PROJECT TITLE :
Lower Bound on Expected Complexity of Depth-First Tree Search with Multiple Radii
Depth-first tree search with multiple radii (DFTS-MR) algorithm attains significant complexity reduction over DFTS with one radius (DFTS-SR) for solving integer least-squares (ILS) problems. Herein, we derive the lower sure on the expected complexity of DFTS-MR beneath i.i.d. complex Gaussian environments. Currently, the higher sure on the expected DFTS-MR complexity is understood. Our analytical result shows the computational dependence on the statistics of the channel, the noise, and the transmitted symbols. It conjointly reflects the utilization of multiple radii, which is one in every of the main characteristics of DFTS-MR. The resultant lower bound provides an economical means to higher understand the complexity behavior of DFTS-MR, together with the (known) upper certain.
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