An Improved Interference Cancellation for WCDMA System

As the wireless communication service is widely used and the demand for wireless repeaters is rapidly increasing because of the easiness of extending service areas. But the interference signals may result in the degradation of the network performance. Adaptive filtering has been a general technique to cancel such interference signals in the communication network. Wideband-Code Division Multiple Access (WCDMA) using the spread-spectrum signaling has gained increased interest for application in communication systems. When the interference signals is detected, one solution to inhibit the divergence of the tap coefficients can be obtained by setting the step size of the adopted adaptive algorithm to zero [1]. In this paper, the Constant Modulus Algorithm and its combined versions with the Normalized LMS algorithm were proposed. We proposed a CMA-NLMS algorithm, which utilizes correlation between the desired and input signals to adjust the step sizes, for canceling the interference signals in the WCDMA system. They commonly have to provide faster convergence than the LMS algorithm with increase of computational complexity and a decrease of Mean Square Error (MSE) performance. Here an NLMS based algorithm is considered. Utilizing an efficient method to calculate the tap input power required in the NLMS algorithm, a small increase of the computational complexity relative to the LMS algorithm is required for updating the filter coefficients in the proposed adaptive algorithm [2]. At the same time, the proposed detector uses the CMA-CNLMS algorithm with two different step size to obtain adaptive and more flexible in multi path environment. In this structure, Errors which are obtained from each group are compared, and a minimum error is chosen to the selection block. The structure has a fast convergence and low mean square error simultaneously [3]. The paper is organized as this paper is as follows. We present basic structure for the proposed adaptive algorithm in chapter 2. Simulation and measurement results will be in chapter 3 and conclusion follows in chapter 4.