  The objective of this paper is to design optimal signature matrices for
binary inputs. For the determination of such optimal codes, we need certain
measures as objective functions. The sum-channel capacity and Bit Error Rate
(BER) measures are typical methods for the evaluation of signature matrices. In
this paper, in addition to these measures, we use distance criteria to evaluate
the optimality of signature matrices. The Genetic Algorithm (GA) and Particle
Swarm Optimization (PSO) are used to search the optimum signature matrices
based on these three measures (Sum channel capacity, BER and Distance). Since
the GA and PSO algorithms become computationally expensive for large signature
matrices, we propose suboptimal large signature matrices that can be derived
from small suboptimal matrices.
