocated only the sub-channels they brought. In the case of SOA, if a VNO experiences no traffic then the sub-channels will remain idle and the resources would be wasted. Considering this we propose a two-level-slice scheduler to utilize the idle resources better than the SOA. We implement the proposed scheduler in an open-source RAN platform, Open-Air-Interface (OAI). We provide detailed set-up guides for the OAI platform in emulation and with Commercial-Off-The-Shelf (COTS) hardware. Finally, we compare the performance of the SOA and the proposed scheduler in terms of system throughput and delay in four different scenarios. The proposed two-level-slice scheduler provides strictly less delay than the SOA in all the experiments.