IEEE 2014 NS2 NETWORKING PROJECTS Selective interference alignment for mimo cognitive fem to cell networks

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Text of IEEE 2014 NS2 NETWORKING PROJECTS Selective interference alignment for mimo cognitive fem to cell...

  • 1. GLOBALSOFT TECHNOLOGIESIEEE PROJECTS & SOFTWARE DEVELOPMENTSIEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEEBULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTSCELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.comSelective Interference Alignment for MIMO Cognitive Fem tocell NetworksAbstractThis paper presents a novel cross-tier interference management solution for coexisting two-tiernetworks by exploiting cognition and coordination between tiers via the use of agileradios. The cognitive users sense their environment to determine the receivers they areinterfering with, and adapt to it by designing their precoders using interference alignment(IA) in order to avoid causing performance degradation to nearby receivers. The proposedapproach judiciously chooses the set of users to be aligned at each receiver as a subset ofthe cross-tier interferers, hence is termed selective IA. The proposed solution includesidentification of the subspace in which cross-tier interference signals would be alignedfollowed by a distributed algorithm to identify the precoders needed at the selectedinterferers. The intra-tier interference is then dealt with using minimum mean squared error(MMSE) interference suppression. Numerical results demonstrate the effectiveness ofselective IA for both uplink and downlink interference management.Existing systemThis paper presents a novel cross-tier interference management solution for coexisting two-tiernetworks by exploiting cognition and coordination between tiers via the use of agileradios. The cognitive users sense their environment to determine the receivers they areinterfering with, and adapt to it by designing their precoders using interference alignment(IA) in order to avoid causing performance degradation to nearby receivers. The proposed

2. approach judiciously chooses the set of users to be aligned at each receiver as a subset ofthe cross-tier interferers, hence is termed selective IA.Proposed systemThe proposed solution includes identification of the subspace in which cross-tierinterference signals would be aligned followed by a distributed algorithm to identify theprecoders needed at the selected interferers. The intra-tier interference is then dealt withusing minimum mean squared error (MMSE) interference suppression. Numerical resultsdemonstrate the effectiveness of selective IA for both uplink and downlink interferencemanagement.SYSTEM CONFIGURATION:-HARDWARE CONFIGURATION:- Processor - Pentium IV Speed - 1.1 Ghz RAM - 256 MB(min) Hard Disk - 20 GB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGASOFTWARE CONFIGURATION:- Operating System : Windows XP Programming Language : JAVA Java Version : JDK 1.6 & above.