Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Major Telecomunicações). Faculdade de Engenharia. Universidade do Porto. 2009

Most of the cellular tra c (voice and data) is generated indoors. Due to attenuation from walls, quality of service (QoS) of di erent applications degrades for indoor tra c. Thus in order to provide QoS for such users the Macro base station (MBS) has to transmit at high power. This increases recurring costs to the service provider and contributes to green house emissions. Hence, Femtocells (FC) are considered as an option. Femto Access Points (FAP) are low cost, low powered, small base stations deployed indoors by customers. A substantial part of indoor tra c is diverted from the Macrocell (MC) through the FAP. Since the FCs also use the same channels as the MC, deployment of FCs causes interference to not only its neighbouring FCs but also to the users in the MC. Thus, we need better interference management techniques for this system. In this thesis, we consider a system with multiple Femtocells operating in a Macrocell. FCs and MC use same set of multiple channels and support multiple users. Each user may have a minimum rate requirement. To limit interference to the MC, there is a peak power constraint on each channel. In the rst part of the thesis, we consider sparsely deployed FCs where the interference between the FCs is negligible. For this we formulate the problem of channel allocation and power control in each FC. We develop computationally e cient, suboptimal algorithms to satisfy QoS of each user in the FC. If QoS of each user is not satis ed, we provide solutions which are fair to all the users. In the second part of the thesis, we consider the case of densely deployed FCs where we formulate the problem of channel allocation and power control in each Femtocell as a noncooperative Game. We develop e cient decentralized algorithms to obtain a Nash equilibrium (NE) at which QoS of each user is satis ed. We also obtain e cient decentralized algorithms to obtain fair NE when it may not be feasible to satisfy the QoS of all the users in the FC. Finally, we extend our algorithms to the case where there may be voice and data users in the system. In the third part of the thesis, we continue to study the problem setup in the second part, where we develop algorithms which can simultaneously consider the cases where QoS of users can be satis ed or not. We provide algorithms to compute Coarse Correlated Equilibrium (CCE), Pareto optimal points and Nash bargaining solutions. In the nal part of the thesis, we consider interference limit at the MBS and model FCs as sel sh nodes. The MBS protects itself via pricing subchannels per usage. We obtain a Stackelberg equilibrium (SE) by considering MBS as a leader and FCs as followers.

The cellular industry is undergoing a major paradigm shift from voice-centric, structured homogeneous networks to a more data-driven, distributed and heterogeneous architecture. One of the more promising trends emerging from this cellular revolution is femtocells. Femtocells are primarily viewed as a cost-effective way to improve both capacity and indoor coverage, and they enable offloading data-traffic from macrocell network. However, efficient interference management in co-channel deployment of femtocells remains a challenge. Decentralized strategies such as femtocell access control have been identified as an effective means to mitigate cross-tier interference in two-tier networks. Femtocells can be configured to be either open access or closed access. Prior work on access control schemes show that, in the absence of any coordination between the two tiers in terms of power control and user scheduling, closed access is the preferred approach at high user densities. Present methods suggest that in the case of orthogonal multiple access schemes like TDMA/OFDMA, femtocell access control should be adaptive according to the estimated cellular user density. The approach we follow, in this work, is to adopt an open access policy at the femtocell access points with a cap on the maximum number of users allowed on a femtocell. This ensures the femto owner retains a significant portion of the femtocell resources. We design an iterative algorithm for hybrid access control for femtocells that integrates the problems of uplink power control and base station assignment. This algorithm implicitly adapts the femtocell access method to the current user density. The distributed power control algorithm, which is based on Yates' work on standard interference functions, enables users to overcome the interference in the system and satisfy their minimum QoS requirements. The optimal allocation of femtocell resources is incorporated into the access control algorithm through a constrained sum-rate maximization to protect the femto owner from starvation at high user densities. The performance of a two-tier OFDMA femtocell network is then evaluated under the proposed access scheme from a home owner viewpoint, and network operator perspective. System-level simulations show that the proposed access control method can provide a rate gain of nearly 52% for cellular users, compared to closed access, at high user densities and under moderate-to-dense deployment of femtocells. At the same time, the femto owner is prevented from going into outage and only experiences a negligible rate loss. The results obtained establish the quantitative performance advantage of using hybrid access at femtocells with power control at high user densities. The convergence properties of the proposed iterative hybrid access control algorithm are also investigated by varying the user density and the mean number of femto access points in the network. It is shown that for a given system model, the algorithm converges quickly within thirty iterations, provided a feasible solution exists.

Thesis (M.S.E.C.E.)--University of Delaware, 2009. / Principal faculty advisor: Leonard J. Cimini, Jr., Dept. of Electrical & Computer Engineering. Includes bibliographical references.

Placing smaller cells in a heterogeneous cellular network can be beneficial in terms of energy because better capacities can be obtained for a given energy constraint. These type of deployments not only highlight the need for appropriate metrics to evaluate how well energy is being spent, but also raise important issues that need to be taken into account when analysing the overall use of energy. In this work, handoff strategies, bandwidth allocation, and path loss models in different scenarios, illustrate how energy can be consumed in a more efficient way when cell size is decreased. A handoff strategy based on per-energy capacity is studied in order to give priority to a more energy efficient handoff option. Energy can also be spent more adequately if the transmit power is adjusted as a function of interference. As a result, users can experience higher capacities while spending less energy, depending whether they handoff or not, increasing the overall performance of the network in terms of energy efficiency.

Two-tier macrocell-femtocell network is considered an efficient solution to enhance area spectral-efficiency, improve cell coverage and provide better quality-of-service (QoS) to mobile users. However, interference and mobility management are considered to be the major issues for successful deployment of macrocell-femtocell network. In this thesis, a unified framework is developed for interference management, resource allocation, and call admission control (CAC) for two-tier macrocell-femtocell network. Fractional frequency reuse (FFR) is considered to provide both link-level and call-level QoS measures for mobile users. In this framework, joint resource allocation and interference coordination problem is formulated as an optimization problem to obtain design parameters for sectored FFR. The CAC problem is formulated as Semi-Markov Decision Process and Value Iteration Algorithm is used to obtain optimal admission control policy. Performance of this framework is evaluated through simulations. The performance evaluation results show that the proposed framework outperforms traditional non-optimized FFR scheme in two-tier network.

Two-tier macrocell-femtocell network is considered an efficient solution to enhance area spectral-efficiency, improve cell coverage and provide better quality-of-service (QoS) to mobile users. However, interference and mobility management are considered to be the major issues for successful deployment of macrocell-femtocell network. In this thesis, a unified framework is developed for interference management, resource allocation, and call admission control (CAC) for two-tier macrocell-femtocell network. Fractional frequency reuse (FFR) is considered to provide both link-level and call-level QoS measures for mobile users. In this framework, joint resource allocation and interference coordination problem is formulated as an optimization problem to obtain design parameters for sectored FFR. The CAC problem is formulated as Semi-Markov Decision Process and Value Iteration Algorithm is used to obtain optimal admission control policy. Performance of this framework is evaluated through simulations. The performance evaluation results show that the proposed framework outperforms traditional non-optimized FFR scheme in two-tier network.

The architecture of cellular networks has been undergoing an extraordinarily fast evolution in the last years to keep up with the ever increasing user demands for wireless data and services. Motivated by a search for a breakthrough in network capacity, the paradigm of heterogeneous networks (HetNets) has become prominent in modern cellular systems, where carefully deployed macrocells coexist with layers of irregularly deployed cells of reduced coverage sizes. Users can thus be offloaded from the macrocell and the capacity of the network increases. However, universal frequency reuse is usually employed to maximize capacity gains, thereby introducing the fundamental problem of inter-cell interference (ICI) in the network caused by the sharing of the spectrum among the different tiers of the HetNet. The objective of this PhD thesis is to provide analysis and mitigation techniques for the fundamental problem of interference in heterogeneous cellular networks. First, the interference of a two-tier network is modeled and analyzed by making use of spatial statistics tools that allow the reconstruction of complete coverage maps. A correlation analysis is then performed by deriving a spatial coverage cross-tier correlation function. Second, a novel architecture design is proposed to minimize interference in HetNets whose base stations may be equipped with very large antenna arrays, another key technology of future wireless systems. Then, we present interference mitigation techniques for different types of small cells, namely picocells and femtocells. In the third contribution of this thesis, we analyze the case of clustered deployments by proposing and comparing techniques suitable for this scenario. Fourth, we tackle the case of femtocell deployments by analyzing the degrading effect of interference and proposing new mitigation methods. Fifth, we introduce femtorelays, a novel small cell access technology that combats interference in femtocell networks and provides higher backhaul capacity.

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).

Dense deployment of small base stations (SBSs) brings new challenges such as growing energy consumption, increased carbon footprint, higher inter-cell interference, and complications in handover management. These challenges can be dealt with by taking advantage of sleep/idle mode capabilities of SBSs, and exploiting the delay tolerance of data applications, as well as utilizing information derived from the statistical distributions of SBSs and user equipment (UE)-SBS associations. This dissertation focuses on the formulation of mathematical models and proposes energy efficient algorithms for small cell networks (SCN). It is shown that delay tolerance of some data applications can be taken advantage of to save energy in SCN. This dissertation introduces practical models to study the performance of delayed access to SCNs. Operational states of SBS are modeled as a Markov chain and their probability distributions are analyzed. Also, it argues that SCN can be operated to save energy during low traffic periods by taking advantage of user equipments' (UEs) delay tolerance in SCN while providing high access probability within bounded transmission range. Dense deployment of SCNs cause an increase in overlapping SBS coverage areas, allowing UEs to establish communication with multiple SBSs. A new load metric as a function of the number of SBSs in UE's communication range is defined, and its statistics are rigorously analyzed. Energy saving algorithms based on aforementioned load metric are developed and their efficiencies are compared. Besides, UE's delay tolerance allows establishing communication with close-by SBSs that are either in fully active mode or in sleeping mode. Improvements in coverage probability and bitrate are analyzed by considering different delay tolerance values for UEs. Key parameters such as UE's communication range are optimized with respect to SBS density and delay tolerance. The fundamental problem of local versus remote edge/fog computing and its inherent tradeoffs are studied from a queuing perspective taking into account user/SBS density, server capacity and latency constraints. The task offloading problem is cast as an M/M/1(c) queue in which CPU intensive tasks arrive according to Poisson process and receive service subject to a tolerable delay. The higher the proportion of locally computed tasks, the less traffic SCN handles between edge processor and UE. Therefore, low utilization of SCN can be interperted as increased spectral efficiency due to low interference and close UE-SBS distance. Tradeoff between delay dependent SCN utilization and spectral efficiency is evaluated at high and low traffic loads.