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协作虚拟 MIMO 系统在无线传感器网络中的性能分析。

Performance analysis of cooperative virtual MIMO systems for wireless sensor networks.

机构信息

Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1142, New Zealand.

出版信息

Sensors (Basel). 2013 May 28;13(6):7033-52. doi: 10.3390/s130607033.

DOI:10.3390/s130607033
PMID:23760087
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3715254/
Abstract

Multi-Input Multi-Output (MIMO) techniques can be used to increase the data rate for a given bit error rate (BER) and transmission power. Due to the small form factor, energy and processing constraints of wireless sensor nodes, a cooperative Virtual MIMO as opposed to True MIMO system architecture is considered more feasible for wireless sensor network (WSN) applications. Virtual MIMO with Vertical-Bell Labs Layered Space-Time (V-BLAST) multiplexing architecture has been recently established to enhance WSN performance. In this paper, we further investigate the impact of different modulation techniques, and analyze for the first time, the performance of a cooperative Virtual MIMO system based on V-BLAST architecture with multi-carrier modulation techniques. Through analytical models and simulations using real hardware and environment settings, both communication and processing energy consumptions, BER, spectral efficiency, and total time delay of multiple cooperative nodes each with single antenna are evaluated. The results show that cooperative Virtual-MIMO with Binary Phase Shift Keying-Wavelet based Orthogonal Frequency Division Multiplexing (BPSK-WOFDM) modulation is a promising solution for future high data-rate and energy-efficient WSNs.

摘要

多输入多输出 (MIMO) 技术可用于在给定误码率 (BER) 和传输功率的情况下提高数据速率。由于无线传感器节点的小尺寸、能量和处理限制，相对于真正的 MIMO 系统架构，协作虚拟 MIMO 被认为更适用于无线传感器网络 (WSN) 应用。最近已经建立了具有垂直贝尔实验室分层空时 (V-BLAST) 复用架构的虚拟 MIMO，以提高 WSN 的性能。在本文中，我们进一步研究了不同调制技术的影响，并首次分析了基于 V-BLAST 架构的多载波调制技术的协作虚拟 MIMO 系统的性能。通过使用真实硬件和环境设置的分析模型和仿真，评估了多个具有单个天线的协作节点的通信和处理能耗、误码率、频谱效率和总延迟。结果表明，具有二进制相移键控-基于小波的正交频分复用 (BPSK-WOFDM) 调制的协作虚拟-MIMO 是未来高数据速率和高能效 WSN 的有前途的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/5c21c248fd23/sensors-13-07033f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/a6daf842bcf5/sensors-13-07033f1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/a21ab47766dd/sensors-13-07033f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/68c8b3230f64/sensors-13-07033f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/28f192c15020/sensors-13-07033f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/0e300bffdc22/sensors-13-07033f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/d47ee8e651b2/sensors-13-07033f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/71a214621ad6/sensors-13-07033f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/31e5c9a72954/sensors-13-07033f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/5c21c248fd23/sensors-13-07033f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/a6daf842bcf5/sensors-13-07033f1a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/a21ab47766dd/sensors-13-07033f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/68c8b3230f64/sensors-13-07033f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/28f192c15020/sensors-13-07033f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/0e300bffdc22/sensors-13-07033f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/d47ee8e651b2/sensors-13-07033f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/71a214621ad6/sensors-13-07033f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/31e5c9a72954/sensors-13-07033f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a597/3715254/5c21c248fd23/sensors-13-07033f9.jpg

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