Research On The Combining Techniques On Joint Reception For Multi-Antenna Signals

Due to the rapid extension of the wireless communication and the troublesome environment for electromagnetic propagation, the received signals become weaker in some applications. It is possible to be in despair even if using maximum antenna apertures and lower receiver noise temperatures such as in Deep Space Network and military communication. Therefore, it is important to pay attention to improve the quality of the received signal at low Signal-to-Noise Ratio level. An effective method for improving the SNR is to combine the signals from several antennas, and it is based on the characteristics about the correlation of the signal component and the non-correlation for noise component. This technique can offer better performance than a single maximum antenna. Forthermore, it holds many possibilities: increased operational robustness, implementation cost saving and more stable and flexible.For the purpose of the general applicability for the received signals and the adoptive equipments, this thesis mainly deals with signal waveform combining techniques on a randomly distributed multi-antenna array, especially about the phase difference estimate, time delay alignments, the combining weight estimate and the combining algorithm in the frequency selective channels among the signals. If taking no account of the different parameters and the channels, the received signals have the same signal component. As a result, it is likely to improve the performance about the parameters'estimation and reduce the combining loss consequently. Based on the fact that the same signal component exists in the received signals, the paper mainly analyzes and makes a deep research on the key techniques of the sample combining, which utilizes multi-antenna signals jointly to realize the more accurate parameter estimates. The main research results include:1,Analyzing phase compensating performance and phase difference characteristics of the combining weight from SUMPLE algorithm in view of parameter estimation, and a modified weight amplitude method based on SUMPLE algorithm is proposed. On the basis of the deep research on the SUMPLE algorithm, the principle that the algorithm can provide lower combining loss for weak signals is explained on account of the compensating phase performance. At the same time, the paper analyses the phase difference characteristics from the combining weight, and the corresponding theoretical performance and the required least antenna number are also derived. Moreover, in order to reduce the adverse effect from the weaker signal for non-uniform signal combining, a modified weight amplitude method is presented. The validity of modified factor is also analyzed. Theoretical analysis and simulation results show that the modified algorithm can obviously reduce the weight amplitude of the weaker signals, improve the arraying combining performance, and favor for confirming the failed antenna.2,A simple algorithm that aligns signals of different arrival times on a randomly distributed antenna array is presented, and the theoretical convergence characteristic is also analyzed. Analyzing the combining performance affected by the time delay estimation error using the matched filter bound in case of only two signals and it is confirmed by simulation relusts using an optimum maximum-likelihood receiver. To align the signals of different arrival times on a randomly distributed antenna array, a new algorithm for time delay alignment based on quasi-combined output as reference is proposed, which is different from most algorithms based on a single fixed reference. The paper also analyzes the convergence characteristic and the application issue in practice. Finally, results show that the algorithm achieves a substantial performance improvement by making use of the array combining output except self-signal as reference to improve the SNR of reference signal and the performance of time delay estimator, especially at low SNR level. Furthermore, the estimatiom performance of the algorithm is better than redundancy fusion algorithm.3,Cramer-Rao lower bounds for the estimation of combining weight of BPSK and QPSK modulated signals are derived, and a blind combining weight estimation algorithm based on the noise autocorrelation is also present. Theoretical results about estimation lower bound show that it is assured to achieve a substantial performance improvement due to the optimal usage of the mutual information between the signals, and reduce the loss of array combining output gain especially at low SNR level. At the same time, aiming at computing the optimum combining weight generally and practically, a blind combining weight estimation algorithm using signals'second order moment with the characteristic of the noise power spectral autocorrelation jointly is proposed, which discards the solely signal's power and SNR. Theoretical analysis and simulations show that the algorithm can be used in many cases, such as unknown signal's SNR, different modulation and signal bandwidth along with frequency offset, and have achieved preferable performance and low computational complexity which are proper for hardware implementation.4,An effective blind combining algorithm is presented to combine the signals at low SNR from multiple antennas without symbol timing synchronization in the frequency selective channels. The combining weights are studied based on matched filter in the frequency selective channels, and the optimum receiver structure is also presented. The combining algorithm can be interpreted as each frequency component for all the received signals varying co-phasing and maximal ratio combining. The combined signal distortion will be reduced besides improving the ratio of signal to noise for each frequency component. It is shown that the algorithm can achieve a substantial performance improvement, and doesn't require the symbol timing synchronization and the signal modulation mode. It could be considered as a useful combining technique, especially when symbol timing synchronization is difficult to realize at low SNR in the frequency selective channels.5,To meliorate adverse effect on the demodulation performance caused by the single channel's nonlinear phase characteristic, an average phase method from all of the branches is proposed. Because the demodulation scheme with Baud Spaced Equalizer after symbol timing synchronization is often used on the assumption of the unknown channel, the reduction about SNR after symbol timing synchronization and equalizer's output performance is analyzed, which is brought by the channel's nonlinear phase characteristic. Different from the fixed single signal, the new phase compensating algorithm utilizes all of the signals from the antenna array, and the resultant phase is converged to the average phase of the signals. As a result, it could improve the characteristic of the phase frequency and overcome the shortcoming from the fixed single method. Moreover, a relative average phase algorithm is also presented to avoid the multivalued phenomenon about the phase difference. Finally the validity of the phase compensating algorithm is affirmed by the simultations.