Energy Efficient and Reliable K Best Detection Approach with Hybrid Decomposition for WiMAX Applications

Abstract

SummaryK‐best detection algorithm placed a vital role for best signal detection in multi‐input multi‐output (MIMO) systems. The major challenge in K‐best approach is that, if the number of users increases, the preprocessing complexity also increases. To mitigate this limitations, CLD (Cholesky factorization + LDLT factorization)‐based decomposition process is proposed with sorted integer Gauss transformation (SIGT) to design 4 × 4 MIMO system. It limits the processing complexity by reducing the number of pipelining stages. Experimental results exhibit that the novel CLD‐based K‐best detector reduces power consumption by 33.52%, 16.29%, 25.65%, 9.6%, and 6.61% and increases the throughput by 69.62%, 68.84%, 62.61%, 4.73%, and 66.04% when compared with K‐best detector, modified K‐best detector, variable K‐best detector, low‐complexity K‐best, and K‐best with hybrid merge network. The proposed K‐best detection scheme increases the energy efficiency by 79.80%, 73.92%, 72.21%, 13.72%, and 68.28% when compared with the existing techniques such as K‐best detection, modified K‐best detection, variable K‐best, low‐complexity K‐best, and K‐best with hybrid merge network.