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Statistical Delay QoS Driven Energy Efficiency and Effective Capacity Tradeoff for Uplink Multi-User Multi-Carrier Systems

机译:统计延迟QoS驱动的能效和上行多用户多运营商系统的有效容量折衷

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摘要

In this paper, the total system effective capacity (EC) maximization problem for the uplink transmission, in a multi-user multi-carrier OFDMA system, is formulated as a combinatorial integer programming problem, subject to each user’s link-layer energy efficiency (EE) requirement as well as the individual’s average transmission power limit. To solve this challenging problem, we first decouple it into a frequency provisioning problem and an independent multi-carrier linklayer EE-EC tradeoff problem for each user. In order to obtain the subcarrier assignment solution, a low-complexity heuristic algorithm is proposed, which not only offers close-to-optimal solutions, while serving as many users as possible, but also has a complexity linearly relating to the size of the problem. After obtaining the subcarrier assignment matrix, the multi-carrier link-layer EE-EC tradeoff problem for each user is formulated and solved by using Karush-Kuhn-Tucker (KKT) conditions. The per-user optimal power allocation strategy, which is across both frequency and time domains, is then derived. Further, we theoretically investigate the impact of the circuit power and the EE requirement factor on each user’s EE level and optimal average power value. The low-complexity heuristic algorithm is then simulated to compare with the traditional exhaustive algorithm and a fair-exhaustive algorithm. Simulation results confirm our proofs and design intentions, and further show the effects of delay quality-of-service (QoS) exponent, the total number of users and the number of subcarriers on the system tradeoff performance.
机译:本文将多用户多载波OFDMA系统中上行传输的总系统有效容量(EC)最大化问题公式化为组合整数规划问题,具体取决于每个用户的链路层能效(EE) )要求以及个人的平均传输功率限制。为了解决这个具有挑战性的问题,我们首先将其分解为频率配置问题和针对每个用户的独立多载波链路层EE-EC权衡问题。为了获得子载波分配解决方案,提出了一种低复杂度的启发式算法,该算法不仅提供尽可能接近最优的解决方案,同时为尽可能多的用户提供服务,而且其复杂度与问题的大小呈线性关系。在获得子载波分配矩阵之后,通过使用Karush-Kuhn-Tucker(KKT)条件来制定和解决每个用户的多载波链路层EE-EC权衡问题。然后,得出跨频域和时域的每用户最佳功率分配策略。此外,我们从理论上研究电路功率和EE要求因子对每个用户的EE水平和最佳平均功率值的影响。然后对低复杂度启发式算法进行了仿真,以与传统的穷举算法和公平穷举算法进行比较。仿真结果证实了我们的证明和设计意图,并进一步显示了延迟服务质量(QoS)指数,用户总数和子载波数量对系统权衡性能的影响。

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