In wireless communications the transmitted signals may be affected by noise. The receiver must decode the received message, which can be mathematically modelled as a search for the closest lattice point to a given vector. This problem is known to be NP-hard in general, but for communications applications there exist algorithms that, for a certain range of system parameters, offer polynomial expected complexity. The purpose of the thesis is to study the sphere decoding algorithm introduced in the article On Maximum-Likelihood Detection and the Search for the Closest Lattice Point, which was published by M.O. Damen, H. El Gamal and G. Caire in 2003. We concentrate especially on its computational complexity when used in space–time coding. C...
In many communications problems, maximum-likelihood (ML) decoding reduces to nding the closest (skew...
It is well known that maximum-likelihood (ML) decoding in many digital communication schemes reduces...
International audienceTo reduce the decoding complexity of linearly precoded MIMO systems, the spher...
In Part 1, we found a closed-form expression for the expected complexity of the sphere-decoding algo...
The problem of finding the least-squares solution to a system of linear equations where the unknown ...
The exact average complexity analysis of the basic sphere decoder for general space-time codes appli...
Most of the calculations in standard sphere decoders are redundant in the sense that they either cal...
In many communications problems, maximum-likelihood (ML) decoding reduces to finding the closest (sk...
Maximum-likelihood (ML) decoding often reduces to finding the closest (skewed) lattice point in N-d...
Maximum-likelihood (ML) decoding often reduces to solving an integer least-squares problem, which is...
The problem of finding the least-squares solution to a system of linear equations where the unknown ...
An insight on the lattice decoder for flat-fading multiple antenna wireless communications systems i...
International audienceIn this paper, Sphere Decoding (SD) algorithms for Spatial Modulation (SM) are...
ISBN: 978-1-4244-2515-0International audienceIt has been widely shown that the Sphere Decoding can b...
In many communications problems, maximum-likelihood (ML) decoding reduces to nding the closest (skew...
It is well known that maximum-likelihood (ML) decoding in many digital communication schemes reduces...
International audienceTo reduce the decoding complexity of linearly precoded MIMO systems, the spher...
In Part 1, we found a closed-form expression for the expected complexity of the sphere-decoding algo...
The problem of finding the least-squares solution to a system of linear equations where the unknown ...
The exact average complexity analysis of the basic sphere decoder for general space-time codes appli...
Most of the calculations in standard sphere decoders are redundant in the sense that they either cal...
In many communications problems, maximum-likelihood (ML) decoding reduces to finding the closest (sk...
Maximum-likelihood (ML) decoding often reduces to finding the closest (skewed) lattice point in N-d...
Maximum-likelihood (ML) decoding often reduces to solving an integer least-squares problem, which is...
The problem of finding the least-squares solution to a system of linear equations where the unknown ...
An insight on the lattice decoder for flat-fading multiple antenna wireless communications systems i...
International audienceIn this paper, Sphere Decoding (SD) algorithms for Spatial Modulation (SM) are...
ISBN: 978-1-4244-2515-0International audienceIt has been widely shown that the Sphere Decoding can b...
In many communications problems, maximum-likelihood (ML) decoding reduces to nding the closest (skew...
It is well known that maximum-likelihood (ML) decoding in many digital communication schemes reduces...
International audienceTo reduce the decoding complexity of linearly precoded MIMO systems, the spher...