%0 Journal Article %1 noauthororeditor %A Djouani, Peter Chuku Thomas Olwal Karim %D 2018 %J International Journal on AdHoc Networking Systems (IJANS) %K Smart adaptive antennas arrays arrival direction of %N 1 %P 13 %R 10.5121/ijans.2018.8101 %T Adaptive Array Beamforming Using an Enhanced RLS Algorithm %U http://aircconline.com/ijans/V8N1/8118ijans01.pdf %V 8 %X In recent times, the use of Smart antennas (SA) in wireless communications has greatly increased; this is because of their ability to increase the coverage and capacity of a network. There are two main functions which SAs perform: direction of arrival (DOA) and beamforming. SAs are able to produce the main beams towards a desired user and at the same time, form nulls in the direction of interfering signals. They are able to achieve this by the use of beamforming algorithms. The performance of an enhanced Recursive Least Squares (RLS) algorithm which takes into account an enhanced gain factor of the RLS algorithm is evaluated in this paper for adaptive array beamforming. Simulation results show that the enhanced RLS reduces mean square error (MSE), smoothens filter output improves SNR;thus, improving the gain of the RLS algorithm. The result of this work will lead to an increased range of beamforming and directivity of the smart antenna over a long range communication network.

@article{noauthororeditor, abstract = {In recent times, the use of Smart antennas (SA) in wireless communications has greatly increased; this is because of their ability to increase the coverage and capacity of a network. There are two main functions which SAs perform: direction of arrival (DOA) and beamforming. SAs are able to produce the main beams towards a desired user and at the same time, form nulls in the direction of interfering signals. They are able to achieve this by the use of beamforming algorithms. The performance of an enhanced Recursive Least Squares (RLS) algorithm which takes into account an enhanced gain factor of the RLS algorithm is evaluated in this paper for adaptive array beamforming. Simulation results show that the enhanced RLS reduces mean square error (MSE), smoothens filter output improves SNR;thus, improving the gain of the RLS algorithm. The result of this work will lead to an increased range of beamforming and directivity of the smart antenna over a long range communication network. }, added-at = {2018-02-01T10:43:00.000+0100}, author = {Djouani, Peter Chuku Thomas Olwal Karim}, biburl = {https://www.bibsonomy.org/bibtex/280fcb006740e15cf147e3f26f6f992fb/micaelam}, doi = {10.5121/ijans.2018.8101}, interhash = {1cad43f3861e1b6387ddc7785053d85c}, intrahash = {80fcb006740e15cf147e3f26f6f992fb}, journal = {International Journal on AdHoc Networking Systems (IJANS)}, keywords = {Smart adaptive antennas arrays arrival direction of}, month = {January}, number = 1, pages = 13, timestamp = {2018-02-01T10:43:00.000+0100}, title = {Adaptive Array Beamforming Using an Enhanced RLS Algorithm}, url = {http://aircconline.com/ijans/V8N1/8118ijans01.pdf}, volume = 8, year = 2018 }