A Greedy Heuristic Algorithm for Context-Aware User Association and Resource Allocation in Heterogeneous Wireless Networks

Mohamad Zalghout, J. Hélard, M. Crussiére, Samih Abdul-Nabi, Ayman Khalil
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引用次数: 7

Abstract

Wireless heterogeneous networks are usually characterized by the integration of different types of radio access technologies (RATs) to enhance system capacity and meet user requirements. In this context, we formulate a user association and downlink resource allocation optimization problem to maximize the overall user-centric profit in the system. The context-awareness is based on the user preferences, the data rate requested by each user equipment (UE), and the RAT characteristics and constraints. The user preference is based on a normalized weighted profit function that considers both the received signal quality and the power consumption at UEs. To approximate the formulated optimization problem, a greedy heuristic algorithm with polynomial-time complexity is proposed. It is shown through persuasive simulations that the proposed heuristic algorithm, when compared to the trivial profit-function-based solution, enhances the average user satisfaction in the system and lowers the percentage of blocked data rate. In fact, the performance of the proposed heuristic algorithm comes close to the optimal solution while requesting a lower number of handovers (HOs).
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异构无线网络环境感知用户关联与资源分配的贪婪启发式算法
无线异构网络的特点通常是集成不同类型的无线接入技术,以增强系统容量和满足用户需求。在此背景下,我们制定了用户关联和下行资源分配优化问题,以最大化系统中以用户为中心的整体利润。上下文感知基于用户偏好、每个用户设备(UE)请求的数据速率以及RAT特征和约束。用户偏好基于标准化加权收益函数,该函数同时考虑了ue的接收信号质量和功耗。为了逼近所提出的优化问题,提出了一种时间复杂度为多项式的贪心启发式算法。通过有说服力的仿真表明,与基于平凡利润函数的解决方案相比,所提出的启发式算法提高了系统的平均用户满意度,降低了阻塞数据率的百分比。事实上,所提出的启发式算法的性能接近最优解,同时请求更少的移交(HOs)。
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