认知无线网络中导频信道设计和自组织关键技术研究
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摘要
随着工作、学习和生活节奏的日益加快,人们对能够提供丰富应用体验、无处不在的高性能无线通信网络的需求与日俱增。在不同地区和国家已经形成了多种无线接入技术共存的局面,使得无线网络发展趋于异构化,也使得异构网络之间的资源管控变得更加复杂,同时也对异构网络之间的互融与互通提出了新的挑战。无线电频谱资源的紧缺性同业务需求不断增长之间的矛盾也日趋激烈,如何提高频谱资源的利用效率已成为亟待解决的重要问题之一。此外,无线网络的异构化和复杂化也对传统以人工为主的网络规划、设计、管理和维护提出了新的挑战,如何增强无线网络设计、管理与维护的自主化,从而降低网络管控的复杂度并减少网络运营维护的成本,实现网络的自动配置、自动优化、自主管理和自动维护,己成为工程实践中关注的热点问题。
面对无线网络异构融合的新趋势、业务宽带化和多样化的新需求、频谱利用效率和网络容量进一步提升的新目标,已有的静态频谱管理方式和传统以人工为主的网络规划与优化手段无法满足无线网络环境复杂多变和无线业务需求不断增长的新趋势。所以,未来无线网络发展所面临的挑战可归结为：支持异构网络融合的信息有效互通新方法挑战、降低网络资源管控复杂度新技术挑战、提升网络频谱利用效率和网络容量新技术挑战等。
针对未来无线网络发展所面临的新需求和新挑战,具有无线网络认知性、异构网络适变性和网络管控自主性的认知无线网络技术应运而生。认知无线网络能够通过对网络环境的认知,进行智能的决策,通过参数、协议和网络模式的重构实现对无线网络环境变化的自主适变,并通过自主学习实现网络自主适变的智能化。同时,认知无线网络技术还可以有效支持异构网络融合、降低异构网络资源管控的复杂度,达到频谱利用效率提升、网络容量提高和网络覆盖优化等目标。因此,本文重点针对未来无线网络面临的异构网络信息互通不畅、资源管控复杂化、频谱利用效率低下和网络容量有待提高等问题与挑战展开深入研究,提出基于认知导频信道技术进行异构网络信息准确、高效传输方案,并基于此进行自组织网络技术方案的优化设计,以实现降低网络管控复杂度、提高频谱利用效率、提高网络容量、优化网络覆盖的目标。已在相关领域取得理论和技术创新成果。归纳来说,本文研究的内容主要包括以下四个部分：
第一部分,首先阐述未来无线网络发展趋势和面临的两大挑战：无线网络异构化和资源管控复杂化。其次,通过对认知无线网络技术的起源和关键技术的分析,提出采用认知导频信道技术可以有效异构网络之间信息互通的问题,并提出采用自组织网络技术可以有效降低异构网络资源管控的复杂度、提升网络性能。最后,通过认知无线网络中认知导频信道技术和自组织网络技术研究现状的全面分析,明确本文的研究重点在于认知导频信道的优化设计、并基于此进行认知无线网络中自组织方案设计,两方面研究内容相互关联、层层递进。
第二部分,针对异构网络信息有效互通的挑战,本文提出了支持异构网络信息准确和有效传输的认知导频信道理论及关键技术,包括两个创新点。第一,首先,基于已有认知导频信道技术中带外和带内两种部署方式的优点和不足进行比较分析。其次,明确影响异构网络信息准确传输的两大关键因素：终端定位偏移误差因素和栅格划分尺寸因素。针对终端定位偏移误差下的信息错误概率和信息丢失率进行理论建模并通过数学推导获得闭式解。然后,分析栅格划分尺寸大小对异构网络信息准确传输的影响,提出基于层次分析法和灰度关联分析理论的认知导频信道最优栅格划分准则和方案,实现基于认知导频信道的异构网络信息准确传输的目标,填补了本领域理论研究的空白。第二,首先,分析认知导频信道广播和点播两种典型发送方式的优点和不足,明确影响认知导频信道发送效率的关键因素。其次,针对邻近栅格中网络信息存在冗余的问题,提出差异量化的栅格信息编码理论,以提高异构网络信息的编码效率。然后,通过设计基于相同性质栅格信息的群组化改进广播方案,进一步提升异构网络信息发送的效率。总之,第二部分通过基于栅格最优划分准则、栅格信息差异量化编码、同性质栅格群组化发送等认知导频信道改进方案的设计,实现了异构网络信息准确、高效的传输,并为认知无线网络资源管控和有效利用的决策与执行提供了必要的信息有效传输技术手段。
第三部分,针对异构网络资源管控复杂化挑战、频谱利用效率和网络容量提升的新需求,本文重点针对具有容量提升、覆盖优化、自主管控特性的新型家庭基站网络技术和认知协作中继网络技术展开深入研究,分别提出具有自组织功能的家庭基站网络频率自部署、覆盖自优化理论与技术、认知协作中继网络容量自优化理论与技术,包括三个创新点。第一,首先,运用理论分析和数学推导相结合的方法重点研究不同频率部署方式(异频、同频和混频)对家庭基站与宏蜂窝网络共存下层叠网络的下行容量的影响因素,并通过数学建模进行量化表征。其次,研究基于地理位置信息的宏蜂窝基站频谱占用信息的主动认知方法,并设计基于认知导频信道的层叠网络信息有效传输方案,实现层叠网络内频谱占用信息的有效互通。然后,研究基于最优地理区域划分的家庭基站频率自部署理论及技术,降低层叠网络的干扰,从而提高层叠网络下行容量的目标。第二,首先,依据理论模型的定量分析结果,明确采用静态和动态功率分配两种方案对家庭基站覆盖优化的影响。其次,针对三种典型家庭基站室内部署场景(中心、角落和内墙中点位置),通过数学建模与推导获得在室内空洞和室外干扰之和最小化目标下家庭基站最优覆盖半径的闭式解。然后,采用认知导频信道技术进行层叠网络地理位置信息的有效传输,使得家庭基站获得室内位置信息、与宏蜂窝基站相对距离等关键参量值。最后,依据家庭基站部署位置信息,并结合多覆盖天线类型的选取、动态功率分配策略,通过采用人工神经网络对家庭基站典型场景覆盖自优化方案的训练和学习,获得普遍适用于家庭基站随机部署场景的覆盖自优化方案模型,实现家庭基站网络覆盖优化的自主化目标。第三,首先,针对认知协作中继网络三种典型场景运用图论理论进行网络容量模型的构建与定量表示。其次,针对两跳协作中继网络中不同链路可用频谱资源和可达容量存在的差异性,以中继链路传输容量最大化为目标设计动态时隙分配比例方案,并从理论上证明所提动态时隙方案相对固定时隙方案在容量提升方面的突出效果。然后,依据对网络空闲频谱信息认知的结果,基于最优化理论和图论理论,设计中继节点选择、信道分配和动态时隙比例划分的认知协作中继网络容量联合自优化方案。通过与传统固定时隙分配方案相比较,证明所提方案对容量提升的有效性,并进一步体现所提方案对链路容量存在差异性一般情况的自主适变能力。总之,第三部分通过对典型家庭基站网络频率自部署、覆盖自优化、认知中继网络容量自优化等自组织理论及关键技术的研究,提高了异构网络资源管控的自主化,大大降低了异构网络资源管控的复杂度,达到频谱利用效率提高、网络容量提升和网络覆盖优化等目标。
第四部分,对论文所述研究内容进行全面总结。依据对本领域研究现状的分析和归纳,指出本领域未来研究工作的难点与热点,供后续研究人员参考。
Driven by the demands for better user experience and various types of service, wireless network technologies are developing rapidly recently with the capabilities of providing high data rate services with good quality of service (QoS). However, challenges still exist as different kinds of heterogeneous radio access technologies (RATs) are coexisting with each other, which make the network convergence a complex problem. Moreover, fixed spectrum allocation and management schemes are not efficiently adapt to the dynamically changing radio environment and user demands. So the challenges for future wireless network development are summarized as:how to design an efficient technique for heterogeneous network information delivery, how to decrease the complexity of heterogeneous network radio resource management, how to improve the spectrum efficiency and increase network capacity.
In order to solve these challenges and improve radio resource usage efficiency, cognitive wireless networks (CWNs) technologies are considered as candidate solutions, which are based on the software defined radio (SDR) technology and cognitive radio (CR) technology. The CWNs should have the abilities to reconfigurate the parameters, protocol stacks and working modes, which are based on the sensing techniques and learning ability of existing knowledge in database, in order to adapt to the changing radio environment. The CWNs should also have the abilities to obtain the radio environment information, self-optimize radio resource and dynamically tune the parameters and protocols to adapt to the changing environment.
This thesis focuses on novel theories and techniques for efficient heterogeneous network information delivery, simple heterogeneous network radio resource management, improved spectrum usage and increased network capacity in CWNs.
Facing to the challenge of efficient heterogeneous network information delivery, the cognitive pilot channel (CPC) design theory and techniques are proposed in this thesis, which is regarded as a common pilot channel for accurate and efficient heterogeneous network information delivery. The key contributions include two parts.
First, both the out-band CPC and in-band CPC modes are introduced briefly, and both the pros and cons between them are analyzed thoroughly. Next, key parameters for heterogeneous network information delivery using CPC are summarized as terminal position shift error and multi-RAT overlapped effects. The close-form theoretical analyses are achieved based on the mathematics model for the probability calculation of information error caused by the GPS based terminal shifting effect. Then, based on the Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRC) algorithms, novel mesh division schemes are proposed by considering both the terminal position shift error effect and heterogeneous network information, which is an achievement in this field as nobody has proposed complete solutions with proofs before.
Second, to further improve the efficiency of traditional broadcast CPC, the differential mesh information coding (DIC) scheme is proposed in order to reduce the redundancy of network information between adjacent meshes by using image processing techniques. Then, to optimize the traditional broadcast CPC delivery mode, a homogeneous meshes grouping (HoMG) scheme has also been proposed which can reduce duplicate network information delivery in adjacent meshes, assuring an efficient and accurate network information delivery with novel CPC design. Therefore, the proposed optimal mesh division scheme and novel broadcast CPC flow are the fundamental basis for the accurate and efficient heterogeneous network information delivery in CWNs.
Due to the increase of heterogeneity and complexity for the operation and maintenance in CWNs, the traditional techniques for network planning, operation and maintenance are not efficient and applicable in CWNs, which are human interaction dependent, time consuming and cost inefficient. Therefore, self-organizing networks (SON) techniques, including self-planning, self-configuration, self-optimization, self-management and self-healing, are analyzed in this thesis for efficiently autonomous network parameter configuration, optimization and maintenance in CWNs, to improve the radio resource usage efficiency and decrease the CAPEX and OPEX. To improve the network capacity, coverage and spectrum efficiency for indoors and hotspots, self-configuration and self-optimization techniques for femtocell networks and cognitive cooperative relay networks are taken into account in this thesis. The key contributions include three parts.
First, both the downlink capacity model and key parameters of three frequency allocation schemes for femtocells deployment in the hierarchical network are designed and analyzed with close-form solutions. Next, a novel location-based frequency information acquisition scheme is proposed which includes the technique to obtain geo-location based macrocell resource occupancy information, the efficient delivery process using CPC to femtocells. Then, the frequency self-deployment scheme for femtocells is designed with the optimal grid zone size selection for femtocells by leveraging the spatial reuse of macrocell resource to improve system capacity.
Second, to improve the coverage indoors and increase hierarchical network capacity, the joint antenna pattern selection and dynamic power allocation scheme for coverage self-optimization scheme in femtocells is proposed. The effects of both the static power allocation and dynamic power allocation schemes to coverage holes indoors and interference outdoors are analyzed theoretically. Next, the optimal coverage radius for femtocell indoors is analyzed in three scenarios with close-form solutions, such as the center position, corner position and midpoint of side wall. Then, the geo-location information of femtocell is obtained via CPC channel, in order to locate the indoor femtocell position and the distance to macro base station. Thus, the joint antenna pattern selection and dynamic power allocation scheme is modeled by using the artificial neural network (ANN) training the learning techniques, to fulfill the femtocell coverage self-optimization object.
Third, to further extend the coverage and improve network capacity, the dynamic time slot allocation scheme based cognitive cooperative relay network capacity self-optimization scheme is designed. The capacity model for two hop cooperative relay networks is modeled in three different scenarios. Next, considering the difference of channel capacity on various links due to the randomness and time-variant effects, the optimal dynamic time slot allocation scheme is proposed and proved theoretically with close-form solutions, which can improve the relay link capacity by self-tuning transmission time slot between two relay links. Then, based on the vacant spectrum information via CPC, the joint relay node selection, channel allocation and dynamic transmission time slot allocation scheme is designed which is regarded as the capacity self-optimization solution in CWNs by using the optimization theory and graph theory. In summary, the proposed frequency self-deployment, coverage self-optimization in femtocells and capacity self-optimization in cognitive cooperative relay networks prove the efficiency of SON techniques to decrease the complexity of CWNs management and improve the spectrum usage, capacity and coverage.
Finally, the summary is given at the end of this thesis and future research directions in related fields are also pointed out.
面对无线网络异构融合的新趋势、业务宽带化和多样化的新需求、频谱利用效率和网络容量进一步提升的新目标,已有的静态频谱管理方式和传统以人工为主的网络规划与优化手段无法满足无线网络环境复杂多变和无线业务需求不断增长的新趋势。所以,未来无线网络发展所面临的挑战可归结为：支持异构网络融合的信息有效互通新方法挑战、降低网络资源管控复杂度新技术挑战、提升网络频谱利用效率和网络容量新技术挑战等。
针对未来无线网络发展所面临的新需求和新挑战,具有无线网络认知性、异构网络适变性和网络管控自主性的认知无线网络技术应运而生。认知无线网络能够通过对网络环境的认知,进行智能的决策,通过参数、协议和网络模式的重构实现对无线网络环境变化的自主适变,并通过自主学习实现网络自主适变的智能化。同时,认知无线网络技术还可以有效支持异构网络融合、降低异构网络资源管控的复杂度,达到频谱利用效率提升、网络容量提高和网络覆盖优化等目标。因此,本文重点针对未来无线网络面临的异构网络信息互通不畅、资源管控复杂化、频谱利用效率低下和网络容量有待提高等问题与挑战展开深入研究,提出基于认知导频信道技术进行异构网络信息准确、高效传输方案,并基于此进行自组织网络技术方案的优化设计,以实现降低网络管控复杂度、提高频谱利用效率、提高网络容量、优化网络覆盖的目标。已在相关领域取得理论和技术创新成果。归纳来说,本文研究的内容主要包括以下四个部分：
第一部分,首先阐述未来无线网络发展趋势和面临的两大挑战：无线网络异构化和资源管控复杂化。其次,通过对认知无线网络技术的起源和关键技术的分析,提出采用认知导频信道技术可以有效异构网络之间信息互通的问题,并提出采用自组织网络技术可以有效降低异构网络资源管控的复杂度、提升网络性能。最后,通过认知无线网络中认知导频信道技术和自组织网络技术研究现状的全面分析,明确本文的研究重点在于认知导频信道的优化设计、并基于此进行认知无线网络中自组织方案设计,两方面研究内容相互关联、层层递进。
第二部分,针对异构网络信息有效互通的挑战,本文提出了支持异构网络信息准确和有效传输的认知导频信道理论及关键技术,包括两个创新点。第一,首先,基于已有认知导频信道技术中带外和带内两种部署方式的优点和不足进行比较分析。其次,明确影响异构网络信息准确传输的两大关键因素：终端定位偏移误差因素和栅格划分尺寸因素。针对终端定位偏移误差下的信息错误概率和信息丢失率进行理论建模并通过数学推导获得闭式解。然后,分析栅格划分尺寸大小对异构网络信息准确传输的影响,提出基于层次分析法和灰度关联分析理论的认知导频信道最优栅格划分准则和方案,实现基于认知导频信道的异构网络信息准确传输的目标,填补了本领域理论研究的空白。第二,首先,分析认知导频信道广播和点播两种典型发送方式的优点和不足,明确影响认知导频信道发送效率的关键因素。其次,针对邻近栅格中网络信息存在冗余的问题,提出差异量化的栅格信息编码理论,以提高异构网络信息的编码效率。然后,通过设计基于相同性质栅格信息的群组化改进广播方案,进一步提升异构网络信息发送的效率。总之,第二部分通过基于栅格最优划分准则、栅格信息差异量化编码、同性质栅格群组化发送等认知导频信道改进方案的设计,实现了异构网络信息准确、高效的传输,并为认知无线网络资源管控和有效利用的决策与执行提供了必要的信息有效传输技术手段。
第三部分,针对异构网络资源管控复杂化挑战、频谱利用效率和网络容量提升的新需求,本文重点针对具有容量提升、覆盖优化、自主管控特性的新型家庭基站网络技术和认知协作中继网络技术展开深入研究,分别提出具有自组织功能的家庭基站网络频率自部署、覆盖自优化理论与技术、认知协作中继网络容量自优化理论与技术,包括三个创新点。第一,首先,运用理论分析和数学推导相结合的方法重点研究不同频率部署方式(异频、同频和混频)对家庭基站与宏蜂窝网络共存下层叠网络的下行容量的影响因素,并通过数学建模进行量化表征。其次,研究基于地理位置信息的宏蜂窝基站频谱占用信息的主动认知方法,并设计基于认知导频信道的层叠网络信息有效传输方案,实现层叠网络内频谱占用信息的有效互通。然后,研究基于最优地理区域划分的家庭基站频率自部署理论及技术,降低层叠网络的干扰,从而提高层叠网络下行容量的目标。第二,首先,依据理论模型的定量分析结果,明确采用静态和动态功率分配两种方案对家庭基站覆盖优化的影响。其次,针对三种典型家庭基站室内部署场景(中心、角落和内墙中点位置),通过数学建模与推导获得在室内空洞和室外干扰之和最小化目标下家庭基站最优覆盖半径的闭式解。然后,采用认知导频信道技术进行层叠网络地理位置信息的有效传输,使得家庭基站获得室内位置信息、与宏蜂窝基站相对距离等关键参量值。最后,依据家庭基站部署位置信息,并结合多覆盖天线类型的选取、动态功率分配策略,通过采用人工神经网络对家庭基站典型场景覆盖自优化方案的训练和学习,获得普遍适用于家庭基站随机部署场景的覆盖自优化方案模型,实现家庭基站网络覆盖优化的自主化目标。第三,首先,针对认知协作中继网络三种典型场景运用图论理论进行网络容量模型的构建与定量表示。其次,针对两跳协作中继网络中不同链路可用频谱资源和可达容量存在的差异性,以中继链路传输容量最大化为目标设计动态时隙分配比例方案,并从理论上证明所提动态时隙方案相对固定时隙方案在容量提升方面的突出效果。然后,依据对网络空闲频谱信息认知的结果,基于最优化理论和图论理论,设计中继节点选择、信道分配和动态时隙比例划分的认知协作中继网络容量联合自优化方案。通过与传统固定时隙分配方案相比较,证明所提方案对容量提升的有效性,并进一步体现所提方案对链路容量存在差异性一般情况的自主适变能力。总之,第三部分通过对典型家庭基站网络频率自部署、覆盖自优化、认知中继网络容量自优化等自组织理论及关键技术的研究,提高了异构网络资源管控的自主化,大大降低了异构网络资源管控的复杂度,达到频谱利用效率提高、网络容量提升和网络覆盖优化等目标。
第四部分,对论文所述研究内容进行全面总结。依据对本领域研究现状的分析和归纳,指出本领域未来研究工作的难点与热点,供后续研究人员参考。
Driven by the demands for better user experience and various types of service, wireless network technologies are developing rapidly recently with the capabilities of providing high data rate services with good quality of service (QoS). However, challenges still exist as different kinds of heterogeneous radio access technologies (RATs) are coexisting with each other, which make the network convergence a complex problem. Moreover, fixed spectrum allocation and management schemes are not efficiently adapt to the dynamically changing radio environment and user demands. So the challenges for future wireless network development are summarized as:how to design an efficient technique for heterogeneous network information delivery, how to decrease the complexity of heterogeneous network radio resource management, how to improve the spectrum efficiency and increase network capacity.
In order to solve these challenges and improve radio resource usage efficiency, cognitive wireless networks (CWNs) technologies are considered as candidate solutions, which are based on the software defined radio (SDR) technology and cognitive radio (CR) technology. The CWNs should have the abilities to reconfigurate the parameters, protocol stacks and working modes, which are based on the sensing techniques and learning ability of existing knowledge in database, in order to adapt to the changing radio environment. The CWNs should also have the abilities to obtain the radio environment information, self-optimize radio resource and dynamically tune the parameters and protocols to adapt to the changing environment.
This thesis focuses on novel theories and techniques for efficient heterogeneous network information delivery, simple heterogeneous network radio resource management, improved spectrum usage and increased network capacity in CWNs.
Facing to the challenge of efficient heterogeneous network information delivery, the cognitive pilot channel (CPC) design theory and techniques are proposed in this thesis, which is regarded as a common pilot channel for accurate and efficient heterogeneous network information delivery. The key contributions include two parts.
First, both the out-band CPC and in-band CPC modes are introduced briefly, and both the pros and cons between them are analyzed thoroughly. Next, key parameters for heterogeneous network information delivery using CPC are summarized as terminal position shift error and multi-RAT overlapped effects. The close-form theoretical analyses are achieved based on the mathematics model for the probability calculation of information error caused by the GPS based terminal shifting effect. Then, based on the Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRC) algorithms, novel mesh division schemes are proposed by considering both the terminal position shift error effect and heterogeneous network information, which is an achievement in this field as nobody has proposed complete solutions with proofs before.
Second, to further improve the efficiency of traditional broadcast CPC, the differential mesh information coding (DIC) scheme is proposed in order to reduce the redundancy of network information between adjacent meshes by using image processing techniques. Then, to optimize the traditional broadcast CPC delivery mode, a homogeneous meshes grouping (HoMG) scheme has also been proposed which can reduce duplicate network information delivery in adjacent meshes, assuring an efficient and accurate network information delivery with novel CPC design. Therefore, the proposed optimal mesh division scheme and novel broadcast CPC flow are the fundamental basis for the accurate and efficient heterogeneous network information delivery in CWNs.
Due to the increase of heterogeneity and complexity for the operation and maintenance in CWNs, the traditional techniques for network planning, operation and maintenance are not efficient and applicable in CWNs, which are human interaction dependent, time consuming and cost inefficient. Therefore, self-organizing networks (SON) techniques, including self-planning, self-configuration, self-optimization, self-management and self-healing, are analyzed in this thesis for efficiently autonomous network parameter configuration, optimization and maintenance in CWNs, to improve the radio resource usage efficiency and decrease the CAPEX and OPEX. To improve the network capacity, coverage and spectrum efficiency for indoors and hotspots, self-configuration and self-optimization techniques for femtocell networks and cognitive cooperative relay networks are taken into account in this thesis. The key contributions include three parts.
First, both the downlink capacity model and key parameters of three frequency allocation schemes for femtocells deployment in the hierarchical network are designed and analyzed with close-form solutions. Next, a novel location-based frequency information acquisition scheme is proposed which includes the technique to obtain geo-location based macrocell resource occupancy information, the efficient delivery process using CPC to femtocells. Then, the frequency self-deployment scheme for femtocells is designed with the optimal grid zone size selection for femtocells by leveraging the spatial reuse of macrocell resource to improve system capacity.
Second, to improve the coverage indoors and increase hierarchical network capacity, the joint antenna pattern selection and dynamic power allocation scheme for coverage self-optimization scheme in femtocells is proposed. The effects of both the static power allocation and dynamic power allocation schemes to coverage holes indoors and interference outdoors are analyzed theoretically. Next, the optimal coverage radius for femtocell indoors is analyzed in three scenarios with close-form solutions, such as the center position, corner position and midpoint of side wall. Then, the geo-location information of femtocell is obtained via CPC channel, in order to locate the indoor femtocell position and the distance to macro base station. Thus, the joint antenna pattern selection and dynamic power allocation scheme is modeled by using the artificial neural network (ANN) training the learning techniques, to fulfill the femtocell coverage self-optimization object.
Third, to further extend the coverage and improve network capacity, the dynamic time slot allocation scheme based cognitive cooperative relay network capacity self-optimization scheme is designed. The capacity model for two hop cooperative relay networks is modeled in three different scenarios. Next, considering the difference of channel capacity on various links due to the randomness and time-variant effects, the optimal dynamic time slot allocation scheme is proposed and proved theoretically with close-form solutions, which can improve the relay link capacity by self-tuning transmission time slot between two relay links. Then, based on the vacant spectrum information via CPC, the joint relay node selection, channel allocation and dynamic transmission time slot allocation scheme is designed which is regarded as the capacity self-optimization solution in CWNs by using the optimization theory and graph theory. In summary, the proposed frequency self-deployment, coverage self-optimization in femtocells and capacity self-optimization in cognitive cooperative relay networks prove the efficiency of SON techniques to decrease the complexity of CWNs management and improve the spectrum usage, capacity and coverage.
Finally, the summary is given at the end of this thesis and future research directions in related fields are also pointed out.
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