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Enhanced RLS in Smart Antennas for Long Range Communication Networks
- Source :
- ANT/SEIT, ICACCI
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- The utilisation of smart antenna (SA) techniques in future wireless and cellular networks is expected to have an impact on the efficient use of the spectrum and the optimization of service quality. This is because SAs can enhance the maximization of output power of the signal in desired directions amongst a whole lot of functions. In spite of these benefits of SAs, long range communications still face unsolved challenges such as signal fading. Therefore, this paper focuses on enhancing the recursive least squares (RLS) in SA design for long range communication networks. The conventional RLS algorithm does not need any matrix inversion computations because the inverse correlation matrix is determined directly. Therefore, the RLS saves computational power. Hence, we have enhanced the RLS algorithm by introducing a constant m to the gain factor in order to yield an improved gain vector. Results obtained from our simulations show that the enhanced RLS reduces mean square error (MSE), smoothens filter output and improves SNR when compared to the conventional methods. These benefits further result in antenna the gain improvement leading to an increased range and directivity of the smart antenna over a long range communication networks.
- Subjects :
- 0301 basic medicine
Recursive least squares filter
Mean squared error
business.industry
Computer science
Smart antenna
Directivity
03 medical and health sciences
030104 developmental biology
0302 clinical medicine
030220 oncology & carcinogenesis
Cellular network
Electronic engineering
General Earth and Planetary Sciences
Wireless
Fading
business
General Environmental Science
Subjects
Details
- ISSN :
- 18770509
- Volume :
- 130
- Database :
- OpenAIRE
- Journal :
- Procedia Computer Science
- Accession number :
- edsair.doi.dedup.....db804dcefa10e43056eea428b2a32207
- Full Text :
- https://doi.org/10.1016/j.procs.2018.04.030