TY - JOUR
T1 - BER of adaptive arrays in AWGN channel
AU - Huang, Zhiyong
AU - Balanis, Constantine
N1 - Funding Information:
Manuscript received December 19, 2007; revised March 14, 2008. Published July 7, 2008 (projected). This work was supported by the National Science Foundation under Grant 0355255. The authors are with the Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287-5706 USA (e-mail: zhiyong.huang@asu.edu and balanis@asu.edu). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TAP.2008.924764
PY - 2008/7
Y1 - 2008/7
N2 - A system model is presented of adaptive arrays with trellis coded modulation (TCM) to investigate the bit-error-rate (BER) of a wireless system in a co-channel interference environment. Adaptive arrays with different geometries, uniform circular array (UCA), uniform rectangular array (URA) and UCA with center element (UCA-CE), are implemented with the least mean square (LMS) algorithm to combat interference at the same frequency. The wireless systems are investigated in well-separated signals and random direction signals scenarios with additive white Gaussian noise. The URA and UCA-CE have faster convergence and their BERs, in some cases, are slightly influenced by the number of interferers. However, although the UCA converges slowly and its performance degrades as the number of interferers increases, it generally has the best BER. The recursive least square (RLS) algorithm is also investigated. It achieves much better performance than the LMS algorithm when the training sequences are short. However, the optimum BERs attained by these two algorithms are the same.
AB - A system model is presented of adaptive arrays with trellis coded modulation (TCM) to investigate the bit-error-rate (BER) of a wireless system in a co-channel interference environment. Adaptive arrays with different geometries, uniform circular array (UCA), uniform rectangular array (URA) and UCA with center element (UCA-CE), are implemented with the least mean square (LMS) algorithm to combat interference at the same frequency. The wireless systems are investigated in well-separated signals and random direction signals scenarios with additive white Gaussian noise. The URA and UCA-CE have faster convergence and their BERs, in some cases, are slightly influenced by the number of interferers. However, although the UCA converges slowly and its performance degrades as the number of interferers increases, it generally has the best BER. The recursive least square (RLS) algorithm is also investigated. It achieves much better performance than the LMS algorithm when the training sequences are short. However, the optimum BERs attained by these two algorithms are the same.
KW - Adaptive array
KW - Additive white Gaussian noise (AWGN)
KW - Bit-error-rate (BER)
KW - Least mean square (LMS)
KW - Recursive least square (RLS)
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U2 - 10.1109/TAP.2008.924764
DO - 10.1109/TAP.2008.924764
M3 - Article
AN - SCOPUS:47249135043
SN - 0018-926X
VL - 56
SP - 2089
EP - 2097
JO - IEEE Transactions on Antennas and Propagation
JF - IEEE Transactions on Antennas and Propagation
IS - 7
ER -