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Joint Transmission in QoE-Driven Backhaul-Aware MC-NOMA Cognitive Radio Network
arXiv - CS - Multimedia Pub Date : 2020-08-30 , DOI: arxiv-2008.13269
Hosein Zarini, Ata Khalili, Hina Tabassum, and Mehdi Rasti

In this paper, we develop a resource allocation framework to optimize the downlink transmission of a backhaul-aware multi-cell cognitive radio network (CRN) which is enabled with multi-carrier non-orthogonal multiple access (MC-NOMA). The considered CRN is composed of a single macro base station (MBS) and multiple small BSs (SBSs) that are referred to as the primary and secondary tiers, respectively. For the primary tier, we consider orthogonal frequency division multiple access (OFDMA) scheme and also Quality of Service (QoS) to evaluate the user satisfaction. On the other hand in secondary tier, MC-NOMA is employed and the user satisfaction for web, video and audio as popular multimedia services is evaluated by Quality-of-Experience (QoE). Furthermore, each user in secondary tier can be served simultaneously by multiple SBSs over a subcarrier via Joint Transmission (JT). In particular, we formulate a joint optimization problem of power control and scheduling (i.e., user association and subcarrier allocation) in secondary tier to maximize total achievable QoE for the secondary users. An efficient resource allocation mechanism has been developed to handle the non-linear form interference and to overcome the non-convexity of QoE serving functions. The scheduling and power control policy leverage on Augmented Lagrangian Method (ALM). Simulation results reveal that proposed solution approach can control the interference and JT-NOMA improves total perceived QoE compared to the existing schemes.

中文翻译:

QoE-Driven Backhaul-Aware MC-NOMA 认知无线电网络中的联合传输

在本文中,我们开发了一个资源分配框架来优化支持多载波非正交多址 (MC-NOMA) 的回程感知多小区认知无线电网络 (CRN) 的下行链路传输。所考虑的 CRN 由单个宏基站 (MBS) 和多个小基站 (SBS) 组成,分别称为主要和次要层。对于初级,我们考虑正交频分多址 (OFDMA) 方案和服务质量 (QoS) 来评估用户满意度。另一方面,在二级层中,采用 MC-NOMA,用户对网络、视频和音频等流行多媒体服务的满意度通过体验质量 (QoE) 进行评估。此外,次级层中的每个用户可以通过联合传输 (JT) 在一个子载波上同时由多个 SBS 服务。特别地,我们在二级层制定了功率控制和调度(即用户关联和子载波分配)的联合优化问题,以最大化二级用户的总可实现 QoE。已经开发了一种有效的资源分配机制来处理非线性形式的干扰并克服 QoE 服务功能的非凸性。调度和功率控制策略利用了增广拉格朗日方法 (ALM)。仿真结果表明,与现有方案相比,所提出的解决方案方法可以控制干扰,并且 JT-NOMA 提高了总感知 QoE。我们在二级层制定了功率控制和调度(即用户关联和子载波分配)的联合优化问题,以最大化二级用户的总可实现 QoE。已经开发了一种有效的资源分配机制来处理非线性形式的干扰并克服 QoE 服务功能的非凸性。调度和功率控制策略利用了增广拉格朗日方法 (ALM)。仿真结果表明,与现有方案相比,所提出的解决方案方法可以控制干扰,并且 JT-NOMA 提高了总感知 QoE。我们在二级层制定了功率控制和调度(即用户关联和子载波分配)的联合优化问题,以最大化二级用户的总可实现 QoE。已经开发了一种有效的资源分配机制来处理非线性形式的干扰并克服 QoE 服务功能的非凸性。调度和功率控制策略利用了增广拉格朗日方法 (ALM)。仿真结果表明,与现有方案相比,所提出的解决方案方法可以控制干扰,并且 JT-NOMA 提高了总感知 QoE。已经开发了一种有效的资源分配机制来处理非线性形式的干扰并克服 QoE 服务功能的非凸性。调度和功率控制策略利用了增广拉格朗日方法 (ALM)。仿真结果表明,与现有方案相比,所提出的解决方案方法可以控制干扰,并且 JT-NOMA 提高了总感知 QoE。已经开发了一种有效的资源分配机制来处理非线性形式的干扰并克服 QoE 服务功能的非凸性。调度和功率控制策略利用了增广拉格朗日方法 (ALM)。仿真结果表明,与现有方案相比,所提出的解决方案方法可以控制干扰,并且 JT-NOMA 提高了总感知 QoE。
更新日期:2020-09-01
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