Improvement Of DOA Estimation Method And Genetic Composite Beamforming On Smart Antennas

In recent years, smart antenna technology has become the research hot point in communication field. It takes advantage of spatial diversity ability to increase channel capacity, improve spectrum efficiency and enlarge cover area, which improve system performance largely. So these special advantages make smart antenna become the key technology of beyond 3G and 4G.Beamforming stems from smart antenna, with increasing desire signal and suppressing interference as its technical superiority, which is also the foundation for the realization of SDMA. In wideband wireless communication, the number of interference is usually larger than that of antenna array elements. Therefore, optimization of antenna array pattern synthesis is a problem of non-linear multiobjective and multiparameter optimization. Genetic Algorithms (GA) have outstanding advantages in such case. However, the traditional GA-based methods for beamforming are usually with high complexity and unstable convergence. The paper proposed a GA-based composite beamforming method. In comparison with traditional methods, the proposed method has lower computation, stronger convergence stability and faster speed.Firstly, this paper introduces elementary concepts of smart antenna, analyzes and compares the performances of conventional smart antenna beamforming algorithms. At the same time, some methods for smart antenna DOA estimation are discussed and compared. Finally, elementary concepts and implementation methods of GA are introduced. All of these provide enough theoretical basis for the combination of GA and beamforming.In GA-based beamforming methods, the DOAs of coherent singals need to be estimated accurately. This paper proposes and optimizes some DOA estimation methods of coherent singals. Firstly, we propose a new simple weighted forward-backward spatial smoothing-SWFBSS, which spatially smoothes diagonal sub-matrixes of covariance matrix by weighted forward and backward method to de-correlate the coherent sources perfectly. Secondly, we optimize WFSS (weighted forward spatial smoothing) algorithm to decrease its computational amount to half. Finally, we improve and optimize WFBSS(weighted forward backward spatial smoothing). Through mathematical deduction, we obtain the simple relationship of conjugate permutation between the two parts of covariance matrix processed by WFBSS. This property can help to reduce half of the total computational amount. These three methods can discriminate the near coherent signals under low SNR. Moreover, the forward backward spatial smoothing methods can decrease the aperture loss of antenna array.In the GA-based composite beamforming methods, we need to know the DOA of signals as well as those relative mulit-path energies to perform interference suppressing assignment scheme. For multi-user coherent sources, this paper proposes a method to estimate the relative multi-path energy. In this method, spatial eigenvectors and DOAs of signals are obtained by the spatial signature algorithm based on cumulant and the proposed weighted spatial smoothing algorithms, then the relative multi-path energy of each user are estimated by matrix inversing operation. To enhance the stability of algorithm, LS (least squares) and TLS (total least squares) are introduced.GA-based beamforming has obvious advantages in the multi-object, multi-parameter and nonlinear optimization of antenna topology. This paper proposes a GA-based composite algorithm, which divides the antenna elements into two parts, one sub-array suppressing interferences and the other lowering side lobes. The final antenna topology is obtained by multiplying antenna topologies of both sub-arrays. Both theoretical analysis and simulation show the composite algorithm has low complexity of computation, fast convergence and reliable stability.