EM-based soft noncoherent equalization of doubly selective channels using tree search and basis expansion

2009 ◽  
Author(s):  
Sung-Jun Hwang ◽  
Philip Schniter
Keyword(s):  
Tree Search ◽  
Basis Expansion ◽  
Doubly Selective Channels

Estimation of Basis Expansion Models for doubly selective channels

2008 ◽  
Vol 25 (1) ◽  
pp. 115-119
Author(s):  
Yingnan Liu ◽  
Yonghui Gao ◽  
Nu Zhang ◽  
Qinglin Liang
Keyword(s):  
Basis Expansion ◽  
Doubly Selective Channels

Low Complexity Equalization for Doubly Selective Channels Modeled by a Basis Expansion

2010 ◽  
Vol 58 (11) ◽  
pp. 5706-5719 ◽  
Author(s):  
Tomasz Hrycak ◽  
Saptarshi Das ◽  
Gerald Matz ◽  
Hans G. Feichtinger
Keyword(s):  
Low Complexity ◽  
Basis Expansion ◽  
Doubly Selective Channels

scholarly journals Incorporation of Potential Fields and Motion Primitives for the Collision Avoidance of Unmanned Aircraft

2021 ◽  
Vol 11 (7) ◽  
pp. 3103
Author(s):  
Kyuman Lee ◽  
Daegyun Choi ◽  
Donghoon Kim
Keyword(s):  
Collision Avoidance ◽  
Search Algorithm ◽  
Unmanned Aircraft ◽  
Artificial Potential Field ◽  
Tree Search ◽  
Local Minima ◽  
Collision Risk ◽  
Motion Primitives ◽  
Multiple Uavs ◽  
Tree Search Algorithm

Collision avoidance (CA) using the artificial potential field (APF) usually faces several known issues such as local minima and dynamically infeasible problems, so unmanned aerial vehicles’ (UAVs) paths planned based on the APF are safe only in a certain environment. This research proposes a CA approach that combines the APF and motion primitives (MPs) to tackle the known problems associated with the APF. Since MPs solve for a locally optimal trajectory with respect to allocated time, the trajectory obtained by the MPs is verified as dynamically feasible. When a collision checker based on the k-d tree search algorithm detects collision risk on extracted sample points from the planned trajectory, generating re-planned path candidates to avoid obstacles is performed. After rejecting unsafe route candidates, one applies the APF to select the best route among the remaining safe-path candidates. To validate the proposed approach, we simulated two meaningful scenario cases—the presence of static obstacles situation with local minima and dynamic environments with multiple UAVs present. The simulation results show that the proposed approach provides smooth, efficient, and dynamically feasible pathing compared to the APF.

Sign in / Sign up

Export Citation Format

Share Document