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Handoff algorithms in dynamic spreading WCDMA system supporting multimedia traffic

机译:支持多媒体业务的动态扩展WCDMA系统中的切换算法

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摘要

The undergoing third-generation wireless network needs to support the integration of voice and multimedia data services with varying quality-of-service (QoS) requirements. It is critical that the least bit-error rate (BER) for voice traffic, World Wide Web (WWW) traffic, and streaming video traffic be guaranteed at all time. In this paper, we discussed the integration of soft handoff and dynamic spreading factor in wideband code-division multiple-access system in supporting multimedia traffic. The contribution of our work is twofold. First, the processing time of the handoff request is analyzed. We found that intensive mobile handoff might consume significant amount of access channel time and increase the delay of handoff. We, therefore, proposed a batch mechanism such that multiple handoff requests could be processed simultaneously. The average delay is reduced from 1.12 s to 800 ms at heavy handoff rate. Our second contribution is a new resource allocation algorithm, where the spreading factor and transmission power for the handoff mobiles are jointly considered to maximize the throughput. The BER requirements for the handoff mobiles and the target cell are maintained during the handoff process. The original problem is formulated into a nonlinear programming format. We proposed a procedure to simplify it into a linear constraint problem, which is solved by a revised simplex method. Numerical results show a 25% increase in throughput for WWW traffic and a 26% improvement for the video traffic.
机译:正在进行的第三代无线网络需要支持具有变化的服务质量(QoS)要求的语音和多媒体数据服务的集成。始终确保语音流量,万维网(WWW)流量和流视频流量的最小误码率(BER)是至关重要的。在本文中,我们讨论了在支持多媒体业务的宽带码分多址系统中软切换和动态扩频因子的集成。我们工作的贡献是双重的。首先,分析切换请求的处理时间。我们发现密集的移动切换可能会消耗大量的访问信道时间并增加切换延迟。因此,我们提出了一种批处理机制,使得可以同时处理多个切换请求。在较大的切换速率下,平均延迟从1.12 s减少到800 ms。我们的第二个贡献是一种新的资源分配算法,其中结合考虑了切换移动台的扩展因子和传输功率,以最大化吞吐量。在越区切换过程中,维持对越区移动台和目标小区的BER要求。最初的问题被表述为非线性编程格式。我们提出了将其简化为线性约束问题的过程,该问题可以通过修改后的单纯形法来解决。数值结果表明,WWW流量的吞吐量提高了25%,视频流量的吞吐量提高了26%。

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