Open AccessPerformance Analysis of Layer Pruning on Sphere Decoding in MIMO Systems
Author(s) -
Karthikeyan Madurakavi,
Saraswady D.
Publication year - 2014
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.14.0113.1182
Subject(s) - decoding methods , pruning , reduction (mathematics) , mimo , algorithm , tree (set theory) , probabilistic logic , mathematics , computational complexity theory , layer (electronics) , signal to noise ratio (imaging) , search tree , computer science , process (computing) , simple (philosophy) , search algorithm , channel (broadcasting) , statistics , telecommunications , combinatorics , chemistry , geometry , philosophy , organic chemistry , epistemology , agronomy , biology , operating system
Sphere decoding (SD) for multiple‐input and multiple‐output systems is a well‐recognized approach for achieving near‐maximum likelihood performance with reduced complexity. SD is a tree search process, whereby a large number of nodes can be searched in an effort to find an estimation of a transmitted symbol vector. In this paper, a simple and generalized approach called layer pruning is proposed to achieve complexity reduction in SD. Pruning a layer from a search process reduces the total number of nodes in a sphere search. The symbols corresponding to the pruned layer are obtained by adopting a QRM‐MLD receiver. Simulation results show that the proposed method reduces the number of nodes to be searched for decoding the transmitted symbols by maintaining negligible performance loss. The proposed technique reduces the complexity by 35% to 42% in the low and medium signal‐to‐noise ratio regime. To demonstrate the potential of our method, we compare the results with another well‐known method — namely, probabilistic tree pruning SD.