DocumentCode :
3162955
Title :
Near-capacity MIMO Subspace Detection
Author :
Chen, Yejian ; Ten Brink, Stephan
Author_Institution :
Bell Labs., Alcatel-Lucent, Stuttgart, Germany
fYear :
2011
fDate :
11-14 Sept. 2011
Firstpage :
1733
Lastpage :
1737
Abstract :
This paper presents a low complexity detection algorithm for Multiple-Input Multiple-Output (MIMO) systems. The novel subspace approach involves QR Decomposition (QRD) or Cholesky decomposition to triangularize the effective channel matrix so that several (possibly overlapping) groups of data streams can be detected separately. Link layer simulations show that the ergodic MIMO capacity can be closely approached by exploiting an Overlapped Subspace Detection (OSD) strategy. The OSD algorithm offers a scalable performance/complexity trade-off between Zero-Forcing (ZF) and Maximum a posteriori Probability (APP) detection. The proposed algorithm can be straightforwardly applied to large MIMO systems, as prevalent with recent advances in the field such as network MIMO and Coordinated Multi-Point (CoMP) transmission and reception.
Keywords :
MIMO communication; communication complexity; matrix algebra; maximum likelihood estimation; probability; Cholesky decomposition; QR decomposition; channel matrix; coordinated multipoint reception; coordinated multipoint transmission; ergodic MIMO capacity; link layer simulation; low complexity detection algorithm; maximum a posteriori probability detection; multiple-input multiple-output system; near-capacity MIMO subspace detection; overlapped subspace detection strategy; zero-forcing; Complexity theory; Detection algorithms; MIMO; Matrix decomposition; Phase shift keying; Signal to noise ratio; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Personal Indoor and Mobile Radio Communications (PIMRC), 2011 IEEE 22nd International Symposium on
Conference_Location :
Toronto, ON
ISSN :
pending
Print_ISBN :
978-1-4577-1346-0
Electronic_ISBN :
pending
Type :
conf
DOI :
10.1109/PIMRC.2011.6139804
Filename :
6139804
Link To Document :
بازگشت