Unified low-complexity decision feedback equalizer with adjustable double radius constraint

The maximum likelihood sequence estimation (MLSE) is an optimal equalization method to suppress Inter-Symbol Interference (ISI) in communication and storage systems. The Viterbi Algorithm (VA) provides an exact solution of MLSE. To reduce the complexity of VA, MLSE-DFE, which combines the VA within a decision feedback equalizer (DFE), is widely used in practical designs; however, the computing complexity is still too high. In this paper, we propose the SDVA-DFE, a unified DFE combining the concept of sphere detector (SD) and VA. The computing complexity of the SDVA-DFE can be reduced by proposed double radius constraints, upper radius (UR) and lower radius (LR). By adjusting the values of the two radiuses, the SDVA-DFE also provides a trade-off between performance and complexity. Simulation shows that this method is suitable for high-order modulation and long-length channel impulse response. When applied to a Lorentzian channel and channels of different eigenvalue spread, the SDVA-algorithm can reduce the complexity by over 90% at high SNR compared with MLSE-DFE.