On demand SINR based scheduling algorithm (ODSSA) for mobile uplink communication in LTE networks

S. K. L. V. Sai Prakash, M. Visali
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引用次数: 1

Abstract

Long Term Evolution (LTE) a Third Generation Partnership Project (3GPP) is developed for multimedia applications on mobile user equipment with very high data rates of the order 75/300 Mbps and low latency of 10msec. The high data rates are achieved by using SC-FDMA radio access mechanism for uplink communication and OFDM access mechanism for downlink. The performance can be further improved by scheduling the user data in an efficient manner considering channel characteristics as well as its QOS parameters, thereby allocating the resources to maximize the throughput. The Packet Scheduler helps in handling the LTE data traffic by allocating the resources both in time and frequency dimension. In this paper, we propose a novel scheduling algorithm that allocates maximum resources for the random users depending on their channel SNR condition with main focus on the data flow behavior. This is then compared with the two distinct algorithms that focus mainly on flow level dynamics- Fair Fixed Assignment (FFA) and Maximum added value (MAV) algorithms. It is shown that our algorithm outperforms the other two algorithms in terms of mean flow transfer time.
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基于随需应变SINR的LTE移动上行通信调度算法(ODSSA)
长期演进(LTE)第三代合作伙伴计划(3GPP)是为移动用户设备上的多媒体应用开发的,具有75/300 Mbps的非常高的数据速率和10毫秒的低延迟。上行通信采用SC-FDMA无线接入机制,下行通信采用OFDM接入机制,实现了高数据速率。通过考虑信道特征及其QOS参数,有效地调度用户数据,从而分配资源,使吞吐量最大化,从而进一步提高性能。分组调度程序通过在时间和频率两个维度上分配资源来帮助处理LTE数据流量。在本文中,我们提出了一种新的调度算法,该算法主要关注数据流行为,根据随机用户的信道信噪比条件为其分配最大的资源。然后将其与两种主要关注流水平动态的不同算法——公平固定分配(Fair Fixed Assignment, FFA)和最大附加价值(Maximum added value, MAV)算法进行比较。结果表明,该算法在平均流传输时间方面优于其他两种算法。
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