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GLOBALSOFT TECHNOLOGIES 
IEEE PROJECTS & SOFTWARE DEVELOPMENTS 
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE 
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS 
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com 
A Low-Complexity Algorithm for Neighbor Discovery 
in Wireless Networks 
ABSTRACT: 
We study a neighbor discovery problem in wireless networks for 
which each node wishes to identify the so-called neighboring nodes 
within a single-hop communication. This problem can be optimally 
addressed using maximum a posteriori (MAP) estimation, but its 
implementation is notoriously difficult in practice. In this letter, we 
present a low-complexity algorithm consisting of two stages: 1) we 
solve such problem using LASSO estimator that is a convex 
relaxation of MAP estimator to encourage a sparse solution; and 2) 
we find a desired binary vector (e.g., indicator of neighbor nodes) by 
taking a “hard-decision” with threshold, carefully chosen by 
exploiting fading statistics. Finally, we provide some numerical 
results to confirm that the proposed algorithm performs quite well.
SYSTEM REQUIREMENTS: 
HARDWARE REQUIREMENTS: 
 System : Pentium IV 2.4 GHz. 
 Hard Disk : 40 GB. 
 Floppy Drive : 1.44 Mb. 
 Monitor : 15 VGA Colour. 
 Mouse : Logitech. 
 Ram : 512 Mb. 
SOFTWARE REQUIREMENTS: 
 Operating system : Windows XP/7. 
 Coding Language : JAVA/J2EE 
 IDE : Netbeans 7.4 
 Database : MYSQL

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Low-Complexity Algorithm for Neighbor Discovery

  • 1. GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com A Low-Complexity Algorithm for Neighbor Discovery in Wireless Networks ABSTRACT: We study a neighbor discovery problem in wireless networks for which each node wishes to identify the so-called neighboring nodes within a single-hop communication. This problem can be optimally addressed using maximum a posteriori (MAP) estimation, but its implementation is notoriously difficult in practice. In this letter, we present a low-complexity algorithm consisting of two stages: 1) we solve such problem using LASSO estimator that is a convex relaxation of MAP estimator to encourage a sparse solution; and 2) we find a desired binary vector (e.g., indicator of neighbor nodes) by taking a “hard-decision” with threshold, carefully chosen by exploiting fading statistics. Finally, we provide some numerical results to confirm that the proposed algorithm performs quite well.
  • 2. SYSTEM REQUIREMENTS: HARDWARE REQUIREMENTS:  System : Pentium IV 2.4 GHz.  Hard Disk : 40 GB.  Floppy Drive : 1.44 Mb.  Monitor : 15 VGA Colour.  Mouse : Logitech.  Ram : 512 Mb. SOFTWARE REQUIREMENTS:  Operating system : Windows XP/7.  Coding Language : JAVA/J2EE  IDE : Netbeans 7.4  Database : MYSQL