Performance Comparison between MAI and Noise Constrained LMS Algorithm for MIMO CDMA DFE and Linear Equalizers

Abstract

This paper presents a performance comparison between a constrained least mean squared algorithm for MIMO CDMA decision feedback equalizer and linear equalizer. Both algorithms are constrained on the length of spreading sequence, number of users, variance of multiple access interference as well as additive white Gaussian noise (new constraint). An important feature of both algorithms is that multiple access interference together with noise variance is used as a constraint in MIMO CDMA linear and decision feedback equalization systems. Convergence analysis is performed for algorithm in both cases. From the simulation results shown at the end show that algorithm developed for decision feedback equalizer has outperformed the algorithm developed for linear equalizer in MIMO CDMA case

Authors and Affiliations

Khalid Mahmood

Keywords

Related Articles

Forensic Analysis of Docker Swarm Cluster using Grr Rapid Response Framework

An attack on Internet network does not only hap-pened in the web applications that are running natively by a web server under operating system, but also web applications that are running inside container. The currently p...

13: 32 x 10 and 64 × 10 Gb/s transmission using hybrid Raman-Erbium doped optical amplifiers

We have successfully demonstrated a long-haul transmission of 32 × 10 Gbit/s and 64 × 10 Gbit/s over single-mode fiber of 650 km and 530 km respectively by using RAMAN-EDFA hybrid optical amplifier as inline and preampli...

Analysis of the Impact of Different Parameter Settings on Wireless Sensor Network Lifetime

The importance of wireless sensors is increasing day by day due to their large demand. Sensor networks are facing some issues in which battery lifetime of sensor node is critical. It depends on the nature and application...

Automatic Cyberbullying Detection in Spanish-language Social Networks using Sentiment Analysis Techniques

Cyberbullying is a growing problem in our society that can bring fatal consequences and can be presented in digital text for example at online social networks. Nowadays there is a wide variety of works focused on the det...

Urdu Text Classification using Majority Voting

Text classification is a tool to assign the predefined categories to the text documents using supervised machine learning algorithms. It has various practical applications like spam detection, sentiment detection, and de...

Download PDF file
  • EP ID EP397399
  • DOI 10.14569/IJACSA.2016.071253
  • Views 89
  • Downloads 0

How To Cite

Khalid Mahmood (2016). Performance Comparison between MAI and Noise Constrained LMS Algorithm for MIMO CDMA DFE and Linear Equalizers. International Journal of Advanced Computer Science & Applications, 7(12), 405-410. https://europub.co.uk/articles/-A-397399