Reduced-complexity sphere decoding algorithm based on adaptive radius in each dimension

Sphere Decoding (SD) algorithm was proposed to effectively find the Maximum Likelihood (ML) solution. However, the computational complexity of SD is still too high when SNR is low or the dimension of the problem is large. In this paper, we propose three improved schemes based on contraction factor to reduce the complexity of sphere decoding. In the proposed schemes, a factor was introduced for speeding up contraction of sphere radius in each layer of the searching tree, and the contraction factor was controlled by signal to noise ratio (SNR), layer of the search tree and both of SNR and layer, respectively. The simulation results show that contrasting to traditional SD, the improved SD algorithms based on contraction factor has much lower decoding complexity with negligible performance degradation.