Expected complexity analysis of increasing radii algorithm by considering multiple radius schedules

In this study, the authors investigate the expected complexity of increasing radii algorithm (IRA) in an independent and identified distributed Rayleigh fading multiple-input-multiple-output channel with additive Gaussian noise and then present its upper bound result. IRA employs several radii to yield significant complexity reduction over sphere decoding, whereas performing a near-maximum-likelihood detection. In contrast to the previous expected complexity presented by Gowaikar and Hassibi (2007), where the radius schedule was hypothetically fixed for analytic convenience, a new analytical result is obtained by considering the usage of multiple radius schedules. The authors analysis reflects the effect of the random variation in the radius schedule and thus provides a more reliable complexity estimation. The numerical results support their arguments, and the analytical results show good agreement with the simulation results.