A New Switched-beam Setup for Adaptive Antenna Array Beamforming
Journal Title: Journal of Information Systems and Telecommunication - Year 2016, Vol 4, Issue 1
Abstract
In this paper, a new spatio-temporal based approach is proposed which improves the speed and performance of temporal-based algorithms, conventional Least Mean Square (LMS), Normalized LMS (NLMS) and Variable Step-size LMS (VSLMS), by using the switched beam technique. In the proposed algorithm, first, DOA of the signal source is estimated by MUltiple SIgnal Classification (MUSIC) algorithm. In the second step, depending on the desired user's location, the closest beam of the switched beam system is selected and its predetermined weights are chosen as the initial values for the weight vector. Finally, LMS/NLMS/VSLMS algorithm is applied to initial weights and final weights are calculated. Simulation results show improved convergence and tracking speed and also a higher efficiency in data transmission through increasing the Signal to Interference plus Noise Ratio (SINR) as well as decreasing the Bit Error Rate (BER) and Mean Square Error (MSE), in a joint state. Moreover, Error Vector Magnitude (EVM) as a measure for distortion introduced by the proposed adaptive scheme on the received signal is evaluated for all LMS-based proposed algorithms which are approximately the same as that for conventional ones. In order to investigate the tracking capability of the proposed method, the system is assumed to be time varying and the desired signal location is considered once in the centre of the initial beam and once in the edge of the fixed beam. As depicted in simulation results, the proposed DOA-based methods offer beamforming with higher performance in both cases of the initial beam, centre as the best case and edge as the worst case, with respect to conventional ones. The MSE diagrams for this time varying system show an ideal response for DOA-based methods in the best case. Also, in the worst case, initial height of MSE is reduced and consequently the required iteration to converge is less than the conventional LMS/NLMS/VSLMS
Authors and Affiliations
Shahriar Shirvani Moghaddam, Farida Akbari
Prediction of Deadlocks in Concurrent Programs Using Neural Network
The dependability of concurrent programs is usually limited by concurrency errors like deadlocks and data races in allocation of resources. Deadlocks are difficult to find during the program testing because they happen u...
Simultaneous Methods of Image Registration and Super-Resolution Using Analytical Combinational Jacobian Matrix
In this paper we propose two new simultaneous image registration (IR) and super-resolution (SR) methods using a novel approach to calculate the Jacobian matrix. SR is the process of fusing several low resolution (LR) ima...
Hybrid Task Scheduling Method for Cloud Computing by Genetic and PSO Algorithms
Cloud computing makes it possible for users to use different applications through the internet without having to install them. Cloud computing is considered to be a novel technology which is aimed at handling and providi...
Enhancing Efficiency of Software Fault Tolerance Techniques in Satellite Motion System
This research shows the influence of using multi-core architecture to reduce the execution time and thus increase performance of some software fault tolerance techniques. According to superiority of N-version Programming...
Privacy Preserving Big Data Mining: Association Rule Hiding
Data repositories contain sensitive information which must be protected from unauthorized access. Existing data mining techniques can be considered as a privacy threat to sensitive data. Association rule mining is one of...