Name
Abstract | ||
|---|---|---|
A recently reported result on large/massive multiple-input multiple-output (MIMO) detection shows the utility of the branch and bound (BB)-based tree search approach for this problem. We can consider strong branching for improving upon this approach. However, that will require the solution of a large number of quadratic programs (QPs). We propose a likelihood based branching criteria to reduce the number of QPs required to be solved. We combine this branching criteria with a node selection strategy to achieve a better error performance than the reported BB approach, that too at a lower computational complexity. Simulation results show that the proposed algorithm outperforms the available detection algorithms for large MIMO systems. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LWC.2017.2702639 | IEEE Wireless Commun. Letters |
Keywords | Field | DocType |
MIMO,Search problems,Indexes,Measurement,Computational complexity,Antennas | Mimo systems,Branch and bound,Mathematical optimization,MIMO,Quadratic equation,Mathematics,Computational complexity theory,Branching (version control) | Journal |
Volume | Issue | ISSN |
6 | 4 | 2162-2337 |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saksham Agarwal | 1 | 0 | 0.34 |
| abhay kumar sah | 2 | 20 | 4.84 |
| Ajit Kumar Chaturvedi | 3 | 63 | 11.37 |