Next Article in Journal
Hyperspectral Features of Oil-Polluted Sea Ice and the Response to the Contamination Area Fraction
Next Article in Special Issue
Self-Learning Power Control in Wireless Sensor Networks
Previous Article in Journal / Special Issue
A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(1), 229; doi:10.3390/s18010229

A Novel Adaptive Modulation Based on Nondata-Aided Error Vector Magnitude in Non-Line-Of-Sight Condition of Wireless Sensor Network

1
College of Communication Engineering, Chongqing University, Chongqing 400044, China
2
Chongqing Jinmei Communication Co. Ltd., Chongqing 400030, China
*
Author to whom correspondence should be addressed.
Received: 17 November 2017 / Revised: 31 December 2017 / Accepted: 12 January 2018 / Published: 15 January 2018
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
View Full-Text   |   Download PDF [1583 KB, uploaded 15 January 2018]   |  

Abstract

The high demand for multimedia applications in environmental monitoring, invasion detection, and disaster aid has led to the rise of wireless sensor network (WSN). With the increase of reliability and diversity of information streams, the higher requirements on throughput and quality of service (QoS) have been put forward in data transmission between two sensor nodes. However, lower spectral efficiency becomes a bottleneck in non-line-of-sight (NLOS) transmission of WSN. This paper proposes a novel nondata-aided error vector magnitude based adaptive modulation (NDA-EVM-AM) to solve the problem. NDA-EVM is considered as a new metric to evaluate the quality of NLOS link for adaptive modulation in WSN. By modeling the NLOS scenario as the η μ fading channel, a closed-form expression for the NDA-EVM of multilevel quadrature amplitude modulation (MQAM) signals over the η μ fading channel is derived, and the relationship between SER and NDA-EVM is also formulated. Based on these results, NDA-EVM state machine is designed for adaptation strategy. The algorithmic complexity of NDA-EVM-AM is analyzed and the outage capacity of NDA-EVM-AM in an NLOS scenario is also given. The performances of NDA-EVM-AM are compared by simulation, and the results show that NDA-EVM-AM is an effective technique to be used in the NLOS scenarios of WSN. This technique can accurately reflect the channel variations and efficiently adjust modulation order to better match the channel conditions, hence, obtaining better performance in average spectral efficiency. View Full-Text
Keywords: adaptive modulation; nondata-aided error vector magnitude; non-line-of-sight; ημ fading channel; wireless sensor network adaptive modulation; nondata-aided error vector magnitude; non-line-of-sight; ημ fading channel; wireless sensor network
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Yang, F.; Zeng, X.; Mao, H.; Jian, X.; Tan, X.; Du, D. A Novel Adaptive Modulation Based on Nondata-Aided Error Vector Magnitude in Non-Line-Of-Sight Condition of Wireless Sensor Network. Sensors 2018, 18, 229.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top