Constrained Least Mean Square Algorithm Research Articles

Constrained Normalized Subband Adaptive Filter Algorithm and Its Performance Analysis

Constrained least mean square (CLMS) algorithm is the most popular constrained adaptive filtering algorithm due to its simple structure and easy implementation. However, its convergence slows down when the input signal is colored. To address this issue, this paper firstly introduces the normalized subband adaptive filter (NSAF) into the constrained filtering problem and derives a constrained NSAF (CNSAF) algorithm using the Lagrange multiplier method. Benefiting from the good decorrelation capability of the NSAF, the proposed CNSAF algorithm significantly improves the convergence performance of the CLMS algorithm under colored inputs. Then, the mean and mean-square stability of the CNSAF algorithm is analyzed, and the theoretical models to characterize the transient and steady-state mean square deviation (MSD) behaviors of the CNSAF algorithm are derived utilizing the Kronecker product property and vectorization method. Further to extend the CNSAF algorithm to the problem of sparse system identification, a sparse version of the CNSAF algorithm (S-CNSAF) is derived. Finally, the validity of the derived theoretical MSD prediction models and the superiority of the proposed algorithms are confirmed by extensive computer simulations on system identification with colored inputs.

Joint adaptive beamforming and perfect power control in wireless networks over power control error

In this paper, we use joint perfect power control (PPC) and adaptive beamforming algorithms as constrained least mean square (CLMS) and conjugate gradient adaptive beamforming (CGBF) in a 2D urban environment. The CLMS algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. In addition, with the CGBF algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference (IPI) is canceled in other paths in each RAKE finger. The adaptability of the algorithms is closely observed for uniformly spaced linear array. In addition, in this paper, we present switched-beam (SB) technique. In the SB technique by using a number of fixed, independent, or directional antennas we increase the uplink capacity of the wireless systems. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless communication systems. Simulation results indicate that the SB technique is able to considerably increase the signal to interference plus noise ratio (SINR) of desired user in comparison with other algorithms. In addition, we observe that the SINR in the CLMS algorithm is lower than the CGBF algorithm. Finally, we discuss two parameters of the PCE and path-loss exponent and their effects on capacity of the system via some computer. Keywords: Adaptive beamforming, Power control, Wireless networks

Joint Adaptive Beamforming and Perfect Power Control in Wireless Networks over Power Control Error

In this paper, we use joint perfect power control (PPC) and adaptive beamforming algorithms as constrained least mean square (CLMS) and conjugate gradient adaptive beamforming (CGBF) in a 2D urban environment. The CLMS algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. In addition, with the CGBF algorithm, the desired users' signal in an arbitrary path is passed and the inter-path interference (IPI) is canceled in other paths in each RAKE finger. The adaptability of the algorithms is closely observed for uniformly spaced linear array. In addition, in this paper, we present switched-beam (SB) technique. In the SB technique by using a number of fixed, independent, or directional antennas we increase the uplink capacity of the wireless systems. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless communication systems. Simulation results indicate that the SB technique is able to considerably increase the signal to interference plus noise ratio (SINR) of desired user in comparison with other algorithms. In addition, we observe that the SINR in the CLMS algorithm is lower than the CGBF algorithm. Finally, we discuss two parameters of the PCE and path-loss exponent and their effects on capacity of the system via some computer.

Tracking Mobile User through Adaptive Beamforming for Wireless Cellular Networks in a 2D Urban Environment

The interference reduction capability of array antennas and the power control (PC) algorithms have been considered separately as means to increase the capacity in wireless communication networks. The capability of the smart antenna systems to track the user with the main lobe and interference with the nulls creates a significant impact on the current and future wireless sensor networks. In this paper, we use constrained least mean square (CLMS) and conjugate gradient adaptive beam-forming (CGBF) algorithms for narrowband adaptive beam-forming for tracking mobile user in a 2D urban environment without using PC algorithm. The CLMS algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. In addition, with the CGBF algorithm, the desired users' signal in an arbitrary path is passed and the inter-path interference (IPI) is canceled in other paths in each RAKE finger. The adaptability of the algorithms is closely observed for uniformly spaced linear array. Also in this paper, we present switched-beam (SB) technique. In the SB technique by using a number of fixed, independent, or directional antennas we increase the uplink capacity of the wireless systems. Simulation results indicate that the SB technique is able to considerably increase the signal to interference plus noise ratio (SINR) of mobile user in comparison with other algorithms. In addition, we observe that the SINR in the CLMS algorithm is lower than the CGBF algorithm. Finally, we discuss perfect power control and path loss parameter in urban environments and their effects on system capacity by simulations.

Tracking mobile user through adaptive beamforming for wireless cellular networks in a 2D urban environment

The interference reduction capability of array antennas and the power control (PC) algorithms have been considered separately as means to increase the capacity in wireless communication networks. The capability of the smart antenna systems to track the user with the main lobe and interference with the nulls creates a significant impact on the current and future wireless sensor networks. In this paper, we use constrained least mean square (CLMS) and conjugate gradient adaptive beam-forming (CGBF) algorithms for narrowband adaptive beam-forming for tracking mobile user in a 2D urban environment without using PC algorithm. The CLMS algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. In addition, with the CGBF algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference (IPI) is canceled in other paths in each RAKE finger. The adaptability of the algorithms is closely observed for uniformly spaced linear array. Also in this paper, we present switched-beam (SB) technique. In the SB technique by using a number of fixed, independent, or directional antennas we increase the uplink capacity of the wireless systems. Simulation results indicate that the SB technique is able to considerably increase the signal to interference plus noise ratio (SINR) of mobile user in comparison with other algorithms. In addition, we observe that the SINR in the CLMS algorithm is lower than the CGBF algorithm. Finally, we discuss perfect power control and path loss parameter in urban environments and their effects on system capacity by simulations. Keywords: Antenna, Switched-beam, Power control, Urban signal propagation simulator, Wireless cellular network.

A constrained asymmetry LMS algorithm for PRML disk drive read channels

We present an implementation of a constrained least mean square (C-LMS) algorithm with application to high-speed magnetic disk drive read channels. The main advantage offered by the presented C-LMS algorithm is improved stability of the outer timing recovery loop while the spectral shaping of read-back data is performed in the inner adaptation loop. This eliminates any unstable behavior of the timing recovery loop during C-LMS algorithm adaptation. Another benefit derived from this approach is reduction in coefficient switching gradient noise. The proposed algorithm has been implemented and fabricated in a commercial read channel using a 0.18 /spl mu/m L-effective CMOS technology. It operates at 550 MHz worst case.

Analysis of constrained LMS algorithm with application to adaptive beamforming using perturbation sequences

Adaptive antenna array processing employing a constrained least mean square (LMS) algorithm requires an unbiased estimate of the gradient of the output power with respect to the array weights. There are a number of schemes for obtaining an unbiased estimate of this gradient. Though in each case the estimated gradient is unbiased, the covariance of the estimated gradient with each method is different and thus the transient and the steady state behavior of the constrained algorithm is different in each case. The transient and the steady state behavior of the weight covariancc matrix is analyzed, exact expressions for the misadjustment are derived, and a comparison of the performance of the algorithm is presented when the required gradient is estimated by different schemes. The schemes considered include gradient estimation when all the array signals are accessible as well as gradient estimation using perturbation sequences for eases when the array signals are inaccessible. The necessary and the sufficient condition for the diagonlization of the weight covarience matrix is also derived.