Internet utility evaluation of a multi-start particle swarm optimization beamformer in a partial joint processing cellular network

A. Faisal, F. Hashim, M. Ismail, N. Noordin
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Abstract

Joint processing (JP) is a powerful mechanism in alleviating inter-cell interference (ICI) and maximizing data rate of cell-edge users. However, JP puts tremendous load on both feedback and backhaul overhead, thus partial JP was proposed to overcome high overhead signaling. Unlike linear techniques such as zero-forcing (ZF), achieving an equivalent backhaul reduction and presenting a totally free ICI system based on limited feedback channel state information can be done by designing and implementing a multi-start particle swarm optimization algorithm (MSPSOA) as a beamforming (BF) mechanism. The performance of the proposed MSPSOA and ZF BF is evaluated based on the acquired spectral efficiency and utility of internet application such as hard real-time, adaptive and elastic applications. The simulation results shows that, the proposed MSPSOA BF achieves spectral efficiency up to 69.5% compared to ZF BF, and it maintains total utility for high data rate requirements of three common internet traffic such as hard real-time, adaptive and elastic applications.
部分联合处理蜂窝网络中多起点粒子群优化波束形成器的互联网效用评价
联合处理(JP)是一种有效缓解小区间干扰和最大化小区边缘用户数据速率的机制。然而,JP给反馈开销和回程开销都带来了巨大的负载,因此提出了部分JP来克服高开销信令。与零强迫(zero-forcing, ZF)等线性技术不同,基于有限反馈信道状态信息的等效回程减少和完全自由的ICI系统可以通过设计和实现多启动粒子群优化算法(MSPSOA)作为波束形成(BF)机制来实现。基于获取的频谱效率和硬实时、自适应和弹性等互联网应用的实用性,对所提出的MSPSOA和ZF BF的性能进行了评估。仿真结果表明,与ZF BF相比,所提出的MSPSOA BF的频谱效率高达69.5%,对于硬实时、自适应和弹性等三种常见互联网流量的高数据速率要求保持总体实用。
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