# An Adaptive filtering algorithm and its application to adaptive beamforming in spread-spectrum systems for interference rejection

Abstract (Summary)

Adaptive array and spread-spectrum techniques are widely used for the suppression of interference in many communications applications. In this dissertation, an improved adaptive filtering algorithm is investigated to synthetically overcome some of the problems associated with the conventional least-mean-square (LMS) algorithm, which requires generating a reference signal, and is not effective in coherent interference rejection. The results for the modified LMS algorithm, which we call the ZMS algorithm in this work, shows several advantages over the conventional LMS algorithm including:(1) reference signal generation is not required,(2) input interference signals are not required to be uncorrelated with the desired target signal, (3) convergence range is independent of the desired signal power, and (4) it converges rapidly and achieves small mean-square error. The primary characteristics of the ZMS algorithm are the elimination of the reference signal in the weight control loop and the decorrelation of the interference signal from the array input signal, by separating them using spatial or frequency filtering prior to adaptive minimization procedure. Two types of ZMS beamformers were investigated and simulated: the FIR notch filtered ZMS beamformer (FIR-ZMS) and the spatial notch filtered ZMS beamformer (SP-ZMS). Simulation results confirm the theoretical predictions of the ZMS algorithm for the rejection of coherent and/or non-coherent interference. It is shown that the ZMS algorithm achieves rapid convergence and small mean-square error in comparison with the LMS algorithm. Even in worst case situations where the desired signal information is not available and the interference is at the same frequency as the target signal, the SP-ZMS beamformer effectively rejects the coherent interference and reproduces the desired target signal. The FIR-ZMS beamformer is not effective in a worst case coherent jammer scenario. Signal leakage out of the input notch filter in the ZMS algorithm results in degradation of the array performance. Simulations are given to show this. A combination of the ZMS adaptive beamforming and the frequency-hop spread-spectrum techniques is considered, providing more effective rejection of interferences. The effectiveness of the combined system is improved by using adaptive beamforming to null the jammer, which results in the jammer power being maintained at a level less than the signal power at the front end of receiver prior to despreading the frequency-hop signal. Analysis shows that for a given system processing gain of the spread-spectrum system, the main variable affecting the performance is the jammer-to-signal power ratio (JSR). It is shown that when the multiple jammer powers are rejected down to a level less than the target signal power by the adaptive nulling technique, the theoretical probability of error for detecting the target signal becomes zero. However, in practice the array performance in a frequency-hop signal environment is largely dependent on the convergence speed of the adaptive algorithm used and on the frequency-hop rate. The FIR filter in the ZMS algorithm implementation is simulated to investigate the filter performance for decorrelating the target signal from the interference signal. Simulation results confirm that the performance of an FIR filter is largely dependent on the number of tap coefficients implemented, and that the window function is useful in suppressing high side lobe ripples in the filter response. Simulation results for a tap-switching algorithm using programmable FIR filter are shown to be effective in rejection or reception of the signal in a changing environment. This is due to the fact that the filter transfer function can be adaptively updated by adjusting only the tap coefficients without need of structure modification.
Bibliographical Information:

Advisor:

School:Ohio University

School Location:USA - Ohio

Source Type:Master's Thesis

Keywords:adaptive filtering algorithm beamformers spread spectrum systems interference rejection

ISBN:

Date of Publication:01/01/1987