Efficient multiuser detector based on box-constrained dichotomous coordinate descent and regularization

The presented iterative multiuser detection technique was based on joint deregularized and box-constrained solution to quadratic optimization with iterations similar to that used in the nonstationary Tikhonov iterated algorithm. The deregularization maximized the energy of the solution, which was opposite to the Tikhonov regularization where the energy was minimized. However, combined with box-constraints, the deregularization forced the solution to be close to the binary set. It further exploited the box-constrained dichotomous coordinate descent algorithm and adapted it to the nonstationary iterative Tikhonov regularization to present an efficient detector. As a result, the worst-case and average complexity are reduced down as K28 and K25 floating point operation per second, respectively. The development improves the ＂efficient frontier＂ in multiuser detection, which is illustrated by simulation results. In addition, most operations in the detector are additions and bit-shifts, This makes the proposed technique attractive for fixed-point hardware implementation.