Constant Modulus Algorithm

An adaptive Analytical Simplified Constant Modulus Algo- rithm (adaptive-ASCMA) which accomplishes blind source separation and carrier phase recovery is proposed. This algo- rithm is applied on Multiple Input Multiple Output (MIMO) communication systems and uses some analytical methods to minimize the Simplified Constant Modulus (SCM) cost func- tion. A study was done to find the subspace containing the solution of

Blind equalization is a technique for adaptive equalization of a communication channel without the aid of the usual training sequence. Although the Constant Modulus Algorithm (CMA) is one of the most popular adaptive blind equalization algorithms, it suffers from slow convergence rate. A novel enhanced blind equalization technique based on a supervised CMA (S-CMA) is proposed in this paper. The technique is employed to initialize the coefficients of a linear transversal equalizer (LTE) filter in order to provide a fast startup for blind training. It also presents a computational study and simulation results of this newly proposed algorithm compared to other CMA techniques such as conventional CMA, Normalized CMA (N-CMA) and Modified CMA (M-CMA). The simulation results have demonstrated that the proposed algorithm has considerably better performance than others.

Blind equalization is an important technique
amongst equalization family. A Multimodulus
algorithm based on blind equalization removes
the undesirable effects of ISI and cater ups the
phase issues, saving the cost of rotator at the
receiver end. In this paper a new algorithm
combination of recursive least square and
Multimodulus algorithm named as RLSMMA is
proposed by providing few assumption, fast
convergence and minimum Mean Square Error
(MSE) is achieved. Excellence of this technique
is shown in the simulations presenting MSE
plots and the resulting filter results.

alise em regime. Abstract— Recently, an affine combination of two least mean- square (LMS) adaptive filters was proposed and its transient performance analyzed. This method combines linearly the out- puts of two LMS filters operating in parallel with different step- sizes. The purpose of the combination is to obtain an LMS adaptive filter with fast convergence and reduced steady-stat e

Experimental performances of blind adaptive training algorithms have been evaluated in real-time WiMax (3.5 GHz) radio channels in this paper. Inter symbol interference (ISI) cancellation and mean square error (MSE) performances of the most commonly used blind equalization techniques, constant modulus algorithm (CMA), and CMA based modified CMA (M-CMA) and normalized CMA (N-CMA) algorithms are investigated in study.

This paper proposes a new approach to the analysis of the steady-state performance of constant modulus algorithms (CMA), which are among the most popular adaptive schemes for blind equalization. A major feature of the proposed feedback approach is that it bypasses the need for working directly with the weight error covariance matrix. In so doing, approximate expressions for the steady-state mean-square error of several CM algorithms are derived, including CMA2-2, CMA1-2, normalized CMA, and a new normalized CMA variant with less bias. A comparison among the various algorithms is also performed, along with several simulation results. The conclusions confirm the superior performance of CMA2-2

2618 Abstract—In this paper the behavior of the decision feedback equalizers (DFEs) adapted by the decision-directed or the constant modulus blind algorithms is presented. An analysis of the error surface of the corresponding criterion cost functions is first developed. With the intention of avoiding the ill-convergence of the algorithm, the paper proposes to modify the shape of the cost function error surface by using a soft decision instead of the hard one. This was shown to reduce the influence of false decisions and to smooth the undesirable minima. Modified algorithms using the soft decision during a pseudo-training phase with an automatic switch to the properly tracking phase are then derived. Computer simulations show that these modified algorithms present better ability to avoid local minima than conventional ones.

Recently a dithered signed-error constant modulus algorithm (DSE-CMA) has been proposed for the purpose of low complexity implementation of constant modulus algorithm (CMA), which is widely used for blind adaptive filtering due to its LMS-like desirable robustness properties. Despite the fact that this algorithm has robustness properties closely resembling those of CMA, it is very slow in convergence. In this work, we present a simple modification of DSE -CMA using a variable step size that results in faster convergence while preserves the low computational complexity and robustness properties of the DSE-CMA algorithm.

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

Adaptive antenna array systems have played a central role in removing narrowband multiple-access interference (MAI) in wireless communications. However, due to the actual need for increasing channel capacity, the required bandwidth is becoming wider and can bring significant deteriorations of the narrowband adaptive systems. These performance degradations are mainly caused by the fact that the inter-element phase shift becomes a function of the frequency while the adaptation weights are kept independent of frequency. To compensate the effect of the inter-element phase variations, a new approach called the interpolated constant modulus algorithm (ICMA) is introduced. The system is based on an interpolation technique used in conjunction with the constant modulus algorithm (CMA). Results, both analytical and experimental, showing the performance of the system with and without compensation are given and discussed on the basis of the gain-array patterns