Lattice basis reduction: improved practical algorithms and solving subset sum problems
Mathematical Programming: Series A and B
| Hi-index | 0.01 |
Suboptimal detectors of multiple-input multiple-output (MIMO) have been studied because the implementation of the optimum detector, the maximum-likelihood (ML) detector, has so far been considered infeasible for high-rate system. Sphere decoder (SD) using depth-first tree searching and K-best algorithm are used for near optimum detector. SD has the non-deterministic computational throughput and K-best requires the sorting unit whose complexity is significantly high when a large K is used together with high modulation constellation. In this paper, we propose a suboptimal MIMO detector employing Viterbi algorithm instead of tree searching. This detector can keep the computational throughput constant and reduce the complexity because the sorting is not required. In the simulation, we analyze the advantage and the drawback of the proposed detector in the environment of IEEE 802.11n system.