In fast-fading channels, the constant modulus algorithm (CMA) is unable to properly track the rime-variations because the magnitude of the received signal changes too rapidly. The Kalman filter (KF), however, works we...
详细信息
In fast-fading channels, the constant modulus algorithm (CMA) is unable to properly track the rime-variations because the magnitude of the received signal changes too rapidly. The Kalman filter (KF), however, works well in time-varying channels but needs a training sequence to operate. Therefore, a combined CMA and KF algorithm is proposed in order to utilise the advantages of both algorithms. The associated step sizes of the CMA and the KF algorithm are also varied in accordance with the magnitude of the output. Simulations are presented to demonstrate the potential of the combination.
The constant modulus algorithm (CMA) is an excellent technique for blind channel equalization. Recently signed error version of CMA (SE-CMA) and dithered signed error version (DSE-CMA,) have been proposed which afford...
详细信息
The constant modulus algorithm (CMA) is an excellent technique for blind channel equalization. Recently signed error version of CMA (SE-CMA) and dithered signed error version (DSE-CMA,) have been proposed which afford overall computational efficiency. We propose three different error functions for faster convergence. This would be essential for communication systems, which cannot afford a high startup delay or for systems, where the channel's impulse response is rapidly fluctuating. One of these algorithms relies on the idea of a variable step size, which increases the rate of convergence.
constant modulus algorithm (CMA) for blind multiuser detection is proposed in [3]. However, the first type of stationary points in [3] is not correct. A general expression for the solutions is given in this paper, whi...
详细信息
constant modulus algorithm (CMA) for blind multiuser detection is proposed in [3]. However, the first type of stationary points in [3] is not correct. A general expression for the solutions is given in this paper, which shows there are many undesired stationary points. Therefore, methods that guarantee CMA to converge to the desired point are needed. We present approximate conditions that set initialization in the lock region. Simulation shows that CMA with variable step size has quicker convergence speed than MOE-RLS, while obtaining better performance.
In this correspondence, we extend the results from Wang and Dowling to provide a low-cost and high performance blind adaptive interference suppression scheme for CDMA systems. Simulation results confirm that the propo...
详细信息
In this correspondence, we extend the results from Wang and Dowling to provide a low-cost and high performance blind adaptive interference suppression scheme for CDMA systems. Simulation results confirm that the proposed algorithm outperforms several existing algorithms, even under the most severe cases of near-far and multipath conditions.
The constantmodulus (CM) criterion coupled with a gradient search helps in the design of fractionally spaced equalizers. Effective implementation of CIM algorithm requires proper choice of the scale factor mu called ...
详细信息
ISBN:
(纸本)0780365143
The constantmodulus (CM) criterion coupled with a gradient search helps in the design of fractionally spaced equalizers. Effective implementation of CIM algorithm requires proper choice of the scale factor mu called the step size and initialization of equalizer coefficients. Experience reveals that these two determine the convergence rate and final misadjustment. Recently Brown et al proposed a computationally efficient algorithm, which is a signed error version of CMA. This paper proposes yet another variation of the same and reports faster convergence. The idea is to use a variable step size, which increases the convergence rare.
Recently, we proposed a model for the steady-state estimation error of real-valued constant-modulus-based algorithms as a function of the a priori error and of a term that measures the variability in the modulus of th...
详细信息
ISBN:
(纸本)9781424414833
Recently, we proposed a model for the steady-state estimation error of real-valued constant-modulus-based algorithms as a function of the a priori error and of a term that measures the variability in the modulus of the transmitted signal. In this paper, we extend this model to complex-valued data and use it in conjunction with the feedback analysis method to obtain an analytical expression for the steady-state excess mean-square error (EMSE) of the constant modulus algorithm (CMA). Such expression is more accurate for larger step-sizes than the previous ones in the literature, as confirmed by the good agreement between analytical and simulation results. Furthermore, from the EMSE expression, we obtain an estimate for the CMA step-size interval to ensure its convergence and stability, when it is initialized sufficiently close to the zero-forcing solution.
One of the most popular algorithms for blind equalization is the constant modulus algorithm (CMA), due to its simplicity and low computational cost. However, if the step-size is not properly chosen or if the initializ...
详细信息
ISBN:
(纸本)9781424414833
One of the most popular algorithms for blind equalization is the constant modulus algorithm (CMA), due to its simplicity and low computational cost. However, if the step-size is not properly chosen or if the initialization is distant from the optimal solution, CMA can diverge or converge to undesirable local minima. In order to avoid divergence, we propose a dual-mode algorithm, which works as CMA with a time-variant step-size, but rejects non-consistent estimates of the transmitted signal. We present a deterministic analysis of the stability of the new algorithm for scalar filters. In the vector case, the good performance of the new algorithm is confirmed through numerical simulations.
The constant modulus algorithm (CMA), a popular method for performing blind equalization, has the drawback of failing when the input data has a Gaussian distribution or a kurtosis larger than three, This means that so...
详细信息
The constant modulus algorithm (CMA), a popular method for performing blind equalization, has the drawback of failing when the input data has a Gaussian distribution or a kurtosis larger than three, This means that source shaping (which is used to increase the shaping gain) can produce data unequalizable by CMA and other important blind equalization techniques. This paper proposes a simple extension of CMA that blindly equalizes many types of shaped constellations, including those shaped by shell mapping.
In MIMO-OFDM networks, the main drawback includes the large peak-to-average power ratio (PAPR) of the transmitter's output signal on different antennas. In order to overcome this issue, PAPR is reduced using IDCT ...
详细信息
ISBN:
(纸本)9781479970025
In MIMO-OFDM networks, the main drawback includes the large peak-to-average power ratio (PAPR) of the transmitter's output signal on different antennas. In order to overcome this issue, PAPR is reduced using IDCT in this paper. In this technique, Inverse Discrete Cosine Transform (IDCT) along with constant modulus algorithm is used to reduce the PAPR in MIMO-OFDM networks. It involves two methods, first the time domain signal from the Resource Block is combined linearly using pre-coding weights which is transparent to the receiver side. Then the precoding weights are modified to decrease the modulus variations of the resulting signal, which leads to the reduction of PAPR in MIMO OFDM. By simulation results, it is observed that the proposed technique reduces PAPR.
The constant modulus algorithm (CMA) is commonly used for first stage blind equalization applications. CMA's main advantage is that it will open the eye based on the received signal only. Decision directed (DD) eq...
详细信息
ISBN:
(纸本)0780374029
The constant modulus algorithm (CMA) is commonly used for first stage blind equalization applications. CMA's main advantage is that it will open the eye based on the received signal only. Decision directed (DD) equalization is often used as it provides a lower mean square error (MSE) in the equalized signal. Obvious from its name, DD equalization requires estimates of the transmitted symbols in order to adapt the equalizer - the eye must be open. This paper considers an elegant method to transition between CMA and DD equalization (in a decision feedback equalizer structure). A conventional "brute force" approach to perform the transition is to determine the filter coefficients for the DD equalizer through a MMSE design criterion based on the inverse CMA filter coefficients. This may cause a large procession delay at the point of transition between filter types and requires significant computations. The algorithm in this paper is low complexity and does not require a large processing delay when transitioning from CMA to DD LMS.
暂无评论