Intelligent Processing in Wireless Communications Using Particle Swarm Based Methods

There are a lot of optimization needs in the research and design of wireless communica- tion systems. Many of these optimization problems are Nondeterministic Polynomial (NP) hard problems and could not be solved well. Many of other non-NP-hard optimization problems are combinatorial and do not have satisfying solutions either. This dissertation presents a series of Particle Swarm Optimization (PSO) based search and optimization algorithms that solve open research and design problems in wireless communications. These problems are either avoided or solved approximately before. PSO is a bottom-up approach for optimization problems. It imposes no conditions on the underlying problem. Its simple formulation makes it easy to implement, apply, extend and hybridize. The algorithm uses simple operators like adders, and multipliers to travel through the search space and the process requires just five simple steps. PSO is also easy to control because it has limited number of parameters and is less sensitive to parameters than other swarm intelligence algorithms. It is not dependent on initial points and converges very fast. Four types of PSO based approaches are proposed targeting four different kinds of problems in wireless communications. First, we use binary PSO and continuous PSO together to find optimal compositions of Gaussian derivative pulses to form several UWB pulses that not only comply with the FCC spectrum mask, but also best exploit the avail- able spectrum and power. Second, three different PSO based algorithms are developed to solve the NLOS/LOS channel differentiation, NLOS range error mitigation and multilateration problems respectively. Third, a PSO based search method is proposed to find optimal orthogonal code sets to reduce the inter carrier interference effects in an frequency redundant OFDM system. Fourth, a PSO based phase optimization technique is proposed in reducing the PAPR of an frequency redundant OFDM system. The PSO based approaches are compared with other canonical solutions for these communication problems and showed superior performance in many aspects. which are confirmed by analysis and simulation results provided respectively. Open questions and future Open questions and future works for the dissertation are proposed to serve as a guide for the future research efforts

Adaptive Communications for Next Generation Broadband Wireless Access Systems

Un dels aspectes claus en el disseny i gestió de les xarxes sense fils d'accés de banda ampla és l'ús eficient dels recursos radio. Des del punt de vista de l'operador, l'ample de banda és un bé escàs i preuat que s´ha d'explotar i gestionar de la forma més eficient possible tot garantint la qualitat del servei que es vol proporcionar. Per altra banda, des del punt de vista del usuari, la qualitat del servei ofert ha de ser comparable al de les xarxes fixes, requerint així un baix retard i una baixa pèrdua de paquets per cadascun dels fluxos de dades entre la xarxa i l'usuari. Durant els darrers anys s´han desenvolupat nombroses tècniques i algoritmes amb l'objectiu d'incrementar l'eficiència espectral. Entre aquestes tècniques destaca l'ús de múltiples antenes al transmissor i al receptor amb l'objectiu de transmetre diferents fluxos de dades simultaneament sense necessitat d'augmentar l'ample de banda. Per altra banda, la optimizació conjunta de la capa d'accés al medi i la capa física (fent ús de l'estat del canal per tal de gestionar de manera optima els recursos) també permet incrementar sensiblement l'eficiència espectral del sistema.L'objectiu d'aquesta tesi és l'estudi i desenvolupament de noves tècniques d'adaptació de l'enllaç i gestió dels recursos ràdio aplicades sobre sistemes d'accés ràdio de propera generació (Beyond 3G). Els estudis realitzats parteixen de la premissa que el transmisor coneix (parcialment) l'estat del canal i que la transmissió es realitza fent servir un esquema multiportadora amb múltiples antenes al transmisor i al receptor. En aquesta tesi es presenten dues línies d'investigació, la primera per casos d'una sola antenna a cada banda de l'enllaç, i la segona en cas de múltiples antenes. En el cas d'una sola antena al transmissor i al receptor, un nou esquema d'assignació de recursos ràdio i priorització dels paquets (scheduling) és proposat i analitzat integrant totes dues funcions sobre una mateixa entitat (cross-layer). L'esquema proposat té com a principal característica la seva baixa complexitat i que permet operar amb transmissions multimedia. Alhora, posteriors millores realitzades per l'autor sobre l'esquema proposat han permès també reduir els requeriments de senyalització i combinar de forma óptima usuaris d'alta i baixa mobilitat sobre el mateix accés ràdio, millorant encara més l'eficiència espectral del sistema. En cas d'enllaços amb múltiples antenes es proposa un nou esquema que combina la selecció del conjunt optim d'antenes transmissores amb la selecció de la codificació espai- (frequència-) temps. Finalment es donen una sèrie de recomanacions per tal de combinar totes dues línies d'investigació, així con un estat de l'art de les tècniques proposades per altres autors que combinen en part la gestió dels recursos ràdio i els esquemes de transmissió amb múltiples antenes.Uno de los aspectos claves en el diseño y gestión de las redes inalámbricas de banda ancha es el uso eficiente de los recursos radio. Desde el punto de vista del operador, el ancho de banda es un bien escaso y valioso que se debe explotar y gestionar de la forma más eficiente posible sin afectar a la calidad del servicio ofrecido. Por otro lado, desde el punto de vista del usuario, la calidad del servicio ha de ser comparable al ofrecido por las redes fijas, requiriendo así un bajo retardo y una baja tasa de perdida de paquetes para cada uno de los flujos de datos entre la red y el usuario. Durante los últimos años el número de técnicas y algoritmos que tratan de incrementar la eficiencia espectral en dichas redes es bastante amplio. Entre estas técnicas destaca el uso de múltiples antenas en el transmisor y en el receptor con el objetivo de poder transmitir simultáneamente diferentes flujos de datos sin necesidad de incrementar el ancho de banda. Por otro lado, la optimización conjunta de la capa de acceso al medio y la capa física (utilizando información de estado del canal para gestionar de manera óptima los recursos) también permite incrementar sensiblemente la eficiencia espectral del sistema.El objetivo de esta tesis es el estudio y desarrollo de nuevas técnicas de adaptación del enlace y la gestión de los recursos radio, y su posterior aplicación sobre los sistemas de acceso radio de próxima generación (Beyond 3G). Los estudios realizados parten de la premisa de que el transmisor conoce (parcialmente) el estado del canal a la vez que se considera que la transmisión se realiza sobre un sistema de transmisión multiportadora con múltiple antenas en el transmisor y el receptor. La tesis se centra sobre dos líneas de investigación, la primera para casos de una única antena en cada lado del enlace, y la segunda en caso de múltiples antenas en cada lado. Para el caso de una única antena en el transmisor y en el receptor, se ha desarrollado un nuevo esquema de asignación de los recursos radio así como de priorización de los paquetes de datos (scheduling) integrando ambas funciones sobre una misma entidad (cross-layer). El esquema propuesto tiene como principal característica su bajo coste computacional a la vez que se puede aplicar en caso de transmisiones multimedia. Posteriores mejoras realizadas por el autor sobre el esquema propuesto han permitido también reducir los requisitos de señalización así como combinar de forma óptima usuarios de alta y baja movilidad. Por otro lado, en caso de enlaces con múltiples antenas en transmisión y recepción, se presenta un nuevo esquema de adaptación en el cual se combina la selección de la(s) antena(s) transmisora(s) con la selección del esquema de codificación espacio-(frecuencia-) tiempo. Para finalizar, se dan una serie de recomendaciones con el objetivo de combinar ambas líneas de investigación, así como un estado del arte de las técnicas propuestas por otros autores que combinan en parte la gestión de los recursos radio y los esquemas de transmisión con múltiples antenas.In Broadband Wireless Access systems the efficient use of the resources is crucial from many points of views. From the operator point of view, the bandwidth is a scarce, valuable, and expensive resource which must be exploited in an efficient manner while the Quality of Service (QoS) provided to the users is guaranteed. On the other hand, a tight delay and link quality constraints are imposed on each data flow hence the user experiences the same quality as in fixed networks. During the last few years many techniques have been developed in order to increase the spectral efficiency and the throughput. Among them, the use of multiple antennas at the transmitter and the receiver (exploiting spatial multiplexing) with the joint optimization of the medium access control layer and the physical layer parameters.In this Ph.D. thesis, different adaptive techniques for B3G multicarrier wireless systems are developed and proposed focusing on the SS-MC-MA and the OFDM(A) (IEEE 802.16a/e/m standards) communication schemes. The research lines emphasize into the adaptation of the transmission having (Partial) knowledge of the Channel State Information for both; single antenna and multiple antenna links. For single antenna links, the implementation of a joint resource allocation and scheduling strategy by including adaptive modulation and coding is investigated. A low complexity resource allocation and scheduling algorithm is proposed with the objective to cope with real- and/or non-real- time requirements and constraints. A special attention is also devoted in reducing the required signalling. However, for multiple antenna links, the performance of a proposed adaptive transmit antenna selection scheme jointly with space-time block coding selection is investigated and compared with conventional structures. In this research line, mainly two optimizations criteria are proposed for spatial link adaptation, one based on the minimum error rate for fixed throughput, and the second focused on the maximisation of the rate for fixed error rate. Finally, some indications are given on how to include the spatial adaptation into the investigated and proposed resource allocation and scheduling process developed for single antenna transmission

Resource Allocation and Service Management in Next Generation 5G Wireless Networks

The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond

Efficient radio resource management for future generation heterogeneous wireless networks

The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments

Traffic-Driven Energy Efficient Operational Mechanisms in Cellular Access Networks

Recent explosive growth in mobile data traffic is increasing energy consumption in cellular networks at an incredible rate. Moreover, as a direct result of the conventional static network provisioning approach, a significant amount of electrical energy is being wasted in the existing networks. Therefore, in recent time, the issue of designing energy efficient cellular networks has drawn significant attention, which is also the foremost motivation behind this research. The proposed research is particularly focused on the design of self-organizing type traffic-sensitive dynamic network reconfiguring mechanisms for energy efficiency in cellular systems. Under the proposed techniques, radio access networks (RANs) are adaptively reconfigured using less equipment leading to reduced energy utilization. Several energy efficient cellular network frameworks by employing inter-base station (BS) cooperation in RANs are proposed. Under these frameworks, based on the instantaneous traffic demand, BSs are dynamically switched between active and sleep modes by redistributing traffic among them and thus, energy savings is achieved. The focus is then extended to exploiting the availability of multiple cellular networks for extracting energy savings through inter-RAN cooperation. Mathematical models for both of these single-RAN and multi-RAN cooperation mechanisms are also formulated. An alternative energy saving technique using dynamic sectorization (DS) under which some of the sectors in the underutilized BSs are turned into sleep mode is also proposed. Algorithms for both the distributed and the centralized implementations are developed. Finally, a two-dimensional energy efficient network provisioning mechanism is proposed by jointly applying both the DS and the dynamic BS switching. Extensive simulations are carried out, which demonstrate the capability of the proposed mechanisms in substantially enhancing the energy efficiency of cellular networks

Interference mitigation in cognitive femtocell networks

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.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)