Revisiting Smart Antenna Array Design for Multiple Interferers with Some
Useful Adaptive Beamforming Algorithms: Comparative Performance Study
Abstract
Smart antennas are becoming popular in the cellular wireless
communication for capacity enhancement while reducing multipath effect
and interference from undesired direction and to be useful for both base
station and mobile handset antennas. The demands for smart antenna is
even increasing widely as 5G cellular communication evolves to support
higher data speed and bandwidth. The fundamental principle of smart
antenna design is the adaptive beamforming using any best suited
adaptive algorithm such as Least Mean Square (LMS), Normalized Least
Mean Square (NLMS), Sample Matrix Inversion (SMI) and Recursive Least
Square (RLS) each having its own pros and cons. Among the four, the LMS
and NLMS are iterative approaches while SMI is block adaptive and RLS is
a recursive method. Though there are many discrete research works using
these algorithms, but comprehensive investigations considering all for
smart antenna design is not available to the best of our knowledge.
Thus, in this paper, exhaustive comparative performance studies of LMS,
NLMS, SMI, RLS are performed in antenna array beamforming with multiple
interference rejection using null steering. The contribution of this
paper includes implementation methods of adaptive beamforming algorithms
in presence of multiple interferers through flow charts illustration.
Then exhaustive comparative results are analyzed for all four algorithms
in terms of beamwidth, null depth, maximum sidelobe level, rate of
convergence and error variation with respect to number of antenna
elements and spacing. Finally, a comparative look up table is prepared
which observes the pros and cons of all the algorithms listed. This
paper will be a good ready reference for researcher in smart antenna
design using these adaptive algorithms.