Overloaded Array Processing Using Genetic Algorithms With Soft-Biased Initialization

The application of genetic algorithm (GA) techniques to the problem of overloaded arrays, in which the number of transmitted narrowband signals is greater than the number of receiver array elements, is explored. A new receiver algorithm is presented, which achieves nearly optimal performance but requires significantly less complexity than the maximum-likelihood joint detection (MLJD) receiver. It uses GA techniques with soft-biased initialization, which is efficiently generated using spatial filtering, providing dramatic convergence improvements compared with other initialization schemes. Simulations using both idealized channel models and measured channel responses are used to investigate the impact of spatial correlation and imperfect channel state information (CSI).