Adaptive binary signature design for code-division multiplexing

When data symbols modulate a signature waveform to move across a channel in the presence of disturbance, the signature that maximizes the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum-SINR filter is the smallest-eigenvalue eigenvector of the disturbance autocovariance matrix. In digital communication systems the signature alphabet is finite and digital signature optimization is NP-hard. In this paper, we present a formal search procedure of cost, upon eigenvector decomposition, log-linear in the signature code length that returns the maximum-SINR binary signature vector near arcs of least SINR decrease from the real maximum SINR solution in the Euclidean vector space. The quality of the proposed adaptive binary designs is measured against the theoretical upper bound of the complex/real eigenvector maximizer.