Name
Abstract | ||
|---|---|---|
In the case of memoryless MIMO channel and when the channel matrix is ill-conditioned, it is well known that performances of the Maximum Likelihood (ML) equalizer are well pronounced, compared to MMSE and ZF equalizers. In dispersive channels the conventional equalizer intends to cancel the inter-symbol interference, and did not take into the account the conditioning of the channel matrix. It intends to inverse the channel matrix somehow, which may cause noise enhancement and performances degradation. Using this fact and in order to overcome this issue, we propose in this paper a joint partial equalization and ML detection approach, where the equalizer is built based on a novel non-quadratic criterion. The proposed criterion ensures that the equalized channel matrix conserves its conditioning; which will be handled by the ML detector. Simulation results show that the improvement is well pronounced in cases where the channel matrix is ill-conditioned. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICTEL.2013.6632138 | Telecommunications |
Keywords | Field | DocType |
MIMO communication,least mean squares methods,matrix algebra,maximum likelihood estimation,radiofrequency interference,wireless channels,FIR MIMO channel equalization,ML detection approach,MMSE equalizers,ZF equalizers,channel matrix,dispersive channels,intersymbol interference,joint partial equalization,maximum likelihood equalizer,noise enhancement,nonquadratic criterion,Equalization,MIMO,ML,MMSE,conditioning,detection | Equalization (audio),Computer science,Matrix (mathematics),Control theory,MIMO,Communication channel,Symmetric matrix,Interference (wave propagation),Detector,Bit error rate | Conference |
ISBN | Citations | PageRank |
978-1-4673-6425-6 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hichem Besbes | 1 | 80 | 22.41 |
| Souha Ben Rayana | 2 | 0 | 0.34 |
| Ghaya Rekaya-Ben Othman | 3 | 24 | 5.55 |