Smart Antenna System in a CDMA Mobile Communication
An alternative way of adaptive beamforming is presented in this paper. The main contribution of the new technique is in its simplicity with a minimal loss of accuracy. Total computational load for computing a suboptimal weight vector from each new signal vector is about It can further be reduced down to (3 ) by approximating the autocorrelation matrix with the instantaneous signal vector at each snapshot. The required condition on the adaptive gain for the proposed algorithm to converge is derived analytically. The proposed beamforming algorithm is applied to the base station of a code-division-multiple access (CDMA) mobile communication system. The performance of the proposed method is shown in multipath fading communication channels in terms of the signal-to-interference + noise ratio (SINR), the bit error rate (BER), and the achievable capacity of a given CDMA cell/sector.
the problem of designing an adaptive antenna array using the second-order statistics of the received signal. The objective is to find a weight vector that provides an appropriate beam pattern to each subscriber in a given cell/sector of a mobile communication system. The new technique utilizes the Lagrange formula to compute the weight vector of the array in an iterative manner. The weight vector computed by the proposed method produces a suboptimal [5] beampattern that generates its maximum gain along the direction of the target subscriber. The gain toward each interferer is relatively much lower. In order to handle the subscribers operating in a given cell/sector, the smart antenna system proposed in this paper consists of beamforming, modules each of which provides the suboptimal beampattern selectively to the corresponding subscriber. It has been shown in [5] that the eigenvector corresponding to the maximum eigenvalue of the autocovariance matrix of the received signal is approximately equal to the steering vector of the target signal source when the target signal is much stronger than each of the interferers at the receiver. (This eigenvector will be referred to as the “maximum eigenvector” in this paper.) The proposed technique is inherently appropriate for the code division multiple access (CDMA) communication system because, in a CDMA system, the desired signal becomes stronger than each interferer after the chip correlation by a factor of the processing gain with the aid of a good performance in power control and chip code synchronization. It is important to observe that the proposed method computes a suboptimal weight vector that does not null out the interferers. In other words, the beampattern provided by the proposed technique simply maximizes the gain along the direction of the desired signal source. Since the proposed technique generates the weight vector in the signal subspace, the beamforming procedure presented in this paper is valid whether or not the number of antenna elements is greater than that of interferers. Note that the number of interferers in a normal CDMA signal environment is at least in the order of tens and it is never realistic to have that many antenna elements in the cell site of a given mobile communication system. It means that the conventional arrays based on the nulling procedure or higher-order-statistics are unlikely to be applicable in practical CDMA mobile communications even if their beamforming procedure is valid for coherent interferers.
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A Novel Adaptive Beamforming Algorithm for a Smart Antenna System in a CDMA Mobile Communication Environment