基于QoE的无线资源管理算法研究
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摘要
随着无线通信系统的蓬勃发展和智能化终端的不断创新,移动互联网业务发展迅速,给无线通信网络的设计和实现提出了新的要求。长期以来,网络优化一般以提高服务质量(Quality of Service, QoS)为目标,但是QoS作为描述网络性能的客观指标并不能直接体现用户对业务的感受,并且严格的QoS要求使网络的服务能力受到一定的限制。用户体验质量(Quality of Experience, QoE)这一概念的引入,将传统基于通信系统客观指标的设计理念拓展到关注主观用户体验的方向上。根据国际电信联盟的定义,QoE可以理解为“决定用户满意程度的服务性能的综合效果。”另外,QoE作为一种业务质量评价指标,不仅能够统一评价业务中的多种QoS指标对用户体验的影响,还能够统一评价不同类型业务的主观使用体验,是一种适用于多业务无线网络的优化指标。而未来的无线通信系统应能实现更高的资源利用效率,并进一步提升用户使用业务的满意程度,无线资源管理是达到这一目标的重要机制。在无线资源管理算法中引入QoE还能提供给不同业务不同用户适度的服务,而不是单纯追求QoS客观指标的提升,从而进一步提高系统的资源利用率。因此,探索基于用户QoE的无线资源管理算法,具有重要的研究意义和应用价值。
基于未来无线通信网络的发展趋势,本文重点研究网络接入选择、接入控制、资源分配、动态资源调度等,旨在从多方面探讨基于QoE的资源管理机制。本文主要内容和创新性工作包括：
1)基于未来无线通信网络的异构化特征,提出一种基于QoE的高能效网络接入选择算法,该算法采用进化博弈理论建模用户网络选择策略的动态过程,决策因素综合考虑用户QoE模型,网络能耗模型的差异及网络负载状况等,是一种兼顾用户与网络利益的分布式网络接入选择算法。由于在影响用户决策的收益函数中引入QoE和能耗,接入用户经过自发的学习和模仿,不断更新网络接入策略,趋于选择能够提升QoE且能耗较低的网络进行接入,从而缓解了负载过重的网络压力。在一定程度上增加了高能效网络被选择接入的机会,最后收敛到进化博弈均衡点,达到收益均等的负载均衡状态。该算法使得用户优先接入高能效的网络,能够有效降低网络能耗。
2)针对用户在接入过程中影响QoE的因素呈现多维化特征,包括网络吞吐量、接入时延、丢包率、用户(业务)优先级等,提出了一种基于QoE的接入控制机制。在该机制中针对多优先级信道接入特性设计了一种新型三维马尔科夫链分析方法,刻画了用户的退避接入行为。推导出用户在各个接入状态下的稳态概率,并分析了饱和及非饱和网络负载状态下的用户接入QoS性能。并基于该分析模型,提出一种基于竞争窗动态调整的接入控制算法。该算法突破了固定竞争窗的限制,利用分析模型实时预测当前负载状态下用户可获得的QoE,并遵循QoE最大化原则动态优化各优先级的竞争窗长度,达到了提升网络的业务承载能力并增强用户QoE的目的。
3)无线资源是业务传输的载体,针对如何在多种传输方式下协调羿构无线资源的问题,研究蜂窝系统中短距通信补充部署场景中的资源分配问题,并利用不同传输方式下的业务类型、业务分布特征及长期信道特性,提出一种QoE最大化的资源分配算法,相比传统资源分配算法,能够显著提升用户的平均QoE。
4)由于用户移动性对系统性能有着重要的影响,研究存在群组移动性的多业务资源分配问题,并提出基于动态子信道关闭技术的资源分配算法,包括最大化系统QoE的高能效资源分配及基于QoE保证的最小化能耗资源分配。该算法通过白适应地关闭一定数量的子信道以抵抗高移动性无线环境下载波间干扰的影响,从而在一定程度上改善信道质量,同时由于子信道的减少能够线性降低发射功率的消耗。所提算法对各群组间的带宽资源分配及群组内子信道关闭数量进行联合优化,并证明该资源分配问题为任意有限区间内存在唯一最优值的拟凹(quasi-concave)问题,通过贪婪算法对该问题进行求解,仿真证明所得到的分配结果能够有效提升用户QoE和网络能效。
5)为了通过资源调度算法提升用户QoE,首先分析了能够最大化QoE的资源调度问题,接着将比例公平思想引入基于QoE的多业务资源调度中,提出了基于QoE的比例公平调度问题。利用整数规划建模以上两种问题,并通过整数变量的松弛转化,分别提出了最大化QoE的资源调度算法及基于QoE的比例公平算法。对比传统的资源调度算法,前者能够显著提升多用户系统的整体QoE,但公平性较差；后者不仅能够获得较优的QoE性能,同时也提高了小区边缘用户被调度的机会,从而取得了系统整体QoE与用户公平性的折中。
With the rapid development of wireless communication systems and smart equipment, mobile internet services grows explosively, which brings in new demands for the design and implementation of communication networks. The previous target of enhancing Quality of Services (QoS) that is an objective indicator in wireless networks optimization could hardly convey the subjective experience of the end users to the current services, and may constrain the service capacity instead as a result of its strict QoS requirements. Quality of experience (QoE) expends the objective technical indicators in a traditional way into a brand-new horizon of users'subjective perception of services. QoE is defined by International Telecommunication Union as "a measure of the overall acceptability of an application or service, as perceived subjectively by the end-user." Moreover, as a uniform quality indicator in multi-services networks, QoE is able to unify many QoS indicators in a single service and also several kinds of different services impacting on user perception. Future wireless telecommunication systems should support more efficient resource utilization and higher users'satisfaction level. Radio resource management is an important approach to achieve this goal. Therefore, the exploration of QoE-based radio resource management is a significant issue for both research and application.
According to the above demands of future wireless communication systems, this dissertation investigates on several radio resource management algorithms from the perspective of QoE including network selection, access control, resource management and dynamic resource scheduling joint. The main contents and contributions of this dissertation are presented as follows:
Regarding with the heterogeneous characteristic of the future wireless communication networks, an energy efficient network selection multi-services resource allocation problem with group mobility is mainly discussed, and energy efficient resource allocation schemes in combination with adaptive sub-channels blackout are developed, including maximizing QoE algorithm and minimizing energy consumption algorithm with QoE guarantee. The two algorithms utilize sub-channels blackout to mitigate the inter-carrier interference in high mobility environment by turning off certain sub-channels when transmitting signals, so that channel quality is improved, a good balance can also be achieved between reduced transmit data rate and increased carrier to interference ratio, and energy can be saved linearly as a result of less active sub-channel. The proposed resource allocation algorithms consisting of inter-group resource allocation and inner-group sub-channels blackout. We also prove that under sub-channels blackout, the achieved throughput and perceptual QoE are quasi-concave in energy saving percentage, which can be figured out by greedy algorithm. Numerical results confirm the theoretical findings and demonstrate the promising energy-saving capability with satisfying QoE of the proposed resource allocation algorithms.
Resource scheduling problem with maximizing QoE is first addressed. Then the proportional fair (PF) principle was adopted in QoE-based multi-services resource scheduling, termed as QoE-aware PF scheduling problem. Two integer programming problems are formed and then max-QoE scheduling algorithm and the QoE-aware PF scheduling algorithm are derived by solving the relaxed problems. Simulation results show that the proposed max-QoE can significantly enhance perceptive QoE but with unsatisfactory user fairness. QoE-aware PF scheduling algorithm performs well in terms of user QoE, and also increases the probability to be scheduled for cell-edge users, which results in a good balance between the overall QoE and fairness.
基于未来无线通信网络的发展趋势,本文重点研究网络接入选择、接入控制、资源分配、动态资源调度等,旨在从多方面探讨基于QoE的资源管理机制。本文主要内容和创新性工作包括：
1)基于未来无线通信网络的异构化特征,提出一种基于QoE的高能效网络接入选择算法,该算法采用进化博弈理论建模用户网络选择策略的动态过程,决策因素综合考虑用户QoE模型,网络能耗模型的差异及网络负载状况等,是一种兼顾用户与网络利益的分布式网络接入选择算法。由于在影响用户决策的收益函数中引入QoE和能耗,接入用户经过自发的学习和模仿,不断更新网络接入策略,趋于选择能够提升QoE且能耗较低的网络进行接入,从而缓解了负载过重的网络压力。在一定程度上增加了高能效网络被选择接入的机会,最后收敛到进化博弈均衡点,达到收益均等的负载均衡状态。该算法使得用户优先接入高能效的网络,能够有效降低网络能耗。
2)针对用户在接入过程中影响QoE的因素呈现多维化特征,包括网络吞吐量、接入时延、丢包率、用户(业务)优先级等,提出了一种基于QoE的接入控制机制。在该机制中针对多优先级信道接入特性设计了一种新型三维马尔科夫链分析方法,刻画了用户的退避接入行为。推导出用户在各个接入状态下的稳态概率,并分析了饱和及非饱和网络负载状态下的用户接入QoS性能。并基于该分析模型,提出一种基于竞争窗动态调整的接入控制算法。该算法突破了固定竞争窗的限制,利用分析模型实时预测当前负载状态下用户可获得的QoE,并遵循QoE最大化原则动态优化各优先级的竞争窗长度,达到了提升网络的业务承载能力并增强用户QoE的目的。
3)无线资源是业务传输的载体,针对如何在多种传输方式下协调羿构无线资源的问题,研究蜂窝系统中短距通信补充部署场景中的资源分配问题,并利用不同传输方式下的业务类型、业务分布特征及长期信道特性,提出一种QoE最大化的资源分配算法,相比传统资源分配算法,能够显著提升用户的平均QoE。
4)由于用户移动性对系统性能有着重要的影响,研究存在群组移动性的多业务资源分配问题,并提出基于动态子信道关闭技术的资源分配算法,包括最大化系统QoE的高能效资源分配及基于QoE保证的最小化能耗资源分配。该算法通过白适应地关闭一定数量的子信道以抵抗高移动性无线环境下载波间干扰的影响,从而在一定程度上改善信道质量,同时由于子信道的减少能够线性降低发射功率的消耗。所提算法对各群组间的带宽资源分配及群组内子信道关闭数量进行联合优化,并证明该资源分配问题为任意有限区间内存在唯一最优值的拟凹(quasi-concave)问题,通过贪婪算法对该问题进行求解,仿真证明所得到的分配结果能够有效提升用户QoE和网络能效。
5)为了通过资源调度算法提升用户QoE,首先分析了能够最大化QoE的资源调度问题,接着将比例公平思想引入基于QoE的多业务资源调度中,提出了基于QoE的比例公平调度问题。利用整数规划建模以上两种问题,并通过整数变量的松弛转化,分别提出了最大化QoE的资源调度算法及基于QoE的比例公平算法。对比传统的资源调度算法,前者能够显著提升多用户系统的整体QoE,但公平性较差；后者不仅能够获得较优的QoE性能,同时也提高了小区边缘用户被调度的机会,从而取得了系统整体QoE与用户公平性的折中。
With the rapid development of wireless communication systems and smart equipment, mobile internet services grows explosively, which brings in new demands for the design and implementation of communication networks. The previous target of enhancing Quality of Services (QoS) that is an objective indicator in wireless networks optimization could hardly convey the subjective experience of the end users to the current services, and may constrain the service capacity instead as a result of its strict QoS requirements. Quality of experience (QoE) expends the objective technical indicators in a traditional way into a brand-new horizon of users'subjective perception of services. QoE is defined by International Telecommunication Union as "a measure of the overall acceptability of an application or service, as perceived subjectively by the end-user." Moreover, as a uniform quality indicator in multi-services networks, QoE is able to unify many QoS indicators in a single service and also several kinds of different services impacting on user perception. Future wireless telecommunication systems should support more efficient resource utilization and higher users'satisfaction level. Radio resource management is an important approach to achieve this goal. Therefore, the exploration of QoE-based radio resource management is a significant issue for both research and application.
According to the above demands of future wireless communication systems, this dissertation investigates on several radio resource management algorithms from the perspective of QoE including network selection, access control, resource management and dynamic resource scheduling joint. The main contents and contributions of this dissertation are presented as follows:
Regarding with the heterogeneous characteristic of the future wireless communication networks, an energy efficient network selection multi-services resource allocation problem with group mobility is mainly discussed, and energy efficient resource allocation schemes in combination with adaptive sub-channels blackout are developed, including maximizing QoE algorithm and minimizing energy consumption algorithm with QoE guarantee. The two algorithms utilize sub-channels blackout to mitigate the inter-carrier interference in high mobility environment by turning off certain sub-channels when transmitting signals, so that channel quality is improved, a good balance can also be achieved between reduced transmit data rate and increased carrier to interference ratio, and energy can be saved linearly as a result of less active sub-channel. The proposed resource allocation algorithms consisting of inter-group resource allocation and inner-group sub-channels blackout. We also prove that under sub-channels blackout, the achieved throughput and perceptual QoE are quasi-concave in energy saving percentage, which can be figured out by greedy algorithm. Numerical results confirm the theoretical findings and demonstrate the promising energy-saving capability with satisfying QoE of the proposed resource allocation algorithms.
Resource scheduling problem with maximizing QoE is first addressed. Then the proportional fair (PF) principle was adopted in QoE-based multi-services resource scheduling, termed as QoE-aware PF scheduling problem. Two integer programming problems are formed and then max-QoE scheduling algorithm and the QoE-aware PF scheduling algorithm are derived by solving the relaxed problems. Simulation results show that the proposed max-QoE can significantly enhance perceptive QoE but with unsatisfactory user fairness. QoE-aware PF scheduling algorithm performs well in terms of user QoE, and also increases the probability to be scheduled for cell-edge users, which results in a good balance between the overall QoE and fairness.
引文
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