Abstract
We consider the application of distributed space-time coding in wireless sensor networks (WSNs). In particular, sensors use a common noncoherent distributed space-time block code (DSTBC) to forward their local decisions to the fusion center (FC) which makes the final decision. We show that the performance of distributed space-time coding is negatively affected by erroneous sensor decisions caused by observation noise. To overcome this problem of error propagation, we introduce censored distributed space-time coding where only reliable decisions are forwarded to the FC. The optimum noncoherent maximum-likelihood and a low-complexity, suboptimum generalized likelihood ratio test (GLRT) FC decision rules are derived and the performance of the GLRT decision rule is analyzed. Based on this performance analysis we derive a gradient algorithm for optimization of the local decision/censoring threshold. Numerical and simulation results show the effectiveness of the proposed censoring scheme making distributed space-time coding a prime candidate for signaling in WSNs.
Highlights
In recent years, wireless sensor networks (WSNs) have been gaining popularity in a wide range of military and civilian applications such as environmental monitoring, health care, and control
We have considered the application of noncoherent distributed space-time block code (DSTBC) in WSNs
We have introduced censoring as an efficient method to overcome the negative effects of erroneous local sensor decisions on the performance of the noncoherent DSTBC
Summary
Wireless sensor networks (WSNs) have been gaining popularity in a wide range of military and civilian applications such as environmental monitoring, health care, and control. Obtaining any form of CSI may not be feasible in large-scale WSNs and cheap sensors make phase synchronization challenging To avoid these problems, simple ON/OFF keying and corresponding fusion rules were considered in [9]. We consider noncoherent distributed spacetime block coding for transmission of censored sensor decisions in WSNs. In particular, we make the following contributions. (vi) Our numerical and simulation results show the effectiveness of the proposed transmission scheme and the ability of the noncoherent DSTBC to achieve a diversity gain in WSNs. This paper is organized as follows. And j −1 denote the Gaussian Q-function, the X ×X identity matrix, the X × Y all zeros matrix, and the imaginary unit, respectively
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
