Optimal Lattices for MIMO Precoding
(2011) IEEE International Symposium on Information Theory, 2011 p.29242928 Abstract
 Consider the communication model (y) over bar = H F (x) over bar + (n) over bar, where H; F are realvalued matrices, (x) over bar is a data vector drawn from some realvalued lattice (e.g. MPAM), (n) over bar is additive white Gaussian noise and (y) over bar is the received vector. It is assumed that the transmitter and the receiver have perfect knowledge of the channel matrix H (perfect CSI) and that the transmitted signal F (x) over bar is subject to an average energy constraint. The columns of the matrix H F can be viewed as basis vectors that span a lattice, and we are interested in the minimum distance of this lattice. More precisely, for a given H, which F under an average energy constraint will maximize the minimum distance of the... (More)
 Consider the communication model (y) over bar = H F (x) over bar + (n) over bar, where H; F are realvalued matrices, (x) over bar is a data vector drawn from some realvalued lattice (e.g. MPAM), (n) over bar is additive white Gaussian noise and (y) over bar is the received vector. It is assumed that the transmitter and the receiver have perfect knowledge of the channel matrix H (perfect CSI) and that the transmitted signal F (x) over bar is subject to an average energy constraint. The columns of the matrix H F can be viewed as basis vectors that span a lattice, and we are interested in the minimum distance of this lattice. More precisely, for a given H, which F under an average energy constraint will maximize the minimum distance of the lattice H F ? This particular question remains open within the theory of lattices. This work provides the solution for 2 x 2 matrices H; F. The answer is an F such that H F is a hexagonal lattice. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/record/2494443
 author
 Kapetanovic, Dzevdan ^{LU} ; Cheng, Hei Victor; Mow, Wai Ho and Rusek, Fredrik ^{LU}
 organization
 publishing date
 2011
 type
 Chapter in Book/Report/Conference proceeding
 publication status
 published
 subject
 host publication
 2011 IEEE International Symposium on Information Theory Proceedings (ISIT)
 pages
 2924  2928
 publisher
 IEEEInstitute of Electrical and Electronics Engineers Inc.
 conference name
 IEEE International Symposium on Information Theory, 2011
 conference location
 Saint Petersburg, Russian Federation
 conference dates
 20110731  20110805
 external identifiers

 wos:000297465103062
 scopus:80054811284
 ISBN
 9781457705953
 DOI
 10.1109/ISIT.2011.6034112
 language
 English
 LU publication?
 yes
 id
 7a35dda41c0b4ef1afa932b0cb2adc02 (old id 2494443)
 date added to LUP
 20120510 14:52:31
 date last changed
 20190730 03:31:16
@inproceedings{7a35dda41c0b4ef1afa932b0cb2adc02, abstract = {Consider the communication model (y) over bar = H F (x) over bar + (n) over bar, where H; F are realvalued matrices, (x) over bar is a data vector drawn from some realvalued lattice (e.g. MPAM), (n) over bar is additive white Gaussian noise and (y) over bar is the received vector. It is assumed that the transmitter and the receiver have perfect knowledge of the channel matrix H (perfect CSI) and that the transmitted signal F (x) over bar is subject to an average energy constraint. The columns of the matrix H F can be viewed as basis vectors that span a lattice, and we are interested in the minimum distance of this lattice. More precisely, for a given H, which F under an average energy constraint will maximize the minimum distance of the lattice H F ? This particular question remains open within the theory of lattices. This work provides the solution for 2 x 2 matrices H; F. The answer is an F such that H F is a hexagonal lattice.}, author = {Kapetanovic, Dzevdan and Cheng, Hei Victor and Mow, Wai Ho and Rusek, Fredrik}, isbn = {9781457705953}, language = {eng}, location = {Saint Petersburg, Russian Federation}, pages = {29242928}, publisher = {IEEEInstitute of Electrical and Electronics Engineers Inc.}, title = {Optimal Lattices for MIMO Precoding}, url = {http://dx.doi.org/10.1109/ISIT.2011.6034112}, year = {2011}, }