This thesis presents several simple, robust, and optimal resource management schemes for multihop wireless access networks with the main focus on multi-channel wireless mesh networks (MC WMNs). In this regard, various resource management optimization problems are formulated arid efficient algorithms are proposed to solve each problem. First, we consider the channel as signment problem in MC-WMNs and formulate different resource management problems within the general framework of network utility maximization (NUM). Unlike most of the previously proposed channel assignment schemes, our algorithms can not only assign the orthogonal (i.e., non-overlapped) channels, but also partially overlapped channels. This better utilizes the avail able frequency spectrum as a critical resource in MC-WMNs. Second, we propose two distributed random medium access control (MAC) algorithms to solve a non-convex NUM problem at the MAC layer. The first algorithm is fast, optimal, and robust to message loss and delay. It also only requires a limited message passing among the wireless nodes. Using distributed learning techniques, we then propose another NUM-based MAC algorithm which achieves the optimal performance without frequent message exchange. Third, based on our results on random MAC, we develop a distributed multi-interface multi-channel random access algorithm to solve the NUM problem in MC-WMNs. Different from most of the previous channel assignment schemes in the literature, where channel assignment is intuitively modeled in the form of combinatorial and discrete optimization problems, our scheme is based on formulating a novel continuous optimization model. This makes the analysis and implementation significantly easier. Finally, we consider the problem of pricing and monetary exchange in multi-hop wireless access networks, where each intermediate node receives a payment to compensate for its offered packet forwarding service. In this regard, we propose a market-based wireless access network model with two-fold pricing. It uses relay-pricing to encourage collaboration among the access points. It also uses interference pricing to leverage optimal resource management. In general, this thesis widely benefits from several mathematical techniques as both modeling and solution tools to achieve simple, robust, optimal, and practical resource management strategies for future wireless access networks.

This thesis presents several simple, robust, and optimal resource management schemes for multihop wireless access networks with the main focus on multi-channel wireless mesh networks (MC WMNs). In this regard, various resource management optimization problems are formulated arid efficient algorithms are proposed to solve each problem. First, we consider the channel as signment problem in MC-WMNs and formulate different resource management problems within the general framework of network utility maximization (NUM). Unlike most of the previously proposed channel assignment schemes, our algorithms can not only assign the orthogonal (i.e., non-overlapped) channels, but also partially overlapped channels. This better utilizes the avail able frequency spectrum as a critical resource in MC-WMNs. Second, we propose two distributed random medium access control (MAC) algorithms to solve a non-convex NUM problem at the MAC layer. The first algorithm is fast, optimal, and robust to message loss and delay. It also only requires a limited message passing among the wireless nodes. Using distributed learning techniques, we then propose another NUM-based MAC algorithm which achieves the optimal performance without frequent message exchange. Third, based on our results on random MAC, we develop a distributed multi-interface multi-channel random access algorithm to solve the NUM problem in MC-WMNs. Different from most of the previous channel assignment schemes in the literature, where channel assignment is intuitively modeled in the form of combinatorial and discrete optimization problems, our scheme is based on formulating a novel continuous optimization model. This makes the analysis and implementation significantly easier. Finally, we consider the problem of pricing and monetary exchange in multi-hop wireless access networks, where each intermediate node receives a payment to compensate for its offered packet forwarding service. In this regard, we propose a market-based wireless access network model with two-fold pricing. It uses relay-pricing to encourage collaboration among the access points. It also uses interference pricing to leverage optimal resource management. In general, this thesis widely benefits from several mathematical techniques as both modeling and solution tools to achieve simple, robust, optimal, and practical resource management strategies for future wireless access networks.

The predicted growth in mobile phone traffic and the move towards enhanced mobility will lead to a need for a wireless infrastructure that provides increasing bandwidth per user. It is envisaged that our world will become increasingly interconnected, with mobile communications enabling us to perform an increasing range of tasks. / Future wireless networks will require an optical network to provide antenna Base Stations with sufficient bandwidth to provide individual users with a larger bandwidth. The combined optical and wireless network is referred to as a “fibre-radio” or “radio-over-fibre” or “fibre-wireless”; network. It is expected that such high-capacity networks will use Wavelength Division Multiplexing (WDM) to increase the total bandwidth transmitted over the optical access network. Such a high-capacity network would not be achievable using a single wavelength or using a copper or coax network. Optical crosstalk is present in WDM optical networks and degrades the received signal quality, increasing the bit-error-rate. Two types of crosstalk occur, depending on whether the crosstalk channel is a different wavelength to the signal or at the same wavelength (out-of-band and in-band crosstalk, respectively). An important consideration for fibre-radio networks is whether or not the optical network transports data at baseband, using standard intensity modulation, or at an RF frequency, using subcarrier modulation. The nature of the optical modulation scheme has implications for the design of the Central Office and the Base Stations, and potentially for optical crosstalk. (For complete abstract open document)

This thesis presents several simple, robust, and optimal resource management schemes for multihop wireless access networks with the main focus on multi-channel wireless mesh networks (MC WMNs). In this regard, various resource management optimization problems are formulated arid efficient algorithms are proposed to solve each problem. First, we consider the channel as signment problem in MC-WMNs and formulate different resource management problems within the general framework of network utility maximization (NUM). Unlike most of the previously proposed channel assignment schemes, our algorithms can not only assign the orthogonal (i.e., non-overlapped) channels, but also partially overlapped channels. This better utilizes the avail able frequency spectrum as a critical resource in MC-WMNs. Second, we propose two distributed random medium access control (MAC) algorithms to solve a non-convex NUM problem at the MAC layer. The first algorithm is fast, optimal, and robust to message loss and delay. It also only requires a limited message passing among the wireless nodes. Using distributed learning techniques, we then propose another NUM-based MAC algorithm which achieves the optimal performance without frequent message exchange. Third, based on our results on random MAC, we develop a distributed multi-interface multi-channel random access algorithm to solve the NUM problem in MC-WMNs. Different from most of the previous channel assignment schemes in the literature, where channel assignment is intuitively modeled in the form of combinatorial and discrete optimization problems, our scheme is based on formulating a novel continuous optimization model. This makes the analysis and implementation significantly easier. Finally, we consider the problem of pricing and monetary exchange in multi-hop wireless access networks, where each intermediate node receives a payment to compensate for its offered packet forwarding service. In this regard, we propose a market-based wireless access network model with two-fold pricing. It uses relay-pricing to encourage collaboration among the access points. It also uses interference pricing to leverage optimal resource management. In general, this thesis widely benefits from several mathematical techniques as both modeling and solution tools to achieve simple, robust, optimal, and practical resource management strategies for future wireless access networks. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

<p>Internet access using IEEE 802.11 wireless local area networks has become very common. In home and office networks where voice, video and audio will be delivered, quality of service (QoS) support is essential so that customers can be offered video on demand, audio on demand, voice over IP and high-speed Internet access. In addition to the proliferation of WLAN hotspots, WLAN mesh networks are now being used as a cost-effective means for coverage extension and backhaul relaying between IEEE 802.11 access points (APs).</p> <p> In conventional IEEE 802.11, APs are always continuously powered using fixed wired connections. In future WLAN mesh networks however, wired power connections may not always be readily available, especially in Wi-Fi hotzone installations which cover expansive outdoor areas. In such cases, fixed power connections can often be replaced by a battery operated or solar powered design. For this reason, power saving on the AP is highly desirable for this type of application. Unfortunately, this is not possible since the existing IEEE 802.11 standard requires that APs remain active at all times.</p> <p> In this thesis, we propose and investigate a comprehensive framework for a power saving QoS-enabled access point (PSQAP), intended for use in solar and low power IEEE 802.11 infrastructure applications. An energy-efficient media access control protocol is proposed using the contention-based channel access mode for IEEE 802.11. When real-time flows are present, a PSQAP schedules its awakening/sleeping pattern in a manner that satisfies the delay and packet loss requirements for the admitted real-time flows. A dynamic connection-admission control algorithm is proposed for efficient management of wireless resources. We show that both background traffic and the synchronization of stations' transmissions due to AP's alternating between awake and sleep states can cause excess queuing and packet collision rate. These effects result in an increase in packet delay and power consumption at the mobile stations in contention-based channel access mode. We propose and investigate several scheduling methods for mitigating these effects. It is also shown that voice over IP over WLAN (VoWLAN) suffers a low capacity problem and high handset/AP power consumption. A novel adaptive voice packetization scheme is proposed which improves VoIP capacity and reduces power consumption. The work in this thesis is characterized by analytical models and evaluated through extensive network simulations to study and analyze the key performance aspects of the proposed framework and the associated protocols.</p> / Thesis / Doctor of Philosophy (PhD)

In the LTE access networks, the Radio Resource Management (RRM) is one of the most important modules which is responsible for handling the overall management of radio resources. The packet scheduler is a particular sub-module which assigns the existing radio resources to each user in order to deliver the requested services in the most efficient manner. Data packets are scheduled dynamically at every Transmission Time Interval (TTI), a time window used to take the user’s requests and to respond them accordingly. The scheduling procedure is conducted by using scheduling rules which select different users to be scheduled at each TTI based on some priority metrics. Various scheduling rules exist and they behave differently by balancing the scheduler performance in the direction imposed by one of the following objectives: increasing the system throughput, maintaining the user fairness, respecting the Guaranteed Bit Rate (GBR), Head of Line (HoL) packet delay, packet loss rate and queue stability requirements. Most of the static scheduling rules follow the sequential multi-objective optimization in the sense that when the first targeted objective is satisfied, then other objectives can be prioritized. When the targeted scheduling objective(s) can be satisfied at each TTI, the LTE scheduler is considered to be optimal or feasible. So, the scheduling performance depends on the exploited rule being focused on particular objectives. This study aims to increase the percentage of feasible TTIs for a given downlink transmission by applying a mixture of scheduling rules instead of using one discipline adopted across the entire scheduling session. Two types of optimization problems are proposed in this sense: Dynamic Scheduling Rule based Sequential Multi-Objective Optimization (DSR-SMOO) when the applied scheduling rules address the same objective and Dynamic Scheduling Rule based Concurrent Multi-Objective Optimization (DSR-CMOO) if the pool of rules addresses different scheduling objectives. The best way of solving such complex optimization problems is to adapt and to refine scheduling policies which are able to call different rules at each TTI based on the best matching scheduler conditions (states). The idea is to develop a set of non-linear functions which maps the scheduler state at each TTI in optimal distribution probabilities of selecting the best scheduling rule. Due to the multi-dimensional and continuous characteristics of the scheduler state space, the scheduling functions should be approximated. Moreover, the function approximations are learned through the interaction with the RRM environment. The Reinforcement Learning (RL) algorithms are used in this sense in order to evaluate and to refine the scheduling policies for the considered DSR-SMOO/CMOO optimization problems. The neural networks are used to train the non-linear mapping functions based on the interaction among the intelligent controller, the LTE packet scheduler and the RRM environment. In order to enhance the convergence in the feasible state and to reduce the scheduler state space dimension, meta-heuristic approaches are used for the channel statement aggregation. Simulation results show that the proposed aggregation scheme is able to outperform other heuristic methods. When the aggregation scheme of the channel statements is exploited, the proposed DSR-SMOO/CMOO problems focusing on different objectives which are solved by using various RL approaches are able to: increase the mean percentage of feasible TTIs, minimize the number of TTIs when the RL approaches punish the actions taken TTI-by-TTI, and minimize the variation of the performance indicators when different simulations are launched in parallel. This way, the obtained scheduling policies being focused on the multi-objective criteria are sustainable. Keywords: LTE, packet scheduling, scheduling rules, multi-objective optimization, reinforcement learning, channel, aggregation, scheduling policies, sustainable.

In this thesis, components and parameters based power models (PMs) are produced to measure the power consumption (PC) of cloud radio access network (CRAN) architecture. In components PM, the power figure of each component within C-RAN is evaluated. After, this model is parametrised such that the computation complexity of each component is converted to a straightforward, but accurate method, called parameterised PM. This model compares cooling and total PC of traditional LTE architecture with C-RAN. This comparison considered different parameters such as, utilised bandwidth, number of antenna, base band units (BBUs) and remote radio heads (RRHs). This model draws about 33% reduction in power. Next, this PC model is updated to serve and exhibit the cost of integrating software defined networks (SDNs) with C-RAN. Alongside, modelling the power cost of the control plane units in the core network (CN), such as serving gateway (SGW), packet gateway (PGW) and mobility management entity (MME). Although there is power cost, the proposed model shows the directions to mitigate it. Consequently, a simplified PM is proposed for virtualisation based C-RAN. In this model, the power cost of server virtualisation by hosting several virtual machines (VMs) is shown, in a time and cost effective way. The total reduction in the PC was about 75%, due to short-cutting the number of active servers in the network. Alongside, the latency cost due to such technique is modelled. Finally, to enable efficient virtualisation technology, live migrating the VMs amongst the servers is vital. However, this advantageous situation is concurrent with VM's migration time and power cost. Therefore, a model is proposed to calculate the power cost of VM's live migration, and shows the effect of such decision upon the total PC of the network/C-RAN. The proposed work converts the complexity of other proposed PMs, to a simplified and costless method. Concurrently, the time cost is added to the imposed virtualisation's time cost to formulate the total delay expected prior to these techniques' execution.

Emerging 5G mobile networks are envisioned to become multi-service environments, enabling the dynamic deployment of services with a diverse set of performance requirements, accommodating the needs of mobile network operators, verticals and over-the-top service providers. The Radio Access Network (RAN) part of mobile networks is expected to play a very significant role towards this evolution. Unfortunately, such a vision cannot be efficiently supported by the conventional RAN architecture, which adopts a fixed and rigid design. For the network to evolve, flexibility in the creation, management and control of the RAN components is of paramount importance. The key elements that can allow us to attain this flexibility are the programmability and the virtualization of the network functions. While in the case of the mobile core, these issues have been extensively studied due to the advent of technologies like Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) and the similarities that the core shares with other wired networks like data centers, research in the domain of the RAN is still in its infancy. The contributions made in this thesis significantly advance the state of the art in the domain of RAN programmability and virtualization in three dimensions. First, we design and implement a software-defined RAN (SD-RAN) platform called FlexRAN, that provides a flexible control plane designed with support for real-time RAN control applications, flexibility to realize various degrees of coordination among RAN infrastructure entities, and programmability to adapt control over time and easier evolution to the future following SDN/NFV principles. Second, we leverage the capabilities of the FlexRAN platform to design and implement Orion, which is a novel RAN slicing system that enables the dynamic on-the-fly virtualization of base stations, the flexible customization of slices to meet their respective service needs and which can be used in an end-to-end network slicing setting. Third, we focus on the use case of multi-tenancy in a neutral-host indoors small-cell environment, where we design Iris, a system that builds on the capabilities of FlexRAN and Orion and introduces a dynamic pricing mechanism for the efficient and flexible allocation of shared spectrum to the tenants. A number of additional use cases that highlight the benefits of the developed systems are also presented. The lessons learned through this research are summarized and a discussion is made on interesting topics for future work in this domain. The prototype systems presented in this thesis have been made publicly available and are being used by various research groups worldwide in the context of 5G research.

This thesis explores a novel technique for transceiver design in future wireless systems, which is cloud radio access networks (CRANs) with single radio frequency (RF) chain antennas at each remote radio head (RRH). This thesis seeks to make three contributions. Firstly, it proposes a novel algorithm to solve the oscillatory/unstable behaviour of electronically steerable parasitic array radiators (ESPAR) when it provides multi-antenna functionality with a single RF chain. This thesis formulates an optimization problem and derives closed-form expressions when calculating the configuration of an ESPAR antenna (EA) for arbitrary signals transmission. This results in simplified processing at the transmitter. The results illustrate that the EA transmitter, when utilizing novel closed-form expressions, shows significant improvement over the performance of the EA transmitter without any pre-processing. It performs at nearly the same symbol error rate (SER) as standard multiple antenna systems. Secondly, this thesis illustrates how a practical peak power constraint can be put into an EA transceiver design. In an EA, all the antenna elements are fed centrally by a single power amplifier. This makes it more probable that during use, the power amplifier reaches maximum power during transmission. Considering limited power availability, this thesis proposes a new algorithm to achieve stable signal transmission. Thirdly, this thesis shows that an energy efficiency (EE) optimization problem can be formulated and solved in CRANs that deploy single RF chain antennas at RRHs. The closed-form expressions of the precoder and power allocation schemes to transmit desired signals are obtained to maximise EE for both single-user and multi-user systems. The results show that the CRANs with single RF chain antennas provide superior EE performance compared to the standard multiple antenna based systems.

To achieve a cost-effective network deployment, employing state-of-art technical advances provides a practical and effective way to enhance system performance and quality of service provisioning. Cooperative transmission has been recognized as one of the most effective paradigms to achieve higher system performance in terms of lower bit-error rate, higher throughput, larger coverage, more efficient energy utilization, and higher network reliability. This dissertation studies the location planning for the deployment of broadband access networks and explores the great potential of cooperative transmission in the context of single-cell cooperative relaying and multi-cell cooperative transmission, respectively. The placement problem is investigated in two categories of network deployment environment, i.e., an existing wireless access network and a perspective broadband access network, respectively. In an existing wireless access network, to solve some practical problems such as the requirements of capacity enhancement and coverage extension, relay stations (RSs) are introduced in the network architecture. We propose two optimization frameworks with the design objectives of maximizing cell capacity and minimizing number of RSs for deployment, respectively. Mathematical formulations are provided to precisely capture the characteristics of the placement problems. The corresponding solution algorithms are developed to obtain the optimal (or near-optimal) results in polynomial time. Numerical analysis and case studies are conducted to validate the performance benefits due to RS placement and the computation efficiency of the proposed algorithms. To deploy a new metropolitan-area broadband access network, we explore the integration of passive optical network (PON) and wireless cooperative networks (WCN) under the multi-cell cooperative transmission technology. An optimization framework is provided to solve the problem of dimensioning and site planning. The issues of node placement, BS-user association, wireless bandwidth and power breakdown assignment are jointly considered in a single stage to achieve better performance. We also propose a solution to the complex optimization problem based on decomposition and linear approximation. Numerical analysis and case studies are conducted to verify the proposed framework. The results demonstrate the performance gains and economic benefits. Given a set of network parameters, the proposed optimization frameworks and solutions proposed in this dissertation can provide design guidelines for practical network deployment and cost estimations. And the constructed broadband access networks show a more cost-effective deployment by taking advantage of the cooperative transmission technology.