Analysis of quantization effects on performance of hierarchical cooperation schemes in Ad-hoc wireless networks

S. P. Shariatpanahi, B. Khalaj
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引用次数: 2

Abstract

In this paper, we analyze the role of the number of quantization bits on the third phase of the hierarchical cooperation scheme proposed by Ozgur et al. in 2007. The hierarchical cooperation scheme has a digital architecture and requires quantization of MIMO (Multiple-Input Multiple-Output) observations in the third phase. The choice of the number of quantization bits Q has direct effect on the pre-constant factor of the network throughput. By increasing the number of quantization bits, the MIMO capacity in the second phase increases at the expense of higher computational complexity of the third phase. We investigate such trade-off and show that there is an optimum number of quantization bits which maximizes the throughput. In addition, it will be shown that due to quantization noise, it is not possible to increase throughput pre-constant factor as large as desired by increasing transmit power. As a result, there is a saturation value for the pre-constant value. Finally, we will demonstrate that by proper scaling of Q as Q = β log(SNR) for any β independent of SNR, an increasing pre-constant factor of order √log(SNR) can be achieved.
自组织无线网络中分层协作方案的量化影响分析
在本文中,我们分析了量化比特数在Ozgur等人于2007年提出的分层合作方案的第三阶段中的作用。分层合作方案具有数字架构,并要求在第三阶段对MIMO(多输入多输出)观测进行量化。量化比特数Q的选择直接影响到网络吞吐量的预常数系数。通过增加量化比特数,第二阶段的MIMO容量增加,但代价是第三阶段的计算复杂度增加。我们研究了这种权衡,并表明存在最大吞吐量的最佳量化比特数。此外,由于量化噪声,不可能通过增加发射功率来增加吞吐量预常数因子。因此,对于预常数值存在一个饱和值。最后,我们将证明,通过适当缩放Q为Q = β log(SNR),对于任何独立于SNR的β,可以实现增加阶√log(SNR)的预常数因子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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