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Resource Allocation and Energy Management in Green Network SystemsLiu, Jiashang 29 September 2020 (has links)
No description available.
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Enabling Dynamic Spectrum Access in 4G Networks and BeyondDeaton, Juan Diego 03 May 2012 (has links)
As early as 2014, mobile network operators' spectral capacity will be overwhelmed by the demand brought on by new devices and applications. To augment capacity and meet this demand, operators may choose to deploy a Dynamic Spectrum Access (DSA) overlay. Spectrum regulation is following suit, with regulators attempting to incorporate spectrum sharing through the design of spectrum access rules that support DSA. This dissertation explores the idea of DSA applied to Long Term Evolution Advanced (LTE+) networks. This idea is explored under functional, architectural, and spectrum policy aspects.
Under the functional and architectural aspects of this topic, the signaling and functionality required by such an overlay have not yet been fully considered in the architecture of an LTE+. This dissertation presents a Spectrum Accountability framework to be integrated into LTE+ MacroNet and HetNet architectures, defining specific element functionality, protocol interfaces, and signaling flow diagrams required to enforce the rights and responsibilities of primary and secondary users. We also identify and propose three DSA management frameworks for LTE+ HetNets: Spectrum Accountability Client Only, Cell Spectrum Management, and Domain Spectrum Management. Our Spectrum Accountability framework may serve as a guide in the development of future LTE+ network standards that account for DSA.
We also quantify, through simulation and integer programs, the benefits of using DSA channels to augment capacity under a scenario in which LTE+ network can opportunistically use TV and GSM spectrum. In our first experiment, we a consider a scenario where three different operators share the same cell site with LTE+ equipment and a Dynamic Spectrum Access (DSA) band to augment spectral capacity. Our experiments show that throughput can increase by as much as 40%. We develop integer programs to model the assignment of spectrum channels to both a MacroNet and HetNet. In our selected scenario, we observe TV white spectrum provides the largest gain in performance for both Nets: 27% for MacroNet and 9% increase for the HetNet over our measured ranges. Although the gains in using opportunistic use of GSM is more modest, 10% and 2% for the Macro and HetNet, respectively, we believe that these gains will significantly increase as operators continue to migrate users to LTE+, thus freeing up portions of the bands currently used for GSM service. In our final analytical model, we create integer program sets to represent the different three DSA management frameworks for LTE+ HetNets and compare their results.
Under the spectrum policy aspects, this dissertation develops a decision-theoretic framework for regulators to assess the impacts of different spectrum access rules on both primary and secondary operators. We analyze access rules based on sensing and exclusion areas, which in practice can be enforced through geolocation databases. Our results show that receiver-only sensing provides insufficient protection for primary and co-existing secondary users and overall low social welfare. On the other hand, combining sensing information of only the transmitter and receiver of a communication link provides dramatic increases in system performance. The performance of using these link end points is relatively close to that of using many cooperative sensing nodes associated to the same access point and large link exclusion areas. We hope these results will prove useful to regulators and network developers in un and developing rules for future DSA regulation. / Ph. D.
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Cellular-Assisted Vehicular Communications: A Stochastic Geometric ApproachGuha, Sayantan 04 February 2016 (has links)
A major component of future communication systems is vehicle-to-vehicle (V2V) communications, in which vehicles along roadways transfer information directly among themselves and with roadside infrastructure. Despite its numerous potential advantages, V2V communication suffers from one inherent shortcoming: the stochastic and time-varying nature of the node distributions in a vehicular ad hoc network (VANET) often leads to loss of connectivity and lower coverage. One possible way to improve this coverage is to allow the vehicular nodes to connect to the more reliable cellular network, especially in cases of loss of connectivity in the vehicular network. In this thesis, we analyze this possibility of boosting performance of VANETs, especially their node coverage, by taking assistance from the cellular network.
The spatial locations of the vehicular nodes in a VANET exhibit a unique characteristic: they always lie on roadways, which are predominantly linear but are irregularly placed on a two dimensional plane. While there has been a signifcant work on modeling wireless networks using random spatial models, most of it uses homogeneous planar Poisson Point Process (PPP) to maintain tractability, which is clearly not applicable to VANETs. Therefore, to accurately capture the spatial distribution of vehicles in a VANET, we model the roads using the so called Poisson Line Process and then place vehicles randomly on each road according to a one-dimensional homogeneous PPP. As is usually the case, the locations of the cellular base stations are modeled by a planar two-dimensional PPP. Therefore, in this thesis, we propose a new two-tier model for cellular-assisted VANETs, where the cellular base stations form a planar PPP and the vehicular nodes form a one-dimensional PPP on roads modeled as undirected lines according to a Poisson Line Process.
The key contribution of this thesis is the stochastic geometric analysis of a maximum power-based cellular-assisted VANET scheme, in which a vehicle receives information from either the nearest vehicle or the nearest cellular base station, based on the received power. We have characterized the network interference and obtained expressions for coverage probability in this cellular-assisted VANET, and successfully demonstrated that using this switching technique can provide a significant improvement in coverage and thus provide better vehicular network performance in the future. In addition, this thesis also analyzes two threshold-distance based schemes which trade off network coverage for a reduction in additional cellular network load; notably, these schemes also outperform traditional vehicular networks that do not use any cellular assistance. Thus, this thesis mathematically validates the possibility of improving VANET performance using cellular networks. / Master of Science
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Resource Management In Celluar And Mobile Opportunistic NetworksSingh, Chandramani Kishore 11 1900 (has links) (PDF)
In this thesis we study several resource management problems in two classes of wireless networks. The thesis is in two parts, the first being concerned with game theoretic approaches for cellular networks, and the second with control theoretic approaches for mobile opportunistic networks.
In Part I of the thesis, we first investigate optimal association and power control for the uplink of multichannel multicell cellular networks, in which each channel is used by exactly one base station (BS) (i.e., cell). Users have minimum signal to interference ratio(SINR) requirements and associate with BSs where least transmission powers are required. We formulate the problem as a non-cooperative game among users. We propose a distributed association and power update algorithm, and show its convergence to a Nash equilibrium of the game. We consider network models with discrete mobiles(yielding an atomic congestion game),as well as a continuum of mobiles(yielding a population game). We find that the equilibria need not be Pareto efficient, nor need they be system optimal. To address the lack of system optimality, we propose pricing mechanisms. We show that these prices weakly enforce system optimality in general, and strongly enforce it in special settings. We also show that these mechanisms can be implemented in distributed fashions.
Next, we consider the hierarchical problems of user association and BS placement, where BSs may belong to the same(or, cooperating) or to competing service providers. Users transmit with constant power, and associate with base stations that yield better SINRs. We formulate the association problem as a game among users; it determines the cell corresponding to each BS. Some intriguing observations we report are:(i)displacing a BS a little in one direction may result in a displacement of the boundary of the corresponding cell to the opposite direction;(ii)A cell corresponding to a BS may be the union of disconnected sub-cells. We then study the problem of the placement of BSs so as to maximize service providers’ revenues. The service providers need to take into account the mobiles’ behavior that will be induced by the placement decisions. We consider the cases of single frequency band and disjoint frequency bands of operation. We also consider the networks in which BSs employ successive interference cancellation(SIC) decoding. We observe that the BS locations are closer to each other in the competitive case than in the cooperative case, in all scenarios considered.
Finally, we study cooperation among cellular service providers. We consider networks in which communications involving different BSs do not interfere. If service providers jointly deploy and pool their resources, such as spectrum and BSs, and agree to serve each others’ customers, their aggregate payoff substantially increases. The potential of such cooperation can, however ,be realized only if the service providers intelligently determine who they would cooperate with, how they would deploy and share their resources, and how they would share the aggregate payoff. We first assume that the service providers can arbitrarily share the aggregate payoff. A rational basis for payoff sharing is imperative for the stability of the coalitions. We study cooperation using the theory of transferable payoff coalitional games. We show that the optimum cooperation strategy, which involves the acquisition of channels, and deployment and allocation of BSs to customers, is the solution of a concave or an integer optimization problem. We then show that the grand coalition is stable, i.e., if all the service providers cooperate, there is an operating point offering each service provider a share that eliminates the possibility of a subset of service providers splitting from the grand coalition; this operating point also maximizes the service providers’ aggregate payoff. These stabilizing payoff shares are computed by solving the dual of the above optimization problem. Moreover, the optimal cooperation strategy and the stabilizing payoff shares can be obtained in polynomial time using distributed computations and limited exchange of confidential information among the service providers. We then extend the analysis to the scenario where service providers may not be able to share their payoffs. We now model cooperation as a nontransferable payoff coalitional game. We again show that there exists a cooperation strategy that leaves no incentive for any subset of service providers to split from the grand coalition. To compute this cooperation strategy and the corresponding payoffs, we relate this game and its core to an exchange market and its equilibrium. Finally, we extend the formulations and the results to the case when customers are also decision makers in coalition formation.
In Part II of this thesis, we consider the problem of optimal message forwarding in mobile opportunistic wireless networks. A message originates at a node(source), and has to be delivered to another node (destination). In the network, there are several other nodes that can assist in relaying the message at the expense of additional transmission energies. We study the trade-off between delivery delay and energy consumption. First, we consider mobile opportunistic networks employing two-hop relaying. Because of the intermittent connectivity, the source may not have perfect knowledge of the delivery status at every instant. We formulate the problem as a stochastic control problem with partial information, and study structural properties of the optimal policy. We also propose a simple suboptimal policy. We then compare the performance of the suboptimal policy against that of the optimal control with perfect information. These are bounds on the performance of the proposed policy with partial information. We also discuss a few other related open loop policies.
Finally, we investigate the case where a message has to be delivered to several destinations, but we are concerned with delay until a certain fraction of them receive the message. The network employs epidemic relaying. We first assume that, at every instant, all the nodes know the number of relays carrying the packet and the number of destinations that have received the packet. We formulate the problem as a controlled continuous time Markov chain, and derive the optimal forwarding policy. As observed earlier, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we then obtain an ODE(i.e., a deterministic fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal deterministic policy. We evaluate the performance of this policy over finite networks, and demonstrate that this policy performs close to the optimal closed loop policy. We also briefly discuss the case where message forwarding is accomplished via two-hop relaying.
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Advanced interference management techniques for future wireless networksRazavi, Seyed Morteza January 2014 (has links)
In this thesis, we design advanced interference management techniques for future wireless networks under the availability of perfect and imperfect channel state information (CSI). We do so by considering a generalized imperfect CSI model where the variance of the channel estimation error depends on the signal-to-noise ratio (SNR). First, we analyze the performance of standard linear precoders, namely channel inversion (CI) and regularized CI (RCI), in downlink of cellular networks by deriving the received signal-to-interference-plus-noise ratio (SINR) of each user subject to both perfect and imperfect CSI. In this case, novel bounds on the asymptotic performance of linear precoders are derived, which determine howmuch accurate CSI should be to achieve a certain quality of service (QoS). By relying on the knowledge of error variance in advance, we propose an adaptive RCI technique to further improve the performance of standard RCI subject to CSI mismatch. We further consider transmit-power efficient design of wireless cellular networks. We propose two novel linear precoding techniques which can notably decrease the deployed power at transmit side in order to secure the same average output SINR at each user compared to standard linear precoders like CI and RCI. We also address a more sophisticated interference scenario, i.e., wireless interference networks, wherein each of the K transmitters communicates with its corresponding receiver while causing interference to the others. The most representative interference management technique in this case is interference alignment (IA). Unlike standard techniques like time division multiple access (TDMA) and frequency division multiple access (FDMA) where the achievable degrees of freedom (DoF) is one, with IA, the achievable DoF scales up with the number of users. Therefore, in this thesis, we quantify the asymptotic performance of IA under a generalized CSI mismatch model by deriving novel bounds on asymptotic mean loss in sum rate and the achievable DoF. We also propose novel least squares (LS) and minimum mean square error (MMSE) based IA techniques which are able to outperform standard IA schemes under perfect and imperfect CSI. Furthermore, we consider the implementation of IA in coordinated networks which enable us to decrease the number of deployed antennas in order to secure the same achievable DoF compared to standard IA techniques.
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FAULT-TOLERANT DISTRIBUTED CHANNEL ALLOCATION ALGORITHMS FOR CELLULAR NETWORKSYang, Jianchang 01 January 2006 (has links)
In cellular networks, channels should be allocated efficiently to support communication betweenmobile hosts. In addition, in cellular networks, base stations may fail. Therefore, designing a faulttolerantchannel allocation algorithm is important. That is, the algorithm should tolerate failuresof base stations. Many existing algorithms are neither fault-tolerant nor efficient in allocatingchannels.We propose channel allocation algorithms which are both fault-tolerant and efficient. In theproposed algorithms, to borrow a channel, a base station (or a cell) does not need to get channelusage information from all its interference neighbors. This makes the algorithms fault-tolerant,i.e., the algorithms can tolerate base station failures, and perform well in the presence of thesefailures.Channel pre-allocation has effect on the performance of a channel allocation algorithm. Thiseffect has not been studied quantitatively. We propose an adaptive channel allocation algorithmto study this effect. The algorithm allows a subset of channels to be pre-allocated to cells. Performanceevaluation indicates that a channel allocation algorithm benefits from pre-allocating allchannels to cells.Channel selection strategy also inuences the performance of a channel allocation algorithm.Given a set of channels to borrow, how a cell chooses a channel to borrow is called the channelselection problem. When choosing a channel to borrow, many algorithms proposed in the literaturedo not take into account the interference caused by borrowing the channel to the cells which havethe channel allocated to them. However, such interference should be considered; reducing suchinterference helps increase the reuse of the same channel, and hence improving channel utilization.We propose a channel selection algorithm taking such interference into account.Most channel allocation algorithms proposed in the literature are for traditional cellular networkswith static base stations and the neighborhood relationship among the base stations is fixed.Such algorithms are not applicable for cellular networks with mobile base stations. We proposea channel allocation algorithm for cellular networks with mobile base stations. The proposedalgorithm is both fault-tolerant and reuses channels efficiently.KEYWORDS: distributed channel allocation, resource planning, fault-tolerance, cellular networks,3-cell cluster model.
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Queueing models for capacity changes in cellular networks2013 December 1900 (has links)
With the rapid development of cellular communication techniques, many recent studies have focused on improving the quality of service (QoS) in cellular networks. One characteristic of the systems in cellular networks, which can have direct impact on the system QoS, is the fluctuation of the system capacity. In this thesis, the QoS of systems with capacity fluctuations is studied from two perspectives: (1) priority queueing systems with preemption, and (2) the M/M/~C/~C system.
In the first part, we propose two models with controlled preemption and analyze their performance in the context of a single reference cell that supports two kinds of traffic (new calls and handoff calls). The formulae for calculating the performance measures of interest (i.e., handoff call blocking probability, new call blocking and dropping probabilities) are developed, and the procedures for solving optimization problems for the optimal number of channels required for each proposed model are established. The proposed controlled preemption models are then compared to existing non-preemption and full preemption models from the following three perspectives: (i) channel utilization, (ii) low priority call (i.e., new calls) performance, and (iii) flexibility to meet various constraints. The results showed that the proposed controlled preemption models are the best models overall.
In the second part, the loss system with stochastic capacity, denoted by M/M/~C/~C, is analyzed using the Markov regenerative process (MRGP) method. Three different distributions of capacity interchange times (exponential, gamma, and Pareto) and three different capacity variation patterns (skip-free, distance-based, and uniform-based) are considered. Analytic expressions are derived to calculate call blocking and dropping probabilities and are verified by call level simulations. Finally, numerical examples are provided to determine the impact of different distributions of capacity interchange times and different capacity variation patterns on system performance.
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Models and optimisation methods for interference coordination in self-organising cellular networksLopez-Perez, David January 2011 (has links)
We are at that moment of network evolution when we have realised that our telecommunication systems should mimic features of human kind, e.g., the ability to understand the medium and take advantage of its changes. Looking towards the future, the mobile industry envisions the use of fully automatised cells able to self-organise all their parameters and procedures. A fully self-organised network is the one that is able to avoid human involvement and react to the fluctuations of network, traffic and channel through the automatic/autonomous nature of its functioning. Nowadays, the mobile community is far from this fully self-organised kind of network, but they are taken the first steps to achieve this target in the near future. This thesis hopes to contribute to the automatisation of cellular networks, providing models and tools to understand the behaviour of these networks, and algorithms and optimisation approaches to enhance their performance. This work focuses on the next generation of cellular networks, in more detail, in the DownLink (DL) of Orthogonal Frequency Division Multiple Access (OFDMA) based networks. Within this type of cellular system, attention is paid to interference mitigation in self-organising macrocell scenarios and femtocell deployments. Moreover, this thesis investigates the interference issues that arise when these two cell types are jointly deployed, complementing each other in what is currently known as a two-tier network. This thesis also provides new practical approaches to the inter-cell interference problem in both macro cell and femtocell OFDMA systems as well as in two-tier networks by means of the design of a novel framework and the use of mathematical optimisation. Special attention is paid to the formulation of optimisation problems and the development of well-performing solving methods (accurate and fast).
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Power allocation and cell association in cellular networksHo, Danh Huu 26 August 2019 (has links)
In this dissertation, power allocation approaches considering path loss, shadowing,
and Rayleigh and Nakagami-m fading are proposed. The goal is to improve power
consumption, and energy and throughput efficiency based on user target signal to interference plus noise ratio (SINR) requirements and an outage probability threshold.
First, using the moment generating function (MGF), the exact outage probability
over Rayleigh and Nakagami-m fading channels is derived. Then upper and lower
bounds on the outage probability are derived using the Weierstrass, Bernoulli and
exponential inequalities. Second, the problem of minimizing the user power subject
to outage probability and user target SINR constraints is considered. The corresponding power allocation problems are solved using Perron-Frobenius theory and
geometric programming (GP). A GP problem can be transformed into a nonlinear
convex optimization problem using variable substitution and then solved globally and
efficiently by interior point methods. Then, power allocation problems for throughput
maximization and energy efficiency are proposed. As these problems are in a convex
fractional programming form, parametric transformation is used to convert the original problems into subtractive optimization problems which can be solved iteratively.
Simulation results are presented which show that the proposed approaches are better
than existing schemes in terms of power consumption, throughput, energy efficiency
and outage probability.
Prioritized cell association and power allocation (CAPA) to solve the load balancing issue in heterogeneous networks (HetNets) is also considered in this dissertation.
A Hetnet is a group of macrocell base stations (MBSs) underlaid by a diverse set
of small cell base stations (SBSs) such as microcells, picocells and femtocells. These
networks are considered to be a good solution to enhance network capacity, improve
network coverage, and reduce power consumption. However, HetNets are limited
by the disparity of power levels in the different tiers. Conventional cell association
approaches cause MBS overloading, SBS underutilization, excessive user interference
and wasted resources. Satisfying priority user (PU) requirements while maximizing
the number of normal users (NUs) has not been considered in existing power allocation algorithms. Two stage CAPA optimization is proposed to address the prioritized
cell association and power allocation problem. The first stage is employed by PUs
and NUs and the second stage is employed by BSs. First, the product of the channel
access likelihood (CAL) and channel gain to interference plus noise ratio (GINR) is considered for PU cell association while network utility is considered for NU cell association. Here, CAL is defined as the reciprocal of the BS load. In CAL and GINR
cell association, PUs are associated with the BSs that provide the maximum product
of CAL and GINR. This implies that PUs connect to BSs with a low number of users
and good channel conditions. NUs are connected to BSs so that the network utility
is maximized, and this is achieved using an iterative algorithm. Second, prioritized
power allocation is used to reduce power consumption and satisfy as many NUs with
their target SINRs as possible while ensuring that PU requirements are satisfied.
Performance results are presented which show that the proposed schemes provide fair
and efficient solutions which reduce power consumption and have faster convergence
than conventional CAPA schemes. / Graduate
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Joint spatial and spectrum cooperation in wireless networkDeng, Yansha January 2015 (has links)
The sky-rocketing growth of multimedia infotainment applications and broadband-hungry mobile devices exacerbate the stringent demand for ultra high data rate and more spectrum resources. Along with it, the unbalanced temporal and geographical variations of spectrum usage further inspires those spectral-efficient networks, namely, cognitive radio and heterogeneous cellular networks (HCNs). This thesis focuses on the system design and performance enhancement of cognitive radio (CR) and HCNs. Three different aspects of performance improvement are considered, including link reliability of cognitive radio networks (CNs), security enhancement of CNs, and energy efficiency improvement of CNs and HCNs. First, generalized selection combining (GSC) is proposed as an effective receiver design for interference reduction and reliability improvement of CNs with outdated CSI. A uni- ed way for deriving the distribution of received signal-to-noise ratio (SNR) is developed in underlay spectrum sharing networks subject to interference from the primary trans- mitter (PU-Tx) to the secondary receiver (SU-Rx), maximum transmit power constraint at the secondary transmitter (SU-Tx), and peak interference power constraint at the PU receiver (PU-Rx), is developed. Second, transmit antenna selection with receive generalized selection combining (TAS/GSC) in multi-antenna relay-aided communica- tion is introduced in CNs under Rayleigh fading and Nakagami-m fading. Based on newly derived complex statistical properties of channel power gain of TAS/GSC, exact ergodic capacity and high SNR ergodic capacity are derived over Nakagami-m fading. Third, beamforming and arti cial noise generation (BF&AN) is introduced as a robust scheme to enhance the secure transmission of large-scale spectrum sharing networks with multiple randomly located eavesdroppers (Eves) modeled as homogeneous Poisson Point Process (PPP). Stochastic geometry is applied to model and analyze the impact of i BF&AN on this complex network. Optimal power allocation factor for BF&AN which maximizes the average secrecy rate is further studied under the outage probability con- straint of primary network. Fourth, a new wireless energy harvesting protocol is proposed for underlay cognitive relay networks with the energy-constrained SU-Txs. Exact and asymptotic outage probability, delay-sensitive throughput, and delay-tolerant through- put are derived to explore the tradeoff between the energy harvested from the PU-Txs and the interference caused by the PU-Txs. Fifth, a harvest-then-transmit protocol is proposed in K-tier HCNs with randomly located multiple-antenna base stations (BSs) and single antenna mobile terminals (MTs) modeled as homogeneous PPP. The average received power at MT, the uplink (UL) outage probability, and the UL average ergodic rate are derived to demonstrate the intrinsic relationship between the energy harvested from BSs in the downlink (DL) and the MT performance in the UL. Throughout the thesis, it is shown that link reliability, secrecy performance, and energy efficiency of CNs and HCNs can be signi cantly leveraged by taking advantage of multiple antennas, relays, and wireless energy harvesting.
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