Name
Abstract | ||
|---|---|---|
The Cayley unitary (CU) codes constitute a systematic way of constructing unitary space-time modulations for noncoherent MIMO communications. For MIMO systems employing CU codes, there is no explicit expression for block (or bit) error probabilities. Hence, deterministic optimization tools cannot be employed to design the optimal CU codes. In this work, we propose to optimize the design of CU codes through simulation-based optimization techniques, in particular, stochastic approximation together with gradient estimation. The proposed methodology can be employed to design optimal CU codes under the maximum likelihood decoding or the suboptimal linearized sphere decoding. Simulation results show that new CU codes obtained by the proposed design significantly outperform those in the literature designed by minimizing the expected distance between codeword pairs. The new CU codes also enjoy comparable performance over training-based designs. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/TWC.2006.1673105 | Wireless Communications, IEEE Transactions |
Keywords | Field | DocType |
cayley unitary code optimal design,noncoherent cayley unitary space-time,maximum likelihood decoding,error probabilities,stochastic processes,simulation-based optimization techniques,space-time modulations,linear codes,approximation theory,mimo systems,bit error probability,modulation,deterministic optimization tool,new cu code,noncoherent mimo communications,optimum design,estimation theory,unitary space-time modulation,gradient estimation,stochastic approximation,mimo communication,noncoherent mimo communication,gradient methods,suboptimal linearized sphere decoding,optimal cu code,cu code,training-based design,space-time codes,noncoherent space-time codes,error statistics,proposed methodology,noncoherent cayley unitary space-time codes,radiocommunication,proposed design,mimo system,error probability,design optimization,mimo,indexing terms,space time code,fading | BCJR algorithm,Concatenated error correction code,Block code,Simulation-based optimization,MIMO,Algorithm,Theoretical computer science,Real-time computing,Linear code,Decoding methods,Stochastic approximation,Mathematics | Journal |
Volume | Issue | ISSN |
5 | 7 | 1536-1276 |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jibing Wang | 1 | 63 | 9.68 |
| Xiaodong Wang | 2 | 3958 | 310.41 |
| Mohammad Madihian | 3 | 0 | 0.34 |